system

Abstract

Provide a system. A system includes: a means for receiving a file of a system product; a means for analyzing the received file; means for generating a specification document based on the analysis results; a means for providing the generated specification document to a user; A system including:

Description

[Technical Field]

[0001] The technology of the present disclosure relates to a system. [Background technology]

[0002] Patent document 1 discloses a persona chatbot control method performed by at least one processor, the method including the steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to a description of the chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Publication No. 2022-180282 Summary of the Invention [Problem to be solved by the invention]

[0004] When the specifications of an existing system product are unknown, it often causes problems in its operation and maintenance. Specifically, it becomes difficult to understand the system's behavior, fix defects, and evaluate security risks. In such situations, a huge amount of time and effort is required to understand the details of the system, and an efficient method is required. [Means for solving the problem]

[0005] The present invention solves these problems by providing a system that includes a means for receiving a system product file, a means for analyzing the received file, a means for generating a specification document based on the analysis results, and a means for providing the generated specification document to a user. Furthermore, by adding a means for decompiling the received file and a means for performing static analysis of the system based on the analysis results, it is possible to efficiently understand the detailed specifications of the system product. This significantly improves the efficiency of system operation and maintenance.

[0006] A "system product" generally refers to a product that is a collection of software, hardware, etc., and is designed to provide that function.

[0007] A "file" is a container for storing information in digital form, used to store specific data or programs.

[0008] "Means for receiving" refers to the mechanism or process for receiving user-provided data.

[0009] "Analysis tools" refers to the methods and tools used to examine data and understand its internal structure and behavior.

[0010] "Decompilation" refers to the process of converting binary or intermediate form program code into high-level source code.

[0011] A "specification document" is a document that contains detailed information about the design and operation of a system, making it easier to understand and manage the system.

[0012] "Means of generation" refers to the method or process for creating a document in a specific format based on information such as analysis results.

[0013] "Static analysis" refers to a method for examining the structure and properties of code without executing the program.

[0014] "Means for providing to users" refers to the mechanism by which generated data and documentation is distributed in a form accessible to users. [Brief explanation of the drawings]

[0015] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0016] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0017] First, the terms used in the following description will be explained.

[0018] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0019] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0020] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0021] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0022] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0023] [First embodiment]

[0024] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0025] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0026] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0027] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0028] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0029] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0030] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0031] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0032] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0033] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0034] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0035] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0036] The present invention relates to a system that automatically analyzes a system product and generates a specification document when the specifications of the system product are unknown. This system is designed so that a user can upload the system product and ultimately obtain the automatically generated specification document.

[0037] A specific embodiment for implementing the system will be described below.

[0038] File upload procedure

[0039] A user selects a system product file from their device and uploads it to the server through a dedicated website or application. For example, a user selects a file called "Software A.exe" and sends it to the server. In this step, it is important that the file is sent correctly to the server.

[0040] Initial analysis of the file

[0041] The server stores the system product file received from the user in temporary storage and performs an initial analysis to determine the file type and structure. For example, it identifies that the received "Software A.exe" is an executable file and its structural physical characteristics. At this stage, the file's metadata and header information are analyzed.

[0042] Decompiling and Parsing

[0043] The server then selects an appropriate decompiler to decompile the received file. The decompilation process converts binary code or intermediate code into high-level source code. For example, the server converts the binary code extracted from "Software A.exe" into C++ source code, revealing the code's logic and internal structure.

[0044] The server then uses static analysis tools to analyze the decompiled source code. This analysis clarifies the function call relationships and inter-module dependencies in the source code. If necessary, dynamic analysis is also performed to observe runtime behavior, thereby obtaining operational characteristics that cannot be determined by static analysis alone.

[0045] Generate specification documents

[0046] Based on the analysis results, the server automatically generates a specification document, which contains detailed information such as the system overview, module configuration, function roles, and library dependencies. For example, the generated document might explain what libraries "Software A" uses and how each module works together.

[0047] Providing results

[0048] Finally, the server provides the generated specification document to the user. Specifically, it provides the user with a download link that the user can click to download the document. This download link is designed to be provided to the user safely and easily.

[0049] By going through the above process, users can obtain detailed specification documents of the original system product and use them for its operation and maintenance. This invention enables efficient system analysis and document generation, achieving a significant reduction in time and effort compared to conventional manual analysis work.

[0050] The processing flow will be explained below.

[0051] Step 1: Select the file

[0052] The user selects the file of the system product that he / she wants to reverse engineer on the terminal. For example, the user selects "Software A.exe".

[0053] Step 2: Uploading files

[0054] The user uploads the selected file to the server by clicking the "Upload" button on a dedicated website or application, and the device sends the file to the server.

[0055] Step 3: Receive the file

[0056] The server receives the file sent from the device and stores it in temporary storage. The server then verifies that the file was received correctly.

[0057] Step 4: Initial analysis

[0058] The server performs an initial analysis of the received file to determine its type and structure, checking metadata and header information to determine whether the file is an executable or library.

[0059] Step 5: Decompile

[0060] The server selects the appropriate decompiler based on the format of the file. The decompiler is used to convert the binary code into high-level source code, for example, converting "Software A.exe" into C++ source code.

[0061] Step 6: Static Analysis

[0062] The server analyzes the decompiled source code using static analysis tools to identify the code structure, function call relationships, and module dependencies.

[0063] Step 7: Dynamic analysis (if necessary)

[0064] The server emulates the execution environment of the software based on a specific scenario or use case, and uses debugging and monitoring tools to observe its behavior at runtime.

[0065] Step 8: Generate the specification document

[0066] The server automatically generates a system specification document based on the results of static and dynamic analysis, which contains detailed information such as module configuration, function roles, and library dependencies.

[0067] Step 9: Saving the Document

[0068] The server stores the generated specification document in a storage and makes it accessible to users.

[0069] Step 10: Generate a download link

[0070] The server generates a download link to the saved specification document and provides it to the user, who then downloads the document via this link.

[0071] Step 11: Retrieving Documents

[0072] The user clicks on the download link provided by the server to download the generated specification document to the terminal.

[0073] Example 1

[0074] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0075] In conventional systems, when the specifications of a system product are unknown, analyzing it and generating specification documents requires a significant amount of time and effort. Furthermore, because the analysis work is performed manually, the analysis results often lack accuracy and consistency. Therefore, there is a demand for an automated analysis system that can quickly and accurately obtain detailed system product specifications and use them for operation and maintenance.

[0076] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0077] In this invention, the server includes means for receiving an uploaded system product file, means for initially analyzing metadata and header information of the received file, means for decompiling the file based on the analysis results, means for statically analyzing the decompiled code, means for performing dynamic analysis based on the static analysis results, means for integrating the dynamic analysis results to generate a specification document, and means for providing the generated specification document to a user, thereby enabling detailed specifications of the system product to be obtained quickly and accurately.

[0078] "Uploading" is the act of a user sending a data file from their computer or device to a remote system such as a server or cloud service.

[0079] A "system product" is a software or hardware product that is designed to have specific functions and capabilities and is provided for use by users.

[0080] "File metadata" is information that is not contained in the file itself but that describes its contents and characteristics, such as the file's creation date and time, size, and author information.

[0081] "Header information" is data at the beginning of a file that defines the file's type, structure, and other important attributes.

[0082] "Initial analysis" is the initial analysis process for understanding the basic attributes and structure of received data or files.

[0083] "Decompilation" is the process of converting program code written in machine language or intermediate language into source code in a high-level language.

[0084] "Static analysis" is a technique for analyzing a program's code to find errors, potential bugs, and security vulnerabilities without running the program.

[0085] "Dynamic analysis" is a technique for analyzing problems and operating characteristics by observing the behavior and performance of a program while it is being executed.

[0086] A "specification document" is a technical document that describes in detail the structure, functions, operating conditions, dependencies, etc. of a system or software product.

[0087] "Providing" means preparing and making available a particular service or product so that it can be easily accessed by users.

[0088] This invention relates to a system that automatically analyzes a system product and generates a specification document when the specifications of the system product are unknown. This system is designed so that a user can upload the system product and ultimately obtain the automatically generated specification document.

[0089] A specific embodiment for implementing the system will be described below.

[0090] File upload procedure

[0091] The user selects the system product file from their device and uploads it to the server via a dedicated website or application. Specifically, the user opens a browser, accesses the target site, clicks the "Upload" button to display a file selection dialog, selects the file to be analyzed (e.g., "Software A.exe"), and clicks the "Submit" button again to begin uploading.

[0092] Initial analysis of the file

[0093] The server stores the file uploaded by the user in temporary storage and performs an initial analysis to determine the file's type and structure. During this stage, the server analyzes the file's metadata (e.g., creation date and file size) and header information (e.g., file format and entry point). Based on this, the server can determine that the file is an executable file and the platform it is intended for.

[0094] Decompilation and Static Analysis

[0095] The server uses a decompiler such as Ghidra or IDA Pro to decompile the file, converting the binary code into high-level source code that can be understood by humans. For example, the binary code for "Software A.exe" is converted into C++ source code. The server then performs static analysis using SonarQube or Cppcheck. Specifically, the server analyzes the code's function call relationships, inter-module dependencies, variable usage, and other aspects to identify code quality and security issues.

[0096] Dynamic Analysis

[0097] If necessary, the server performs dynamic analysis. Using tools such as Valgrind or QEMU, the server runs the program to be analyzed and observes its operating characteristics. Specifically, the server monitors the program's memory usage, CPU usage, and frequency of I / O operations to detect bugs or abnormal behavior that occur during execution. This allows the server to understand operating characteristics that cannot be determined by static analysis alone.

[0098] Generate specification documents

[0099] Based on the analysis results, the server automatically generates a specification document. This document contains detailed information such as an overview of the system, module configuration, function roles, and library dependencies. The server uses a text generation engine to generate a document describing the analysis results in natural language. Diagrams and tables are also added to this document to make the content easier to understand visually.

[0100] Providing results

[0101] Finally, the server provides the generated specification document to the user. Specifically, the server generates a download link for the user and sends a notification email containing the link. The user can easily download the document by clicking the link. This download link is secure and designed to be user-friendly.

[0102] As a concrete example, the following scenario can be considered.

[0103] If a user has a file called "SoftwareB.exe" that they want to analyze, they can use a prompt statement like this:

[0104] "Please upload the following file and automatically generate its specification document: Software B.exe"

[0105] Through these efforts, users can quickly and accurately obtain detailed specification documents and use them for operation and maintenance. This system significantly reduces the time and effort required compared to conventional manual analysis work.

[0106] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0107] Step 1: Upload a file

[0108] The user selects a system product file from their device and uploads it to the server via a dedicated website or application. Specifically, the user opens a browser, accesses the target site, and clicks the "Upload" button to display a file selection dialog. Next, the user selects the file to be analyzed, such as "Software A.exe," and clicks the "Submit" button again to begin uploading. The input is the target file on the user's device, and the output is the uploaded file saved on the server.

[0109] Step 2: Initial analysis of the file

[0110] The server stores the file uploaded by the user in temporary storage and performs an initial analysis to determine the file's type and structure. Specifically, the server analyzes the file's metadata (e.g., creation date and time, file size) and header information (e.g., file format, entry point). The input is the uploaded file, and the output is the analysis results, including the file's metadata and header information.

[0111] Step 3: Decompile

[0112] The server decompiles the file using an appropriate decompiler (e.g., Ghidra, IDA Pro) and converts the binary code into high-level source code that can be understood by humans. Specifically, the server converts the binary code of "Software A.exe" into C++ source code. The input is a file containing the initial analysis results, and the output is the decompiled source code.

[0113] Step 4: Static Analysis

[0114] The server uses a static analysis tool (e.g., SonarQube, Cppcheck) to analyze the decompiled source code. Specifically, the server analyzes the code's function call relationships, inter-module dependencies, variable usage, etc. to identify code quality and security issues. The input is the decompiled source code, and the output is the static analysis results.

[0115] Step 5: Dynamic Analysis

[0116] If necessary, the server performs dynamic analysis. Using a dynamic analysis tool (e.g., Valgrind or QEMU), the server executes the program to be analyzed and observes its operating characteristics. Specifically, the server monitors the program's memory usage, CPU usage, and frequency of I / O operations to detect bugs or abnormal behavior that occur during execution. The input is the static analysis results and decompiled source code, and the output is the dynamic analysis results.

[0117] Step 6: Generate the specification document

[0118] The server automatically generates a specification document based on the analysis results. Specifically, the server uses a text generation engine to generate a document that details the system overview, module configuration, function roles, library dependencies, etc. This document also includes diagrams and tables. The input is the static and dynamic analysis results, and the output is a specification document.

[0119] Step 7: Delivering the results

[0120] The server provides the generated specification document to the user. Specifically, the server generates a download link for the user and sends a notification email containing this link. The user can easily download the document by clicking the link. The input is the specification document, and the output is providing the download link to the user.

[0121] This system allows users to quickly and accurately obtain detailed specification documents and use them for operation and maintenance.

[0122] (Application example 1)

[0123] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0124] Factory robots have complex software systems, and analyzing them and creating specification documents requires a great deal of effort and time. Furthermore, when detailed analysis of unknown system products is required, conventional methods are inefficient and may hinder production efficiency. Furthermore, accurately understanding software functions and dependencies requires advanced expertise. To solve these problems, a system is needed that can easily and quickly analyze software and automatically generate specification documents.

[0125] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0126] In this invention, the server includes means for receiving a system product file, means for analyzing the received file, means for generating a specification document based on the analysis results, means for providing the generated specification document to a user, means for analyzing the factory robot software, means for static analysis for extracting software functions and dependencies, and means for providing the generated specification document in PDF format, thereby enabling a user to easily and quickly analyze the factory robot software and obtain the results as a detailed specification document.

[0127] "System product file" means an electronic file containing software or program code for a factory robot.

[0128] "Analyzing" refers to the process of analyzing the contents and structure of a file in detail using analytical tools.

[0129] A "specification document" is a document created based on the analysis results that describes the functions and dependencies of the factory robot software.

[0130] "Providing to users" refers to the process of providing the generated specification document to users in a form that is easily accessible to them.

[0131] "Factory robot" is a general term for robots used in automated factories.

[0132] A "software function" is a set of operations or calculations performed by a factory robot's software.

[0133] "Dependencies" refer to the relationships between libraries and modules that are required for software to function.

[0134] "Static analysis" is a technique for analyzing software structure, code functions, dependencies, etc. without running the software.

[0135] "PDF format" is an abbreviation for Portable Document Format, and is a file format for saving and displaying specification documents in a visually easy-to-read format.

[0136] The present invention provides a system that allows a user to upload a software file for a factory robot, analyzes the file on a server, and automatically generates a detailed specification document. Specific embodiments are described below.

[0137] System Program

[0138] The program of this system consists of the following major components:

[0139] 1. File upload interface

[0140] An interface for users to upload factory robot software files, which can be provided as a smartphone application or web application.

[0141] 2. Initial Analysis Module

[0142] The server receives the uploaded file and analyzes the file type and structure.

[0143] 3. Decompilation Module

[0144] It decompiles the received files, converting the binary code into high-level source code.

[0145] 4. Static Analysis Module

[0146] It analyzes decompiled source code and extracts software functions and dependencies.

[0147] 5. Document Generation Module

[0148] Based on the analysis results, a detailed specification document is automatically generated in PDF format.

[0149] 6. Result Delivery Module

[0150] Provide the generated specification document to the user and send a download link.

[0151] Natural language explanations

[0152] First, a user uses a smartphone or computer to upload the factory robot's software file to the server via a dedicated interface. The server first stores the received file in temporary storage. Next, the initial analysis module analyzes the file type and structure. For example, if a file named "RobotControlV2.0.exe" is received, it will identify it as an executable file. This analysis uses metadata and file header information.

[0153] Next, the decompilation module uses a decompiler tool to convert the file into high-level source code, for example, C++ source code, and the static analysis module analyzes the source code for functions and dependencies, extracting functions and libraries such as "function1" and "lib1."

[0154] Based on these analysis results, the document generation module automatically generates a specification document in PDF format. Finally, the generated specification document is provided to the user as a download link via the result provision module.

[0155] Specific examples

[0156] For example, if a factory production manager needs to analyze the software for a factory robot called "RobotControlV2.0.exe" and find out the detailed specifications of the libraries and internal modules it uses, he or she might enter the following prompt into the system:

[0157] Analyze the factory robot software "RobotControlV2.0.exe" and generate a detailed specification document of the libraries and internal modules it uses. The following file was uploaded from a smartphone.

[0158] This invention enables users to efficiently and accurately analyze factory robot software and obtain detailed specification documents without requiring specialized knowledge, significantly improving factory production and maintenance efficiency.

[0159] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0160] Step 1:

[0161] The user uploads the factory robot's software file to the server through a dedicated interface. As input, the user selects the executable file "RobotControlV2.0.exe" on their smartphone or computer and presses the upload button. This action sends the file to the server. As output, the file is accurately saved in temporary storage on the server side.

[0162] Step 2:

[0163] The server passes the received file to the initial analysis module, which analyzes the file type and structure. As input, the uploaded "RobotControlV2.0.exe" file is provided. The server reads the file header and metadata and identifies it as an executable file. As output, the file type and basic structure information are obtained.

[0164] Step 3:

[0165] The server uses a decompilation module to convert the parsed files into high-level source code. As input, it is provided with the binary code of the executable file "RobotControlV2.0.exe". The server runs the decompiler tool and converts the binary code into "C++" source code. As output, it gets the decompiled high-level source code.

[0166] Step 4:

[0167] The server uses a static analysis module to analyze the decompiled source code and extract software functions and dependencies. As input, the decompiled source code is provided. The server runs a static code analysis tool to extract function definitions (e.g., "function1", "function2") and dependent libraries (e.g., "lib1", "lib2"). As output, the functionality and dependency information of the source code is obtained.

[0168] Step 5:

[0169] The server uses a document generation module to automatically generate a specification document in PDF format based on the analysis results. The analysis results of the software's functions and dependencies are provided as input. The server uses a PDF generation library (e.g., ReportLab) to generate a PDF document containing the software's detailed specifications. The output is a specification document in PDF format.

[0170] Step 6:

[0171] The server provides the generated specification document to the user through the result delivery module and sends a download link. The generated PDF document is provided as input. The server generates a secure download link and displays it on the user's interface or sends it by email. The user can then download the specification document by clicking the provided download link. As output, the user gets a specification document that details the analysis results.

[0172] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0173] This invention relates to a system that automatically analyzes a system product and generates specification documents when the specifications are unknown. Furthermore, by combining it with an emotion engine that recognizes the user's emotions, it aims to improve the user experience. This system automates the entire process from receiving files to analyzing them, generating documents, and providing them to the user, enabling flexible responses according to the user's emotional state.

[0174] A specific embodiment for implementing the system will be described below.

[0175] Initial file upload and analysis

[0176] A user selects a system product file from their device and uploads it to the server through a dedicated website or application. For example, a user selects a file called "Software A.exe" and sends it to the server. In this step, it is important that the file is sent correctly to the server.

[0177] The server stores the file received from the user in temporary storage and performs an initial analysis to determine the file type and structure. For example, it identifies that the received file "Software A.exe" is an executable file and its physical structural characteristics. At this stage, the file's metadata and header information are analyzed.

[0178] Decompilation and Static Analysis

[0179] The server then selects an appropriate decompiler to decompile the received file. The decompilation process converts binary code or intermediate code into high-level source code. For example, the server converts the binary code extracted from "Software A.exe" into C++ source code, revealing the code's logic and internal structure.

[0180] The server then uses static analysis tools to analyze the decompiled source code. This analysis clarifies the function call relationships and inter-module dependencies in the source code. If necessary, dynamic analysis is also performed to observe runtime behavior, thereby obtaining operational characteristics that cannot be determined by static analysis alone.

[0181] The role of the emotional engine

[0182] The emotion engine recognizes the user's emotional state and adjusts the system's behavior and user interface based on the results. For example, if a user is feeling irritated or dissatisfied while using the system, the emotion engine will detect this and improve the user experience by increasing the system's response speed and simplifying operation procedures.

[0183] The emotion engine analyzes the user's facial expressions and tone of voice through sensors such as cameras and microphones to evaluate their emotional state in real time, allowing the system to reflect the user's current emotional state.

[0184] Generate and provide specification documents

[0185] Based on the analysis results, the server automatically generates a specification document, which contains detailed information such as the system overview, module configuration, function roles, and library dependencies. For example, the generated document might explain what libraries "Software A" uses and how each module works together.

[0186] Finally, the server provides the generated specification document to the user. Specifically, it provides the user with a download link that the user can click to download the document. This download link is designed to be provided to the user safely and easily.

[0187] By going through the above process, users can obtain detailed specification documents of the original system product, which can be used for its operation and maintenance.Furthermore, the introduction of an emotion engine enables flexible responses according to the user's emotional state, improving the overall user experience.

[0188] The processing flow will be explained below.

[0189] Step 1: Select the file

[0190] The user selects the file of the system product to be reverse engineered from his / her own terminal. For example, the user selects "Software A.exe".

[0191] Step 2: Uploading files

[0192] The user clicks the "Upload" button on a dedicated website or application to upload the selected file to the server, and the device sends the selected file to the server.

[0193] Step 3: Receive the file

[0194] The server receives the file sent from the device and stores it in temporary storage. The server then verifies that the file was received correctly.

[0195] Step 4: Initial analysis

[0196] The server performs an initial analysis of the received file to identify its type and structure. It checks the metadata and header information to determine whether the file is executable or library format. For example, it determines that "Software A.exe" is an executable file.

[0197] Step 5: Decompile

[0198] The server selects the appropriate decompiler based on the file format. The decompiler is used to convert the binary code into high-level source code. For example, from "Software A.exe", it generates C++ source code.

[0199] Step 6: Static Analysis

[0200] The server analyzes the decompiled source code using static analysis tools to identify the code structure, function call relationships, and module dependencies, thereby revealing the internal structure and interrelationships of the source code.

[0201] Step 7: Dynamic analysis (if necessary)

[0202] The server emulates the execution environment of the software based on a specific scenario or use case, and uses debugging and monitoring tools to observe its behavior during runtime, thereby obtaining runtime characteristics that cannot be obtained through static analysis.

[0203] Step 8: Emotion Recognition with the Emotion Engine

[0204] The server uses an emotion engine to analyze the user's facial expressions and voice from sensors such as cameras and microphones installed on the user's device, and recognizes the user's emotional state in real time, for example, identifying whether the user is feeling anxious or irritated.

[0205] Step 9: Adjust your system to your emotions

[0206] The server dynamically adjusts the system's behavior and user interface based on the analysis results of the emotion engine. For example, if the user is frustrated, the server can speed up the system's response or simplify the operation procedure, thus improving the user experience.

[0207] Step 10: Generate the specification document

[0208] The server automatically generates a system specification document based on the results of static and dynamic analysis. The document contains details such as an overview of the system, module configuration, function roles, and library dependencies. For example, the generated document might explain which libraries "Software A" uses and how each module works together.

[0209] Step 11: Saving the Document

[0210] The server stores the generated specification document in a storage and makes it accessible to users.

[0211] Step 12: Generate a download link

[0212] The server generates a download link to the saved specification document and provides it to the user, who can then download the document via this link.

[0213] Step 13: Retrieving Documents

[0214] The user clicks the download link provided by the server to download the generated specification document to their device, allowing them to use detailed system information obtained as a result of the analysis.

[0215] Example 2

[0216] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0217] Conventional system analysis methods require a great deal of time and effort to understand the detailed specifications of a system product, and analyzing the product is particularly difficult when specifications are not available. Furthermore, there is no mechanism to reduce the emotional stress that accompanies user operations, which can lead to a poor user experience.

[0218] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0219] In this invention, the server includes means for receiving a system product file, means for temporarily storing the received file and initially analyzing its type and structure, means for decompiling the initially analyzed file, means for statically and dynamically analyzing the decompiled source code, means for detecting the user's emotional state, means for generating a specification document based on the analysis results and the user's emotional state, and means for providing the generated specification document to the user. This makes it possible to automatically obtain detailed specifications of the system product and flexibly respond to user emotions.

[0220] "System product" refers to a comprehensive product that is composed of various software and hardware and provides functions for a specific purpose.

[0221] "File" refers to a collection of digital data that records components of a system product.

[0222] "Temporary storage" refers to the practice of temporarily storing data for access or processing.

[0223] "Initial Analysis" refers to the process of initial data analysis to determine file type and structure.

[0224] "Decompilation" refers to the process of converting binary code or intermediate form code into high-level source code.

[0225] "Static analysis" refers to a technique for evaluating program behavior by analyzing the syntax and structure of the source code without executing it.

[0226] "Dynamic analysis" refers to a method of observing and analyzing the operating characteristics of software while it is running.

[0227] "Emotional state" refers to an emotional response that reflects a user's current state of mind or psychology.

[0228] A "specification document" refers to a document that describes the detailed specifications, structure, and operating characteristics of a system product.

[0229] "Providing" refers to the act of providing generated information or services to users in an accessible form.

[0230] This invention relates to a system that automatically analyzes a system product and generates specification documents when the specifications are unknown. Furthermore, by combining it with an emotion engine that recognizes the user's emotions, it aims to improve the user experience. This system automates the entire process from receiving files to analyzing them, generating documents, and providing them to the user, enabling flexible responses according to the user's emotional state.

[0231] Hardware and Software Use

[0232] To implement the system, the following hardware and software must be used:

[0233] Server: A server equipped with a high-performance processor and a large amount of memory is used. The server stores files, performs analysis, generates documents, and processes the emotion engine.

[0234] Terminal: A computer or mobile device used by a user to upload files or download generated documents.

[0235] Website or application: Used as an interface for users to upload files.

[0236] Decompiler: For example, using IDA Pro or Decompiler, converting binary code into high-level source code.

[0237] Static analysis tools: For example, SonarQube or CppDepend are used to analyze the source code.

[0238] Emotion engine: Software that uses a camera and microphone to analyze a user's facial expressions and tone of voice to assess their emotional state.

[0239] Process example

[0240] 1. File Upload

[0241] The user selects the system product file they want to analyze from their device and uploads it to the server via a dedicated website or application. For example, the user selects the file "Software A.exe" and clicks the upload button. At this time, the device sends the file to the server.

[0242] 2. Initial analysis

[0243] The server stores the uploaded file in temporary storage and performs an initial analysis to determine its type and structure. Specifically, the server analyzes the metadata and header information of the received "Software A.exe" file to confirm that it is an executable file. At this stage, the server also obtains the file's size, creation date and time, hash value, etc.

[0244] 3. Decompilation

[0245] The server selects an appropriate decompiler and decompiles the received file. Specifically, it converts the binary code of "Software A.exe" into high-level source code (e.g., C++) using a decompilation tool (e.g., IDA Pro or Decompiler). The server performs this process asynchronously and stores the results in temporary storage.

[0246] 4. Static and Dynamic Analysis

[0247] The server analyzes the decompiled source code using a static analysis tool (such as SonarQube or CppDepend). Specifically, it identifies function call relationships and inter-module dependencies. It also performs dynamic analysis as needed, running the program in a simulator or sandbox environment to closely observe its operating characteristics. This allows it to understand things like memory usage, CPU load, and network communication patterns during runtime.

[0248] 5. Operation of the Emotion Engine

[0249] The server runs an emotion engine to detect user emotions in real time. When a user operates the system, facial expressions and voice are captured through the device's camera and microphone. Specifically, the server analyzes the camera images and identifies the user's emotional state using a facial expression recognition algorithm (e.g., OpenFace or Microsoft® Face API). Voice data is also analyzed to evaluate emotions based on the tone and content of the voice.

[0250] 6. Generating and Providing Specification Documents

[0251] The server automatically generates a specification document based on the analysis results. Specifically, it integrates the results of the analysis tools and creates a document that includes a system overview, module configuration, function roles, library dependencies, etc. This document is generated in formats such as Markdown, PDF, and HTML, making it easy for users to access.

[0252] Finally, the server provides the generated specification document to the user. Specifically, it generates a download link for the document and notifies the user. The user can click this link to download the document to their device. The download link is provided via a secure protocol (e.g., HTTPS) to ensure safe and fast access.

[0253] Prompt Sentence Examples

[0254] How can the system automatically analyze unknown product files and generate detailed specification documents? Please also provide details on the specific steps from file upload to document submission, the tools used, and the analysis process.

[0255]

[0256] How can an emotion engine be used to improve the user experience? Give an example of how you can detect and respond to frustrations that users may experience while interacting with a system.

[0257] Through the above process, users can easily obtain detailed specification documents, and the emotion engine can improve the user experience.

[0258] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0259] Step 1: File Upload

[0260] The user selects the system product file to be analyzed from their own device and uploads it to the server via a dedicated website or application.

[0261] Input: System product file (e.g. Software A.exe)

[0262] Specific operation: The user clicks the upload button and the device sends the file to the server.

[0263] Output: The file uploaded to the server.

[0264] Step 2: Initial analysis of the file

[0265] The server temporarily stores the received files and performs an initial analysis to determine their type and structure.

[0266] Input: A file uploaded to the server

[0267] What happens: The server parses the metadata and header information to determine the file type (e.g., executable).

[0268] Output: File type, metadata (e.g. size, creation date, hash value)

[0269] Step 3: Decompile

[0270] The server selects the appropriate decompiler and performs the decompilation of the file.

[0271] Input: The initial parsed file and its metadata

[0272] Specific operation: The server uses a decompilation tool (e.g., IDA Pro, Decompiler) to convert the binary code into high-level source code (e.g., C++).

[0273] Output: Decompiled source code

[0274] Step 4: Static and Dynamic Analysis

[0275] The server analyzes the decompiled source code using static and dynamic analysis tools.

[0276] Input: Decompiled source code

[0277] Specific operation: The server identifies function call relationships and module dependencies using static analysis tools (e.g., SonarQube, CppDepend), and if necessary, uses dynamic analysis tools to examine runtime behavior.

[0278] Output: Analysis results (e.g., function call graph, module dependencies, behavioral characteristics)

[0279] Step 5: Detecting user emotions with the emotion engine

[0280] The server detects user emotions in real time.

[0281] Input: Camera image and audio data from the user device

[0282] How it works: The server analyzes camera images and uses facial expression recognition algorithms (e.g., OpenFace, Microsoft Face API) to identify emotional states. It also analyzes audio data and assesses emotions based on tone and content.

[0283] Output: User's emotional state (e.g., annoyed, frustrated, satisfied)

[0284] Step 6: Generate the specification document

[0285] The server generates a specification document based on the analysis results and the user's emotional state.

[0286] Input: Analysis results and user's emotional state

[0287] What it does: The server integrates the results of the analysis tools and creates a document that includes an overview of the system, module structure, function roles, library dependencies, etc.

[0288] Output: Generated specification document (e.g. Markdown, PDF, HTML)

[0289] Step 7: Provide documentation

[0290] The server provides the generated specification document to the user.

[0291] Input: Generated specification document

[0292] Specific operation: The server generates a download link for the document and notifies the user. The user clicks on this link to download the document to their device.

[0293] Output: User downloaded specification document

[0294] (Application example 2)

[0295] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0296] Currently, when the specifications of a system product are unknown, analyzing them and generating specification documents is extremely time-consuming, and the process can be frustrating for users. Furthermore, there is a lack of a way to detect in real time the stress or frustration felt by on-site workers regarding system operation or interfaces, and provide optimal feedback accordingly. This leads to issues such as reduced work efficiency and a worsening user experience.

[0297] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0298] In this invention, the server includes means for receiving a system product file, means for analyzing the received file, means for generating a specification document based on the analysis results, and means for recognizing the user's emotional state and adjusting the system operation and user interface. This not only automates the generation of the specification document, but also makes it possible to provide real-time feedback according to the user's emotions.

[0299] "System product files" are executable files and configuration files necessary for the operation of a particular system, such as software or control programs.

[0300] "Analysis" is the process of interpreting the contents of a file or program to understand its structure and behavior.

[0301] A "specification document" is a document that describes in detail the behavior, functions, design, dependencies, etc. of a system or software.

[0302] "User" means the ultimate user who operates or utilizes the system.

[0303] "Means for receiving" refers to the function or method for receiving system product files from users.

[0304] "Means of analysis" refers to a method for interpreting the received file and clarifying its internal structure and operation.

[0305] "Means for generating" refers to a method for automatically creating a specification document based on the analysis results.

[0306] The "means for providing" is a method or function for presenting the generated specification document to the user.

[0307] An "emotional state" is a psychological state that indicates a user's current mood or feelings.

[0308] "Means for recognizing and adjusting emotional states" refers to a method or function that uses sensors such as cameras and microphones to detect a user's emotions in real time and changes the system's behavior or interface based on the results.

[0309] "Decompilation" is the process of converting binary or intermediate form code into high-level source code.

[0310] "Static analysis" is the process of analyzing a program's source code and structure without executing it.

[0311] The present invention is a system that automatically analyzes files of a system product, generates specification documents, and further includes a function for recognizing user emotions and adjusting the operation of the system. Specific embodiments of the present invention will be described below.

[0312] File upload and initial analysis

[0313] Users upload system product files to the server using a dedicated website or application. The uploaded file is stored in temporary storage, where its metadata and structure are initially analyzed. For example, if a file such as "control program.exe" is uploaded, it is identified as an executable file and its physical characteristics are identified.

[0314] Decompilation and Static Analysis

[0315] The server uses a decompiler to decompile the received file. The decompiled code is converted into a high-level language and then analyzed using a static analysis tool. Static analysis reveals the function call relationships and inter-module dependencies. For example, "control program.exe" is converted into C++ source code, and the function connections are analyzed from that code.

[0316] Generate specification documents

[0317] Based on the results of decompilation and static analysis, the server automatically generates a specification document that details the system overview, module structure, function roles, library dependencies, etc. The generated specification document is provided to the user via a download link.

[0318] Emotion recognition and system behavior adjustment

[0319] The emotion engine uses sensors such as cameras and microphones to recognize the user's emotional state in real time. For example, it can analyze a worker's facial expressions and tone of voice to detect irritation or fatigue. Based on the detected emotional state, the server adjusts the system's behavior and interface. If the worker is irritated, the robot's movement speed can be slowed down, improving safety and work efficiency.

[0320] Hardware and software used

[0321] 1. Hardware

[0322] Camera (e.g. Logitech C920): Used to capture the facial expressions of the workers.

[0323] Microphone (e.g. Blue Yeti): Used to capture the worker's tone of voice.

[0324] 2. Software

[0325] dlib library: Used for face detection and landmark extraction.

[0326] EmotionRecognition library: Used to analyze and determine emotions from facial expressions.

[0327] Decompiler library: Decompiles robot control systems and programs.

[0328] Specific examples

[0329] In factories, when workers interact with robotic control systems, the system analyzes their emotions in real time, for example, if it detects that a worker is feeling frustrated, it can adjust the robot's movement speed to improve work safety and the experience.

[0330] Prompt Sentence Examples

[0331] "Write a program to run an application that analyzes the robot control system in a factory and generates specification documents. We will also use a camera and microphone to capture the emotions of workers. Write a program to adjust the robot's behavior according to the worker's emotional state."

[0332] In this way, a system can be constructed that simultaneously generates specification documents and optimizes the user experience.

[0333] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0334] Step 1:

[0335] A user uploads a system product file to the server using a dedicated website or application. The input is the system product file, and the output is that the file is transferred to the server and stored in temporary storage. The server then confirms that the file has been sent.

[0336] Step 2:

[0337] The server performs pre-processing to analyze the uploaded file. Here, it obtains the file's metadata and header information and identifies the file type and structure. The input is the uploaded file, and the output is information about the file type and structure. The server uses this information to prepare for the next decompilation process.

[0338] Step 3:

[0339] The server selects an appropriate decompiler and decompiles the file. The input for decompilation is the file type and structure information obtained in the previous step, along with the actual file itself. The output is high-level source code. For example, binary code is converted into C++ source code. The server saves the converted source code and prepares it for static analysis.

[0340] Step 4:

[0341] The server analyzes the decompiled source code using a static analysis tool. The input is the decompiled source code, and the output is the analysis results, such as function call relationships and inter-module dependencies. The server obtains these analysis results and uses them to generate a specification document.

[0342] Step 5:

[0343] The server automatically generates a specification document based on the analysis results. The input is the static analysis results, and the output is a specification document that describes the system overview, module configuration, function roles, library dependencies, etc. The server generates a link so that the user can download this specification document.

[0344] Step 6:

[0345] The user clicks on the provided link to download the generated specification document. The input is the download link for the specification document, and the output is the specification document downloaded to the local machine. The server verifies that the document was downloaded correctly.

[0346] Step 7:

[0347] The server activates an emotion engine and recognizes the user's emotional state in real time. The input is the user's facial expression and tone of voice captured by a camera or microphone, and the output is the user's emotional state. The server analyzes this data and determines the user's emotional state.

[0348] Step 8:

[0349] The server adjusts the system's behavior and interface based on the user's emotional state. The input is the user's emotional state output from the emotion engine, and the output is the adjusted system behavior and interface. For example, if the user is irritated, the server will adjust the robot's movement speed to slow down. The entire system is adjusted to perform optimally according to the user's emotional state.

[0350] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0351] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0352] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0353] [Second embodiment]

[0354] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0355] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0356] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0357] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0358] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0359] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0360] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0361] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0362] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0363] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0364] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0365] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0366] The present invention relates to a system that automatically analyzes a system product and generates a specification document when the specifications of the system product are unknown. This system is designed so that a user can upload the system product and ultimately obtain the automatically generated specification document.

[0367] A specific embodiment for implementing the system will be described below.

[0368] File upload procedure

[0369] A user selects a system product file from their device and uploads it to the server through a dedicated website or application. For example, a user selects a file called "Software A.exe" and sends it to the server. In this step, it is important that the file is sent correctly to the server.

[0370] Initial analysis of the file

[0371] The server stores the system product file received from the user in temporary storage and performs an initial analysis to determine the file type and structure. For example, it identifies that the received "Software A.exe" is an executable file and its structural physical characteristics. At this stage, the file's metadata and header information are analyzed.

[0372] Decompiling and Parsing

[0373] The server then selects an appropriate decompiler to decompile the received file. The decompilation process converts binary code or intermediate code into high-level source code. For example, the server converts the binary code extracted from "Software A.exe" into C++ source code, revealing the code's logic and internal structure.

[0374] The server then uses static analysis tools to analyze the decompiled source code. This analysis clarifies the function call relationships and inter-module dependencies in the source code. If necessary, dynamic analysis is also performed to observe runtime behavior, thereby obtaining operational characteristics that cannot be determined by static analysis alone.

[0375] Generate specification documents

[0376] Based on the analysis results, the server automatically generates a specification document, which contains detailed information such as the system overview, module configuration, function roles, and library dependencies. For example, the generated document might explain what libraries "Software A" uses and how each module works together.

[0377] Providing results

[0378] Finally, the server provides the generated specification document to the user. Specifically, it provides the user with a download link that the user can click to download the document. This download link is designed to be provided to the user safely and easily.

[0379] By going through the above process, users can obtain detailed specification documents of the original system product and use them for its operation and maintenance. This invention enables efficient system analysis and document generation, achieving a significant reduction in time and effort compared to conventional manual analysis work.

[0380] The processing flow will be explained below.

[0381] Step 1: Select the file

[0382] The user selects the file of the system product that he / she wants to reverse engineer on the terminal. For example, the user selects "Software A.exe".

[0383] Step 2: Uploading files

[0384] The user uploads the selected file to the server by clicking the "Upload" button on a dedicated website or application, and the device sends the file to the server.

[0385] Step 3: Receive the file

[0386] The server receives the file sent from the device and stores it in temporary storage. The server then verifies that the file was received correctly.

[0387] Step 4: Initial analysis

[0388] The server performs an initial analysis of the received file to determine its type and structure, checking metadata and header information to determine whether the file is an executable or library.

[0389] Step 5: Decompile

[0390] The server selects the appropriate decompiler based on the format of the file. The decompiler is used to convert the binary code into high-level source code, for example, converting "Software A.exe" into C++ source code.

[0391] Step 6: Static Analysis

[0392] The server analyzes the decompiled source code using static analysis tools to identify the code structure, function call relationships, and module dependencies.

[0393] Step 7: Dynamic analysis (if necessary)

[0394] The server emulates the execution environment of the software based on a specific scenario or use case, and uses debugging and monitoring tools to observe its behavior at runtime.

[0395] Step 8: Generate the specification document

[0396] The server automatically generates a system specification document based on the results of static and dynamic analysis, which contains detailed information such as module configuration, function roles, and library dependencies.

[0397] Step 9: Saving the Document

[0398] The server stores the generated specification document in a storage and makes it accessible to users.

[0399] Step 10: Generate a download link

[0400] The server generates a download link to the saved specification document and provides it to the user, who then downloads the document via this link.

[0401] Step 11: Retrieving Documents

[0402] The user clicks on the download link provided by the server to download the generated specification document to the terminal.

[0403] Example 1

[0404] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0405] In conventional systems, when the specifications of a system product are unknown, analyzing it and generating specification documents requires a significant amount of time and effort. Furthermore, because the analysis work is performed manually, the analysis results often lack accuracy and consistency. Therefore, there is a demand for an automated analysis system that can quickly and accurately obtain detailed system product specifications and use them for operation and maintenance.

[0406] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0407] In this invention, the server includes means for receiving an uploaded system product file, means for initially analyzing metadata and header information of the received file, means for decompiling the file based on the analysis results, means for statically analyzing the decompiled code, means for performing dynamic analysis based on the static analysis results, means for integrating the dynamic analysis results to generate a specification document, and means for providing the generated specification document to a user, thereby enabling detailed specifications of the system product to be obtained quickly and accurately.

[0408] "Uploading" is the act of a user sending a data file from their computer or device to a remote system such as a server or cloud service.

[0409] A "system product" is a software or hardware product that is designed to have specific functions and capabilities and is provided for use by users.

[0410] "File metadata" is information that is not contained in the file itself but that describes its contents and characteristics, such as the file's creation date and time, size, and author information.

[0411] "Header information" is data at the beginning of a file that defines the file's type, structure, and other important attributes.

[0412] "Initial analysis" is the initial analysis process for understanding the basic attributes and structure of received data or files.

[0413] "Decompilation" is the process of converting program code written in machine language or intermediate language into source code in a high-level language.

[0414] "Static analysis" is a technique for analyzing a program's code to find errors, potential bugs, and security vulnerabilities without running the program.

[0415] "Dynamic analysis" is a technique for analyzing problems and operating characteristics by observing the behavior and performance of a program while it is being executed.

[0416] A "specification document" is a technical document that describes in detail the structure, functions, operating conditions, dependencies, etc. of a system or software product.

[0417] "Providing" means preparing and making available a particular service or product so that it can be easily accessed by users.

[0418] This invention relates to a system that automatically analyzes a system product and generates a specification document when the specifications of the system product are unknown. This system is designed so that a user can upload the system product and ultimately obtain the automatically generated specification document.

[0419] A specific embodiment for implementing the system will be described below.

[0420] File upload procedure

[0421] The user selects the system product file from their device and uploads it to the server via a dedicated website or application. Specifically, the user opens a browser, accesses the target site, clicks the "Upload" button to display a file selection dialog, selects the file to be analyzed (e.g., "Software A.exe"), and clicks the "Submit" button again to begin uploading.

[0422] Initial analysis of the file

[0423] The server stores the file uploaded by the user in temporary storage and performs an initial analysis to determine the file's type and structure. During this stage, the server analyzes the file's metadata (e.g., creation date and file size) and header information (e.g., file format and entry point). Based on this, the server can determine that the file is an executable file and the platform it is intended for.

[0424] Decompilation and Static Analysis

[0425] The server uses a decompiler such as Ghidra or IDA Pro to decompile the file, converting the binary code into high-level source code that can be understood by humans. For example, the binary code for "Software A.exe" is converted into C++ source code. The server then performs static analysis using SonarQube or Cppcheck. Specifically, the server analyzes the code's function call relationships, inter-module dependencies, variable usage, and other aspects to identify code quality and security issues.

[0426] Dynamic Analysis

[0427] If necessary, the server performs dynamic analysis. Using tools such as Valgrind or QEMU, the server runs the program to be analyzed and observes its operating characteristics. Specifically, the server monitors the program's memory usage, CPU usage, and frequency of I / O operations to detect bugs or abnormal behavior that occur during execution. This allows the server to understand operating characteristics that cannot be determined by static analysis alone.

[0428] Generate specification documents

[0429] Based on the analysis results, the server automatically generates a specification document. This document contains detailed information such as an overview of the system, module configuration, function roles, and library dependencies. The server uses a text generation engine to generate a document describing the analysis results in natural language. Diagrams and tables are also added to this document to make the content easier to understand visually.

[0430] Providing results

[0431] Finally, the server provides the generated specification document to the user. Specifically, the server generates a download link for the user and sends a notification email containing the link. The user can easily download the document by clicking the link. This download link is secure and designed to be user-friendly.

[0432] As a concrete example, the following scenario can be considered.

[0433] If a user has a file called "SoftwareB.exe" that they want to analyze, they can use a prompt statement like this:

[0434] "Please upload the following file and automatically generate its specification document: Software B.exe"

[0435] Through these efforts, users can quickly and accurately obtain detailed specification documents and use them for operation and maintenance. This system significantly reduces the time and effort required compared to conventional manual analysis work.

[0436] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0437] Step 1: Upload a file

[0438] The user selects a system product file from their device and uploads it to the server via a dedicated website or application. Specifically, the user opens a browser, accesses the target site, and clicks the "Upload" button to display a file selection dialog. Next, the user selects the file to be analyzed, such as "Software A.exe," and clicks the "Submit" button again to begin uploading. The input is the target file on the user's device, and the output is the uploaded file saved on the server.

[0439] Step 2: Initial analysis of the file

[0440] The server stores the file uploaded by the user in temporary storage and performs an initial analysis to determine the file's type and structure. Specifically, the server analyzes the file's metadata (e.g., creation date and time, file size) and header information (e.g., file format, entry point). The input is the uploaded file, and the output is the analysis results, including the file's metadata and header information.

[0441] Step 3: Decompile

[0442] The server decompiles the file using an appropriate decompiler (e.g., Ghidra, IDA Pro) and converts the binary code into high-level source code that can be understood by humans. Specifically, the server converts the binary code of "Software A.exe" into C++ source code. The input is a file containing the initial analysis results, and the output is the decompiled source code.

[0443] Step 4: Static Analysis

[0444] The server uses a static analysis tool (e.g., SonarQube, Cppcheck) to analyze the decompiled source code. Specifically, the server analyzes the code's function call relationships, inter-module dependencies, variable usage, etc. to identify code quality and security issues. The input is the decompiled source code, and the output is the static analysis results.

[0445] Step 5: Dynamic Analysis

[0446] If necessary, the server performs dynamic analysis. Using a dynamic analysis tool (e.g., Valgrind or QEMU), the server executes the program to be analyzed and observes its operating characteristics. Specifically, the server monitors the program's memory usage, CPU usage, and frequency of I / O operations to detect bugs or abnormal behavior that occur during execution. The input is the static analysis results and decompiled source code, and the output is the dynamic analysis results.

[0447] Step 6: Generate the specification document

[0448] The server automatically generates a specification document based on the analysis results. Specifically, the server uses a text generation engine to generate a document that details the system overview, module configuration, function roles, library dependencies, etc. This document also includes diagrams and tables. The input is the static and dynamic analysis results, and the output is a specification document.

[0449] Step 7: Delivering the results

[0450] The server provides the generated specification document to the user. Specifically, the server generates a download link for the user and sends a notification email containing this link. The user can easily download the document by clicking the link. The input is the specification document, and the output is providing the download link to the user.

[0451] This system allows users to quickly and accurately obtain detailed specification documents and use them for operation and maintenance.

[0452] (Application example 1)

[0453] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0454] Factory robots have complex software systems, and analyzing them and creating specification documents requires a great deal of effort and time. Furthermore, when detailed analysis of unknown system products is required, conventional methods are inefficient and may hinder production efficiency. Furthermore, accurately understanding software functions and dependencies requires advanced expertise. To solve these problems, a system is needed that can easily and quickly analyze software and automatically generate specification documents.

[0455] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0456] In this invention, the server includes means for receiving a system product file, means for analyzing the received file, means for generating a specification document based on the analysis results, means for providing the generated specification document to a user, means for analyzing the factory robot software, means for static analysis for extracting software functions and dependencies, and means for providing the generated specification document in PDF format, thereby enabling a user to easily and quickly analyze the factory robot software and obtain the results as a detailed specification document.

[0457] "System product file" means an electronic file containing software or program code for a factory robot.

[0458] "Analyzing" refers to the process of analyzing the contents and structure of a file in detail using analytical tools.

[0459] A "specification document" is a document created based on the analysis results that describes the functions and dependencies of the factory robot software.

[0460] "Providing to users" refers to the process of providing the generated specification document to users in a form that is easily accessible to them.

[0461] "Factory robot" is a general term for robots used in automated factories.

[0462] A "software function" is a set of operations or calculations performed by a factory robot's software.

[0463] "Dependencies" refer to the relationships between libraries and modules that are required for software to function.

[0464] "Static analysis" is a technique for analyzing software structure, code functions, dependencies, etc. without running the software.

[0465] "PDF format" is an abbreviation for Portable Document Format, and is a file format for saving and displaying specification documents in a visually easy-to-read format.

[0466] The present invention provides a system that allows a user to upload a software file for a factory robot, analyzes the file on a server, and automatically generates a detailed specification document. Specific embodiments are described below.

[0467] System Program

[0468] The program of this system consists of the following major components:

[0469] 1. File upload interface

[0470] An interface for users to upload factory robot software files, which can be provided as a smartphone application or web application.

[0471] 2. Initial Analysis Module

[0472] The server receives the uploaded file and analyzes the file type and structure.

[0473] 3. Decompilation Module

[0474] It decompiles the received files, converting the binary code into high-level source code.

[0475] 4. Static Analysis Module

[0476] It analyzes decompiled source code and extracts software functions and dependencies.

[0477] 5. Document Generation Module

[0478] Based on the analysis results, a detailed specification document is automatically generated in PDF format.

[0479] 6. Result Delivery Module

[0480] Provide the generated specification document to the user and send a download link.

[0481] Natural language explanations

[0482] First, a user uses a smartphone or computer to upload the factory robot's software file to the server via a dedicated interface. The server first stores the received file in temporary storage. Next, the initial analysis module analyzes the file type and structure. For example, if a file named "RobotControlV2.0.exe" is received, it will identify it as an executable file. This analysis uses metadata and file header information.

[0483] Next, the decompilation module uses a decompiler tool to convert the file into high-level source code, for example, C++ source code, and the static analysis module analyzes the source code for functions and dependencies, extracting functions and libraries such as "function1" and "lib1."

[0484] Based on these analysis results, the document generation module automatically generates a specification document in PDF format. Finally, the generated specification document is provided to the user as a download link via the result provision module.

[0485] Specific examples

[0486] For example, if a factory production manager needs to analyze the software for a factory robot called "RobotControlV2.0.exe" and find out the detailed specifications of the libraries and internal modules it uses, he or she might enter the following prompt into the system:

[0487] Analyze the factory robot software "RobotControlV2.0.exe" and generate a detailed specification document of the libraries and internal modules it uses. The following file was uploaded from a smartphone.

[0488] This invention enables users to efficiently and accurately analyze factory robot software and obtain detailed specification documents without requiring specialized knowledge, significantly improving factory production and maintenance efficiency.

[0489] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0490] Step 1:

[0491] The user uploads the factory robot's software file to the server through a dedicated interface. As input, the user selects the executable file "RobotControlV2.0.exe" on their smartphone or computer and presses the upload button. This action sends the file to the server. As output, the file is accurately saved in temporary storage on the server side.

[0492] Step 2:

[0493] The server passes the received file to the initial analysis module, which analyzes the file type and structure. As input, the uploaded "RobotControlV2.0.exe" file is provided. The server reads the file header and metadata and identifies it as an executable file. As output, the file type and basic structure information are obtained.

[0494] Step 3:

[0495] The server uses a decompilation module to convert the parsed files into high-level source code. As input, it is provided with the binary code of the executable file "RobotControlV2.0.exe". The server runs the decompiler tool and converts the binary code into "C++" source code. As output, it gets the decompiled high-level source code.

[0496] Step 4:

[0497] The server uses a static analysis module to analyze the decompiled source code and extract software functions and dependencies. As input, the decompiled source code is provided. The server runs a static code analysis tool to extract function definitions (e.g., "function1", "function2") and dependent libraries (e.g., "lib1", "lib2"). As output, the functionality and dependency information of the source code is obtained.

[0498] Step 5:

[0499] The server uses a document generation module to automatically generate a specification document in PDF format based on the analysis results. The analysis results of the software's functions and dependencies are provided as input. The server uses a PDF generation library (e.g., ReportLab) to generate a PDF document containing the software's detailed specifications. The output is a specification document in PDF format.

[0500] Step 6:

[0501] The server provides the generated specification document to the user through the result delivery module and sends a download link. The generated PDF document is provided as input. The server generates a secure download link and displays it on the user's interface or sends it by email. The user can then download the specification document by clicking the provided download link. As output, the user gets a specification document that details the analysis results.

[0502] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0503] This invention relates to a system that automatically analyzes a system product and generates specification documents when the specifications are unknown. Furthermore, by combining it with an emotion engine that recognizes the user's emotions, it aims to improve the user experience. This system automates the entire process from receiving files to analyzing them, generating documents, and providing them to the user, enabling flexible responses according to the user's emotional state.

[0504] A specific embodiment for implementing the system will be described below.

[0505] Initial file upload and analysis

[0506] A user selects a system product file from their device and uploads it to the server through a dedicated website or application. For example, a user selects a file called "Software A.exe" and sends it to the server. In this step, it is important that the file is sent correctly to the server.

[0507] The server stores the file received from the user in temporary storage and performs an initial analysis to determine the file type and structure. For example, it identifies that the received file "Software A.exe" is an executable file and its physical structural characteristics. At this stage, the file's metadata and header information are analyzed.

[0508] Decompilation and Static Analysis

[0509] The server then selects an appropriate decompiler to decompile the received file. The decompilation process converts binary code or intermediate code into high-level source code. For example, the server converts the binary code extracted from "Software A.exe" into C++ source code, revealing the code's logic and internal structure.

[0510] The server then uses static analysis tools to analyze the decompiled source code. This analysis clarifies the function call relationships and inter-module dependencies in the source code. If necessary, dynamic analysis is also performed to observe runtime behavior, thereby obtaining operational characteristics that cannot be determined by static analysis alone.

[0511] The role of the emotional engine

[0512] The emotion engine recognizes the user's emotional state and adjusts the system's behavior and user interface based on the results. For example, if a user is feeling irritated or dissatisfied while using the system, the emotion engine will detect this and improve the user experience by increasing the system's response speed and simplifying operation procedures.

[0513] The emotion engine analyzes the user's facial expressions and tone of voice through sensors such as cameras and microphones to evaluate their emotional state in real time, allowing the system to reflect the user's current emotional state.

[0514] Generate and provide specification documents

[0515] Based on the analysis results, the server automatically generates a specification document, which contains detailed information such as the system overview, module configuration, function roles, and library dependencies. For example, the generated document might explain what libraries "Software A" uses and how each module works together.

[0516] Finally, the server provides the generated specification document to the user. Specifically, it provides the user with a download link that the user can click to download the document. This download link is designed to be provided to the user safely and easily.

[0517] By going through the above process, users can obtain detailed specification documents of the original system product, which can be used for its operation and maintenance.Furthermore, the introduction of an emotion engine enables flexible responses according to the user's emotional state, improving the overall user experience.

[0518] The processing flow will be explained below.

[0519] Step 1: Select the file

[0520] The user selects the file of the system product to be reverse engineered from his / her own terminal. For example, the user selects "Software A.exe".

[0521] Step 2: Uploading files

[0522] The user clicks the "Upload" button on a dedicated website or application to upload the selected file to the server, and the device sends the selected file to the server.

[0523] Step 3: Receive the file

[0524] The server receives the file sent from the device and stores it in temporary storage. The server then verifies that the file was received correctly.

[0525] Step 4: Initial analysis

[0526] The server performs an initial analysis of the received file to identify its type and structure. It checks the metadata and header information to determine whether the file is executable or library format. For example, it determines that "Software A.exe" is an executable file.

[0527] Step 5: Decompile

[0528] The server selects the appropriate decompiler based on the file format. The decompiler is used to convert the binary code into high-level source code. For example, from "Software A.exe", it generates C++ source code.

[0529] Step 6: Static Analysis

[0530] The server analyzes the decompiled source code using static analysis tools to identify the code structure, function call relationships, and module dependencies, thereby revealing the internal structure and interrelationships of the source code.

[0531] Step 7: Dynamic analysis (if necessary)

[0532] The server emulates the execution environment of the software based on a specific scenario or use case, and uses debugging and monitoring tools to observe its behavior during runtime, thereby obtaining runtime characteristics that cannot be obtained through static analysis.

[0533] Step 8: Emotion Recognition with the Emotion Engine

[0534] The server uses an emotion engine to analyze the user's facial expressions and voice from sensors such as cameras and microphones installed on the user's device, and recognizes the user's emotional state in real time, for example, identifying whether the user is feeling anxious or irritated.

[0535] Step 9: Adjust your system to your emotions

[0536] The server dynamically adjusts the system's behavior and user interface based on the analysis results of the emotion engine. For example, if the user is frustrated, the server can speed up the system's response or simplify the operation procedure, thus improving the user experience.

[0537] Step 10: Generate the specification document

[0538] The server automatically generates a system specification document based on the results of static and dynamic analysis. The document contains details such as an overview of the system, module configuration, function roles, and library dependencies. For example, the generated document might explain which libraries "Software A" uses and how each module works together.

[0539] Step 11: Saving the Document

[0540] The server stores the generated specification document in a storage and makes it accessible to users.

[0541] Step 12: Generate a download link

[0542] The server generates a download link to the saved specification document and provides it to the user, who can then download the document via this link.

[0543] Step 13: Retrieving Documents

[0544] The user clicks the download link provided by the server to download the generated specification document to their device, allowing them to use detailed system information obtained as a result of the analysis.

[0545] Example 2

[0546] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0547] Conventional system analysis methods require a great deal of time and effort to understand the detailed specifications of a system product, and analyzing the product is particularly difficult when specifications are not available. Furthermore, there is no mechanism to reduce the emotional stress that accompanies user operations, which can lead to a poor user experience.

[0548] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0549] In this invention, the server includes means for receiving a system product file, means for temporarily storing the received file and initially analyzing its type and structure, means for decompiling the initially analyzed file, means for statically and dynamically analyzing the decompiled source code, means for detecting the user's emotional state, means for generating a specification document based on the analysis results and the user's emotional state, and means for providing the generated specification document to the user. This makes it possible to automatically obtain detailed specifications of the system product and flexibly respond to user emotions.

[0550] "System product" refers to a comprehensive product that is composed of various software and hardware and provides functions for a specific purpose.

[0551] "File" refers to a collection of digital data that records components of a system product.

[0552] "Temporary storage" refers to the practice of temporarily storing data for access or processing.

[0553] "Initial Analysis" refers to the process of initial data analysis to determine file type and structure.

[0554] "Decompilation" refers to the process of converting binary code or intermediate form code into high-level source code.

[0555] "Static analysis" refers to a technique for evaluating program behavior by analyzing the syntax and structure of the source code without executing it.

[0556] "Dynamic analysis" refers to a method of observing and analyzing the operating characteristics of software while it is running.

[0557] "Emotional state" refers to an emotional response that reflects a user's current state of mind or psychology.

[0558] A "specification document" refers to a document that describes the detailed specifications, structure, and operating characteristics of a system product.

[0559] "Providing" refers to the act of providing generated information or services to users in an accessible form.

[0560] This invention relates to a system that automatically analyzes a system product and generates specification documents when the specifications are unknown. Furthermore, by combining it with an emotion engine that recognizes the user's emotions, it aims to improve the user experience. This system automates the entire process from receiving files to analyzing them, generating documents, and providing them to the user, enabling flexible responses according to the user's emotional state.

[0561] Hardware and Software Use

[0562] To implement the system, the following hardware and software must be used:

[0563] Server: A server equipped with a high-performance processor and a large amount of memory is used. The server stores files, performs analysis, generates documents, and processes the emotion engine.

[0564] Terminal: A computer or mobile device used by a user to upload files or download generated documents.

[0565] Website or application: Used as an interface for users to upload files.

[0566] Decompiler: For example, using IDA Pro or Decompiler, converting binary code into high-level source code.

[0567] Static analysis tools: For example, SonarQube or CppDepend are used to analyze the source code.

[0568] Emotion engine: Software that uses a camera and microphone to analyze a user's facial expressions and tone of voice to assess their emotional state.

[0569] Process example

[0570] 1. File Upload

[0571] The user selects the system product file they want to analyze from their device and uploads it to the server via a dedicated website or application. For example, the user selects the file "Software A.exe" and clicks the upload button. At this time, the device sends the file to the server.

[0572] 2. Initial analysis

[0573] The server stores the uploaded file in temporary storage and performs an initial analysis to determine its type and structure. Specifically, the server analyzes the metadata and header information of the received "Software A.exe" file to confirm that it is an executable file. At this stage, the server also obtains the file's size, creation date and time, hash value, etc.

[0574] 3. Decompilation

[0575] The server selects an appropriate decompiler and decompiles the received file. Specifically, it converts the binary code of "Software A.exe" into high-level source code (e.g., C++) using a decompilation tool (e.g., IDA Pro or Decompiler). The server performs this process asynchronously and stores the results in temporary storage.

[0576] 4. Static and Dynamic Analysis

[0577] The server analyzes the decompiled source code using a static analysis tool (such as SonarQube or CppDepend). Specifically, it identifies function call relationships and inter-module dependencies. It also performs dynamic analysis as needed, running the program in a simulator or sandbox environment to closely observe its operating characteristics. This allows it to understand things like memory usage, CPU load, and network communication patterns during runtime.

[0578] 5. Operation of the Emotion Engine

[0579] The server runs an emotion engine to detect user emotions in real time. When a user operates the system, facial expressions and voice are captured through the device's camera and microphone. Specifically, the server analyzes the camera images and identifies the user's emotional state using a facial expression recognition algorithm (e.g., OpenFace or Microsoft Face API). Voice data is also analyzed to evaluate emotions based on the tone and content of the voice.

[0580] 6. Generating and Providing Specification Documents

[0581] The server automatically generates a specification document based on the analysis results. Specifically, it integrates the results of the analysis tools and creates a document that includes a system overview, module configuration, function roles, library dependencies, etc. This document is generated in formats such as Markdown, PDF, and HTML, making it easy for users to access.

[0582] Finally, the server provides the generated specification document to the user. Specifically, it generates a download link for the document and notifies the user. The user can click this link to download the document to their device. The download link is provided via a secure protocol (e.g., HTTPS) to ensure safe and fast access.

[0583] Prompt Sentence Examples

[0584] How can the system automatically analyze unknown product files and generate detailed specification documents? Please also provide details on the specific steps from file upload to document submission, the tools used, and the analysis process.

[0585]

[0586] How can an emotion engine be used to improve the user experience? Give an example of how you can detect and respond to frustrations that users may experience while interacting with a system.

[0587] Through the above process, users can easily obtain detailed specification documents, and the emotion engine can improve the user experience.

[0588] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0589] Step 1: File Upload

[0590] The user selects the system product file to be analyzed from their own device and uploads it to the server via a dedicated website or application.

[0591] Input: System product file (e.g. Software A.exe)

[0592] Specific operation: The user clicks the upload button and the device sends the file to the server.

[0593] Output: The file uploaded to the server.

[0594] Step 2: Initial analysis of the file

[0595] The server temporarily stores the received files and performs an initial analysis to determine their type and structure.

[0596] Input: A file uploaded to the server

[0597] What happens: The server parses the metadata and header information to determine the file type (e.g., executable).

[0598] Output: File type, metadata (e.g. size, creation date, hash value)

[0599] Step 3: Decompile

[0600] The server selects the appropriate decompiler and performs the decompilation of the file.

[0601] Input: The initial parsed file and its metadata

[0602] Specific operation: The server uses a decompilation tool (e.g., IDA Pro, Decompiler) to convert the binary code into high-level source code (e.g., C++).

[0603] Output: Decompiled source code

[0604] Step 4: Static and Dynamic Analysis

[0605] The server analyzes the decompiled source code using static and dynamic analysis tools.

[0606] Input: Decompiled source code

[0607] Specific operation: The server identifies function call relationships and module dependencies using static analysis tools (e.g., SonarQube, CppDepend), and if necessary, uses dynamic analysis tools to examine runtime behavior.

[0608] Output: Analysis results (e.g., function call graph, module dependencies, behavioral characteristics)

[0609] Step 5: Detecting user emotions with the emotion engine

[0610] The server detects user emotions in real time.

[0611] Input: Camera image and audio data from the user device

[0612] How it works: The server analyzes camera images and uses facial expression recognition algorithms (e.g., OpenFace, Microsoft Face API) to identify emotional states. It also analyzes audio data and assesses emotions based on tone and content.

[0613] Output: User's emotional state (e.g., annoyed, frustrated, satisfied)

[0614] Step 6: Generate the specification document

[0615] The server generates a specification document based on the analysis results and the user's emotional state.

[0616] Input: Analysis results and user's emotional state

[0617] What it does: The server integrates the results of the analysis tools and creates a document that includes an overview of the system, module structure, function roles, library dependencies, etc.

[0618] Output: Generated specification document (e.g. Markdown, PDF, HTML)

[0619] Step 7: Provide documentation

[0620] The server provides the generated specification document to the user.

[0621] Input: Generated specification document

[0622] Specific operation: The server generates a download link for the document and notifies the user. The user clicks on this link to download the document to their device.

[0623] Output: User downloaded specification document

[0624] (Application example 2)

[0625] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0626] Currently, when the specifications of a system product are unknown, analyzing them and generating specification documents is extremely time-consuming, and the process can be frustrating for users. Furthermore, there is a lack of a way to detect in real time the stress or frustration felt by on-site workers regarding system operation or interfaces, and provide optimal feedback accordingly. This leads to issues such as reduced work efficiency and a worsening user experience.

[0627] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0628] In this invention, the server includes means for receiving a system product file, means for analyzing the received file, means for generating a specification document based on the analysis results, and means for recognizing the user's emotional state and adjusting the system operation and user interface. This not only automates the generation of the specification document, but also makes it possible to provide real-time feedback according to the user's emotions.

[0629] "System product files" are executable files and configuration files necessary for the operation of a particular system, such as software or control programs.

[0630] "Analysis" is the process of interpreting the contents of a file or program to understand its structure and behavior.

[0631] A "specification document" is a document that describes in detail the behavior, functions, design, dependencies, etc. of a system or software.

[0632] "User" means the ultimate user who operates or utilizes the system.

[0633] "Means for receiving" refers to the function or method for receiving system product files from users.

[0634] "Means of analysis" refers to a method for interpreting the received file and clarifying its internal structure and operation.

[0635] "Means for generating" refers to a method for automatically creating a specification document based on the analysis results.

[0636] The "means for providing" is a method or function for presenting the generated specification document to the user.

[0637] An "emotional state" is a psychological state that indicates a user's current mood or feelings.

[0638] "Means for recognizing and adjusting emotional states" refers to a method or function that uses sensors such as cameras and microphones to detect a user's emotions in real time and changes the system's behavior or interface based on the results.

[0639] "Decompilation" is the process of converting binary or intermediate form code into high-level source code.

[0640] "Static analysis" is the process of analyzing a program's source code and structure without executing it.

[0641] The present invention is a system that automatically analyzes files of a system product, generates specification documents, and further includes a function for recognizing user emotions and adjusting the operation of the system. Specific embodiments of the present invention will be described below.

[0642] File upload and initial analysis

[0643] Users upload system product files to the server using a dedicated website or application. The uploaded file is stored in temporary storage, where its metadata and structure are initially analyzed. For example, if a file such as "control program.exe" is uploaded, it is identified as an executable file and its physical characteristics are identified.

[0644] Decompilation and Static Analysis

[0645] The server uses a decompiler to decompile the received file. The decompiled code is converted into a high-level language and then analyzed using a static analysis tool. Static analysis reveals the function call relationships and inter-module dependencies. For example, "control program.exe" is converted into C++ source code, and the function connections are analyzed from that code.

[0646] Generate specification documents

[0647] Based on the results of decompilation and static analysis, the server automatically generates a specification document that details the system overview, module structure, function roles, library dependencies, etc. The generated specification document is provided to the user via a download link.

[0648] Emotion recognition and system behavior adjustment

[0649] The emotion engine uses sensors such as cameras and microphones to recognize the user's emotional state in real time. For example, it can analyze a worker's facial expressions and tone of voice to detect irritation or fatigue. Based on the detected emotional state, the server adjusts the system's behavior and interface. If the worker is irritated, the robot's movement speed can be slowed down, improving safety and work efficiency.

[0650] Hardware and software used

[0651] 1. Hardware

[0652] Camera (e.g. Logitech C920): Used to capture the facial expressions of the workers.

[0653] Microphone (e.g. Blue Yeti): Used to capture the worker's tone of voice.

[0654] 2. Software

[0655] dlib library: Used for face detection and landmark extraction.

[0656] EmotionRecognition library: Used to analyze and determine emotions from facial expressions.

[0657] Decompiler library: Decompiles robot control systems and programs.

[0658] Specific examples

[0659] In factories, when workers interact with robotic control systems, the system analyzes their emotions in real time, for example, if it detects that a worker is feeling frustrated, it can adjust the robot's movement speed to improve work safety and the experience.

[0660] Prompt Sentence Examples

[0661] "Write a program to run an application that analyzes the robot control system in a factory and generates specification documents. We will also use a camera and microphone to capture the emotions of workers. Write a program to adjust the robot's behavior according to the worker's emotional state."

[0662] In this way, a system can be constructed that simultaneously generates specification documents and optimizes the user experience.

[0663] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0664] Step 1:

[0665] A user uploads a system product file to the server using a dedicated website or application. The input is the system product file, and the output is that the file is transferred to the server and stored in temporary storage. The server then confirms that the file has been sent.

[0666] Step 2:

[0667] The server performs pre-processing to analyze the uploaded file. Here, it obtains the file's metadata and header information and identifies the file type and structure. The input is the uploaded file, and the output is information about the file type and structure. The server uses this information to prepare for the next decompilation process.

[0668] Step 3:

[0669] The server selects an appropriate decompiler and decompiles the file. The input for decompilation is the file type and structure information obtained in the previous step, along with the actual file itself. The output is high-level source code. For example, binary code is converted into C++ source code. The server saves the converted source code and prepares it for static analysis.

[0670] Step 4:

[0671] The server analyzes the decompiled source code using a static analysis tool. The input is the decompiled source code, and the output is the analysis results, such as function call relationships and inter-module dependencies. The server obtains these analysis results and uses them to generate a specification document.

[0672] Step 5:

[0673] The server automatically generates a specification document based on the analysis results. The input is the static analysis results, and the output is a specification document that describes the system overview, module configuration, function roles, library dependencies, etc. The server generates a link so that the user can download this specification document.

[0674] Step 6:

[0675] The user clicks on the provided link to download the generated specification document. The input is the download link for the specification document, and the output is the specification document downloaded to the local machine. The server verifies that the document was downloaded correctly.

[0676] Step 7:

[0677] The server activates an emotion engine and recognizes the user's emotional state in real time. The input is the user's facial expression and tone of voice captured by a camera or microphone, and the output is the user's emotional state. The server analyzes this data and determines the user's emotional state.

[0678] Step 8:

[0679] The server adjusts the system's behavior and interface based on the user's emotional state. The input is the user's emotional state output from the emotion engine, and the output is the adjusted system behavior and interface. For example, if the user is irritated, the server will adjust the robot's movement speed to slow down. The entire system is adjusted to perform optimally according to the user's emotional state.

[0680] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0681] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0682] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[0683] [Third embodiment]

[0684] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0685] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0686] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0687] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0688] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0689] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0690] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0691] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0692] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0693] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0694] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0695] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[0696] The present invention relates to a system that automatically analyzes a system product and generates a specification document when the specifications of the system product are unknown. This system is designed so that a user can upload the system product and ultimately obtain the automatically generated specification document.

[0697] A specific embodiment for implementing the system will be described below.

[0698] File upload procedure

[0699] A user selects a system product file from their device and uploads it to the server through a dedicated website or application. For example, a user selects a file called "Software A.exe" and sends it to the server. In this step, it is important that the file is sent correctly to the server.

[0700] Initial analysis of the file

[0701] The server stores the system product file received from the user in temporary storage and performs an initial analysis to determine the file type and structure. For example, it identifies that the received "Software A.exe" is an executable file and its structural physical characteristics. At this stage, the file's metadata and header information are analyzed.

[0702] Decompiling and Parsing

[0703] The server then selects an appropriate decompiler to decompile the received file. The decompilation process converts binary code or intermediate code into high-level source code. For example, the server converts the binary code extracted from "Software A.exe" into C++ source code, revealing the code's logic and internal structure.

[0704] The server then uses static analysis tools to analyze the decompiled source code. This analysis clarifies the function call relationships and inter-module dependencies in the source code. If necessary, dynamic analysis is also performed to observe runtime behavior, thereby obtaining operational characteristics that cannot be determined by static analysis alone.

[0705] Generate specification documents

[0706] Based on the analysis results, the server automatically generates a specification document, which contains detailed information such as the system overview, module configuration, function roles, and library dependencies. For example, the generated document might explain what libraries "Software A" uses and how each module works together.

[0707] Providing results

[0708] Finally, the server provides the generated specification document to the user. Specifically, it provides the user with a download link that the user can click to download the document. This download link is designed to be provided to the user safely and easily.

[0709] By going through the above process, users can obtain detailed specification documents of the original system product and use them for its operation and maintenance. This invention enables efficient system analysis and document generation, achieving a significant reduction in time and effort compared to conventional manual analysis work.

[0710] The processing flow will be explained below.

[0711] Step 1: Select the file

[0712] The user selects the file of the system product that he / she wants to reverse engineer on the terminal. For example, the user selects "Software A.exe".

[0713] Step 2: Uploading files

[0714] The user uploads the selected file to the server by clicking the "Upload" button on a dedicated website or application, and the device sends the file to the server.

[0715] Step 3: Receive the file

[0716] The server receives the file sent from the device and stores it in temporary storage. The server then verifies that the file was received correctly.

[0717] Step 4: Initial analysis

[0718] The server performs an initial analysis of the received file to determine its type and structure, checking metadata and header information to determine whether the file is an executable or library.

[0719] Step 5: Decompile

[0720] The server selects the appropriate decompiler based on the format of the file. The decompiler is used to convert the binary code into high-level source code, for example, converting "Software A.exe" into C++ source code.

[0721] Step 6: Static Analysis

[0722] The server analyzes the decompiled source code using static analysis tools to identify the code structure, function call relationships, and module dependencies.

[0723] Step 7: Dynamic analysis (if necessary)

[0724] The server emulates the execution environment of the software based on a specific scenario or use case, and uses debugging and monitoring tools to observe its behavior at runtime.

[0725] Step 8: Generate the specification document

[0726] The server automatically generates a system specification document based on the results of static and dynamic analysis, which contains detailed information such as module configuration, function roles, and library dependencies.

[0727] Step 9: Saving the Document

[0728] The server stores the generated specification document in a storage and makes it accessible to users.

[0729] Step 10: Generate a download link

[0730] The server generates a download link to the saved specification document and provides it to the user, who then downloads the document via this link.

[0731] Step 11: Retrieving Documents

[0732] The user clicks on the download link provided by the server to download the generated specification document to the terminal.

[0733] Example 1

[0734] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0735] In conventional systems, when the specifications of a system product are unknown, analyzing it and generating specification documents requires a significant amount of time and effort. Furthermore, because the analysis work is performed manually, the analysis results often lack accuracy and consistency. Therefore, there is a demand for an automated analysis system that can quickly and accurately obtain detailed system product specifications and use them for operation and maintenance.

[0736] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0737] In this invention, the server includes means for receiving an uploaded system product file, means for initially analyzing metadata and header information of the received file, means for decompiling the file based on the analysis results, means for statically analyzing the decompiled code, means for performing dynamic analysis based on the static analysis results, means for integrating the dynamic analysis results to generate a specification document, and means for providing the generated specification document to a user, thereby enabling detailed specifications of the system product to be obtained quickly and accurately.

[0738] "Uploading" is the act of a user sending a data file from their computer or device to a remote system such as a server or cloud service.

[0739] A "system product" is a software or hardware product that is designed to have specific functions and capabilities and is provided for use by users.

[0740] "File metadata" is information that is not contained in the file itself but that describes its contents and characteristics, such as the file's creation date and time, size, and author information.

[0741] "Header information" is data at the beginning of a file that defines the file's type, structure, and other important attributes.

[0742] "Initial analysis" is the initial analysis process for understanding the basic attributes and structure of received data or files.

[0743] "Decompilation" is the process of converting program code written in machine language or intermediate language into source code in a high-level language.

[0744] "Static analysis" is a technique for analyzing a program's code to find errors, potential bugs, and security vulnerabilities without running the program.

[0745] "Dynamic analysis" is a technique for analyzing problems and operating characteristics by observing the behavior and performance of a program while it is being executed.

[0746] A "specification document" is a technical document that describes in detail the structure, functions, operating conditions, dependencies, etc. of a system or software product.

[0747] "Providing" means preparing and making available a particular service or product so that it can be easily accessed by users.

[0748] This invention relates to a system that automatically analyzes a system product and generates a specification document when the specifications of the system product are unknown. This system is designed so that a user can upload the system product and ultimately obtain the automatically generated specification document.

[0749] A specific embodiment for implementing the system will be described below.

[0750] File upload procedure

[0751] The user selects the system product file from their device and uploads it to the server via a dedicated website or application. Specifically, the user opens a browser, accesses the target site, clicks the "Upload" button to display a file selection dialog, selects the file to be analyzed (e.g., "Software A.exe"), and clicks the "Submit" button again to begin uploading.

[0752] Initial analysis of the file

[0753] The server stores the file uploaded by the user in temporary storage and performs an initial analysis to determine the file's type and structure. During this stage, the server analyzes the file's metadata (e.g., creation date and file size) and header information (e.g., file format and entry point). Based on this, the server can determine that the file is an executable file and the platform it is intended for.

[0754] Decompilation and Static Analysis

[0755] The server uses a decompiler such as Ghidra or IDA Pro to decompile the file, converting the binary code into high-level source code that can be understood by humans. For example, the binary code for "Software A.exe" is converted into C++ source code. The server then performs static analysis using SonarQube or Cppcheck. Specifically, the server analyzes the code's function call relationships, inter-module dependencies, variable usage, and other aspects to identify code quality and security issues.

[0756] Dynamic Analysis

[0757] If necessary, the server performs dynamic analysis. Using tools such as Valgrind or QEMU, the server runs the program to be analyzed and observes its operating characteristics. Specifically, the server monitors the program's memory usage, CPU usage, and frequency of I / O operations to detect bugs or abnormal behavior that occur during execution. This allows the server to understand operating characteristics that cannot be determined by static analysis alone.

[0758] Generate specification documents

[0759] Based on the analysis results, the server automatically generates a specification document. This document contains detailed information such as an overview of the system, module configuration, function roles, and library dependencies. The server uses a text generation engine to generate a document describing the analysis results in natural language. Diagrams and tables are also added to this document to make the content easier to understand visually.

[0760] Providing results

[0761] Finally, the server provides the generated specification document to the user. Specifically, the server generates a download link for the user and sends a notification email containing the link. The user can easily download the document by clicking the link. This download link is secure and designed to be user-friendly.

[0762] As a concrete example, the following scenario can be considered.

[0763] If a user has a file called "SoftwareB.exe" that they want to analyze, they can use a prompt statement like this:

[0764] "Please upload the following file and automatically generate its specification document: Software B.exe"

[0765] Through these efforts, users can quickly and accurately obtain detailed specification documents and use them for operation and maintenance. This system significantly reduces the time and effort required compared to conventional manual analysis work.

[0766] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0767] Step 1: Upload a file

[0768] The user selects a system product file from their device and uploads it to the server via a dedicated website or application. Specifically, the user opens a browser, accesses the target site, and clicks the "Upload" button to display a file selection dialog. Next, the user selects the file to be analyzed, such as "Software A.exe," and clicks the "Submit" button again to begin uploading. The input is the target file on the user's device, and the output is the uploaded file saved on the server.

[0769] Step 2: Initial analysis of the file

[0770] The server stores the file uploaded by the user in temporary storage and performs an initial analysis to determine the file's type and structure. Specifically, the server analyzes the file's metadata (e.g., creation date and time, file size) and header information (e.g., file format, entry point). The input is the uploaded file, and the output is the analysis results, including the file's metadata and header information.

[0771] Step 3: Decompile

[0772] The server decompiles the file using an appropriate decompiler (e.g., Ghidra, IDA Pro) and converts the binary code into high-level source code that can be understood by humans. Specifically, the server converts the binary code of "Software A.exe" into C++ source code. The input is a file containing the initial analysis results, and the output is the decompiled source code.

[0773] Step 4: Static Analysis

[0774] The server uses a static analysis tool (e.g., SonarQube, Cppcheck) to analyze the decompiled source code. Specifically, the server analyzes the code's function call relationships, inter-module dependencies, variable usage, etc. to identify code quality and security issues. The input is the decompiled source code, and the output is the static analysis results.

[0775] Step 5: Dynamic Analysis

[0776] If necessary, the server performs dynamic analysis. Using a dynamic analysis tool (e.g., Valgrind or QEMU), the server executes the program to be analyzed and observes its operating characteristics. Specifically, the server monitors the program's memory usage, CPU usage, and frequency of I / O operations to detect bugs or abnormal behavior that occur during execution. The input is the static analysis results and decompiled source code, and the output is the dynamic analysis results.

[0777] Step 6: Generate the specification document

[0778] The server automatically generates a specification document based on the analysis results. Specifically, the server uses a text generation engine to generate a document that details the system overview, module configuration, function roles, library dependencies, etc. This document also includes diagrams and tables. The input is the static and dynamic analysis results, and the output is a specification document.

[0779] Step 7: Delivering the results

[0780] The server provides the generated specification document to the user. Specifically, the server generates a download link for the user and sends a notification email containing this link. The user can easily download the document by clicking the link. The input is the specification document, and the output is providing the download link to the user.

[0781] This system allows users to quickly and accurately obtain detailed specification documents and use them for operation and maintenance.

[0782] (Application example 1)

[0783] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0784] Factory robots have complex software systems, and analyzing them and creating specification documents requires a great deal of effort and time. Furthermore, when detailed analysis of unknown system products is required, conventional methods are inefficient and may hinder production efficiency. Furthermore, accurately understanding software functions and dependencies requires advanced expertise. To solve these problems, a system is needed that can easily and quickly analyze software and automatically generate specification documents.

[0785] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0786] In this invention, the server includes means for receiving a system product file, means for analyzing the received file, means for generating a specification document based on the analysis results, means for providing the generated specification document to a user, means for analyzing the factory robot software, means for static analysis for extracting software functions and dependencies, and means for providing the generated specification document in PDF format, thereby enabling a user to easily and quickly analyze the factory robot software and obtain the results as a detailed specification document.

[0787] "System product file" means an electronic file containing software or program code for a factory robot.

[0788] "Analyzing" refers to the process of analyzing the contents and structure of a file in detail using analytical tools.

[0789] A "specification document" is a document created based on the analysis results that describes the functions and dependencies of the factory robot software.

[0790] "Providing to users" refers to the process of providing the generated specification document to users in a form that is easily accessible to them.

[0791] "Factory robot" is a general term for robots used in automated factories.

[0792] A "software function" is a set of operations or calculations performed by a factory robot's software.

[0793] "Dependencies" refer to the relationships between libraries and modules that are required for software to function.

[0794] "Static analysis" is a technique for analyzing software structure, code functions, dependencies, etc. without running the software.

[0795] "PDF format" is an abbreviation for Portable Document Format, and is a file format for saving and displaying specification documents in a visually easy-to-read format.

[0796] The present invention provides a system that allows a user to upload a software file for a factory robot, analyzes the file on a server, and automatically generates a detailed specification document. Specific embodiments are described below.

[0797] System Program

[0798] The program of this system consists of the following major components:

[0799] 1. File upload interface

[0800] An interface for users to upload factory robot software files, which can be provided as a smartphone application or web application.

[0801] 2. Initial Analysis Module

[0802] The server receives the uploaded file and analyzes the file type and structure.

[0803] 3. Decompilation Module

[0804] It decompiles the received files, converting the binary code into high-level source code.

[0805] 4. Static Analysis Module

[0806] It analyzes decompiled source code and extracts software functions and dependencies.

[0807] 5. Document Generation Module

[0808] Based on the analysis results, a detailed specification document is automatically generated in PDF format.

[0809] 6. Result Delivery Module

[0810] Provide the generated specification document to the user and send a download link.

[0811] Natural language explanations

[0812] First, a user uses a smartphone or computer to upload the factory robot's software file to the server via a dedicated interface. The server first stores the received file in temporary storage. Next, the initial analysis module analyzes the file type and structure. For example, if a file named "RobotControlV2.0.exe" is received, it will identify it as an executable file. This analysis uses metadata and file header information.

[0813] Next, the decompilation module uses a decompiler tool to convert the file into high-level source code, for example, C++ source code, and the static analysis module analyzes the source code for functions and dependencies, extracting functions and libraries such as "function1" and "lib1."

[0814] Based on these analysis results, the document generation module automatically generates a specification document in PDF format. Finally, the generated specification document is provided to the user as a download link via the result provision module.

[0815] Specific examples

[0816] For example, if a factory production manager needs to analyze the software for a factory robot called "RobotControlV2.0.exe" and find out the detailed specifications of the libraries and internal modules it uses, he or she might enter the following prompt into the system:

[0817] Analyze the factory robot software "RobotControlV2.0.exe" and generate a detailed specification document of the libraries and internal modules it uses. The following file was uploaded from a smartphone.

[0818] This invention enables users to efficiently and accurately analyze factory robot software and obtain detailed specification documents without requiring specialized knowledge, significantly improving factory production and maintenance efficiency.

[0819] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0820] Step 1:

[0821] The user uploads the factory robot's software file to the server through a dedicated interface. As input, the user selects the executable file "RobotControlV2.0.exe" on their smartphone or computer and presses the upload button. This action sends the file to the server. As output, the file is accurately saved in temporary storage on the server side.

[0822] Step 2:

[0823] The server passes the received file to the initial analysis module, which analyzes the file type and structure. As input, the uploaded "RobotControlV2.0.exe" file is provided. The server reads the file header and metadata and identifies it as an executable file. As output, the file type and basic structure information are obtained.

[0824] Step 3:

[0825] The server uses a decompilation module to convert the parsed files into high-level source code. As input, it is provided with the binary code of the executable file "RobotControlV2.0.exe". The server runs the decompiler tool and converts the binary code into "C++" source code. As output, it gets the decompiled high-level source code.

[0826] Step 4:

[0827] The server uses a static analysis module to analyze the decompiled source code and extract software functions and dependencies. As input, the decompiled source code is provided. The server runs a static code analysis tool to extract function definitions (e.g., "function1", "function2") and dependent libraries (e.g., "lib1", "lib2"). As output, the functionality and dependency information of the source code is obtained.

[0828] Step 5:

[0829] The server uses a document generation module to automatically generate a specification document in PDF format based on the analysis results. The analysis results of the software's functions and dependencies are provided as input. The server uses a PDF generation library (e.g., ReportLab) to generate a PDF document containing the software's detailed specifications. The output is a specification document in PDF format.

[0830] Step 6:

[0831] The server provides the generated specification document to the user through the result delivery module and sends a download link. The generated PDF document is provided as input. The server generates a secure download link and displays it on the user's interface or sends it by email. The user can then download the specification document by clicking the provided download link. As output, the user gets a specification document that details the analysis results.

[0832] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0833] This invention relates to a system that automatically analyzes a system product and generates specification documents when the specifications are unknown. Furthermore, by combining it with an emotion engine that recognizes the user's emotions, it aims to improve the user experience. This system automates the entire process from receiving files to analyzing them, generating documents, and providing them to the user, enabling flexible responses according to the user's emotional state.

[0834] A specific embodiment for implementing the system will be described below.

[0835] Initial file upload and analysis

[0836] A user selects a system product file from their device and uploads it to the server through a dedicated website or application. For example, a user selects a file called "Software A.exe" and sends it to the server. In this step, it is important that the file is sent correctly to the server.

[0837] The server stores the file received from the user in temporary storage and performs an initial analysis to determine the file type and structure. For example, it identifies that the received file "Software A.exe" is an executable file and its physical structural characteristics. At this stage, the file's metadata and header information are analyzed.

[0838] Decompilation and Static Analysis

[0839] The server then selects an appropriate decompiler to decompile the received file. The decompilation process converts binary code or intermediate code into high-level source code. For example, the server converts the binary code extracted from "Software A.exe" into C++ source code, revealing the code's logic and internal structure.

[0840] The server then uses static analysis tools to analyze the decompiled source code. This analysis clarifies the function call relationships and inter-module dependencies in the source code. If necessary, dynamic analysis is also performed to observe runtime behavior, thereby obtaining operational characteristics that cannot be determined by static analysis alone.

[0841] The role of the emotional engine

[0842] The emotion engine recognizes the user's emotional state and adjusts the system's behavior and user interface based on the results. For example, if a user is feeling irritated or dissatisfied while using the system, the emotion engine will detect this and improve the user experience by increasing the system's response speed and simplifying operation procedures.

[0843] The emotion engine analyzes the user's facial expressions and tone of voice through sensors such as cameras and microphones to evaluate their emotional state in real time, allowing the system to reflect the user's current emotional state.

[0844] Generate and provide specification documents

[0845] Based on the analysis results, the server automatically generates a specification document, which contains detailed information such as the system overview, module configuration, function roles, and library dependencies. For example, the generated document might explain what libraries "Software A" uses and how each module works together.

[0846] Finally, the server provides the generated specification document to the user. Specifically, it provides the user with a download link that the user can click to download the document. This download link is designed to be provided to the user safely and easily.

[0847] By going through the above process, users can obtain detailed specification documents of the original system product, which can be used for its operation and maintenance.Furthermore, the introduction of an emotion engine enables flexible responses according to the user's emotional state, improving the overall user experience.

[0848] The processing flow will be explained below.

[0849] Step 1: Select the file

[0850] The user selects the file of the system product to be reverse engineered from his / her own terminal. For example, the user selects "Software A.exe".

[0851] Step 2: Uploading files

[0852] The user clicks the "Upload" button on a dedicated website or application to upload the selected file to the server, and the device sends the selected file to the server.

[0853] Step 3: Receive the file

[0854] The server receives the file sent from the device and stores it in temporary storage. The server then verifies that the file was received correctly.

[0855] Step 4: Initial analysis

[0856] The server performs an initial analysis of the received file to identify its type and structure. It checks the metadata and header information to determine whether the file is executable or library format. For example, it determines that "Software A.exe" is an executable file.

[0857] Step 5: Decompile

[0858] The server selects the appropriate decompiler based on the file format. The decompiler is used to convert the binary code into high-level source code. For example, from "Software A.exe", it generates C++ source code.

[0859] Step 6: Static Analysis

[0860] The server analyzes the decompiled source code using static analysis tools to identify the code structure, function call relationships, and module dependencies, thereby revealing the internal structure and interrelationships of the source code.

[0861] Step 7: Dynamic analysis (if necessary)

[0862] The server emulates the execution environment of the software based on a specific scenario or use case, and uses debugging and monitoring tools to observe its behavior during runtime, thereby obtaining runtime characteristics that cannot be obtained through static analysis.

[0863] Step 8: Emotion Recognition with the Emotion Engine

[0864] The server uses an emotion engine to analyze the user's facial expressions and voice from sensors such as cameras and microphones installed on the user's device, and recognizes the user's emotional state in real time, for example, identifying whether the user is feeling anxious or irritated.

[0865] Step 9: Adjust your system to your emotions

[0866] The server dynamically adjusts the system's behavior and user interface based on the analysis results of the emotion engine. For example, if the user is frustrated, the server can speed up the system's response or simplify the operation procedure, thus improving the user experience.

[0867] Step 10: Generate the specification document

[0868] The server automatically generates a system specification document based on the results of static and dynamic analysis. The document contains details such as an overview of the system, module configuration, function roles, and library dependencies. For example, the generated document might explain which libraries "Software A" uses and how each module works together.

[0869] Step 11: Saving the Document

[0870] The server stores the generated specification document in a storage and makes it accessible to users.

[0871] Step 12: Generate a download link

[0872] The server generates a download link to the saved specification document and provides it to the user, who can then download the document via this link.

[0873] Step 13: Retrieving Documents

[0874] The user clicks the download link provided by the server to download the generated specification document to their device, allowing them to use detailed system information obtained as a result of the analysis.

[0875] Example 2

[0876] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0877] Conventional system analysis methods require a great deal of time and effort to understand the detailed specifications of a system product, and analyzing the product is particularly difficult when specifications are not available. Furthermore, there is no mechanism to reduce the emotional stress that accompanies user operations, which can lead to a poor user experience.

[0878] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0879] In this invention, the server includes means for receiving a system product file, means for temporarily storing the received file and initially analyzing its type and structure, means for decompiling the initially analyzed file, means for statically and dynamically analyzing the decompiled source code, means for detecting the user's emotional state, means for generating a specification document based on the analysis results and the user's emotional state, and means for providing the generated specification document to the user. This makes it possible to automatically obtain detailed specifications of the system product and flexibly respond to user emotions.

[0880] "System product" refers to a comprehensive product that is composed of various software and hardware and provides functions for a specific purpose.

[0881] "File" refers to a collection of digital data that records components of a system product.

[0882] "Temporary storage" refers to the practice of temporarily storing data for access or processing.

[0883] "Initial Analysis" refers to the process of initial data analysis to determine file type and structure.

[0884] "Decompilation" refers to the process of converting binary code or intermediate form code into high-level source code.

[0885] "Static analysis" refers to a technique for evaluating program behavior by analyzing the syntax and structure of the source code without executing it.

[0886] "Dynamic analysis" refers to a method of observing and analyzing the operating characteristics of software while it is running.

[0887] "Emotional state" refers to an emotional response that reflects a user's current state of mind or psychology.

[0888] A "specification document" refers to a document that describes the detailed specifications, structure, and operating characteristics of a system product.

[0889] "Providing" refers to the act of providing generated information or services to users in an accessible form.

[0890] This invention relates to a system that automatically analyzes a system product and generates specification documents when the specifications are unknown. Furthermore, by combining it with an emotion engine that recognizes the user's emotions, it aims to improve the user experience. This system automates the entire process from receiving files to analyzing them, generating documents, and providing them to the user, enabling flexible responses according to the user's emotional state.

[0891] Hardware and Software Use

[0892] To implement the system, the following hardware and software must be used:

[0893] Server: A server equipped with a high-performance processor and a large amount of memory is used. The server stores files, performs analysis, generates documents, and processes the emotion engine.

[0894] Terminal: A computer or mobile device used by a user to upload files or download generated documents.

[0895] Website or application: Used as an interface for users to upload files.

[0896] Decompiler: For example, using IDA Pro or Decompiler, converting binary code into high-level source code.

[0897] Static analysis tools: For example, SonarQube or CppDepend are used to analyze the source code.

[0898] Emotion engine: Software that uses a camera and microphone to analyze a user's facial expressions and tone of voice to assess their emotional state.

[0899] Process example

[0900] 1. File Upload

[0901] The user selects the system product file they want to analyze from their device and uploads it to the server via a dedicated website or application. For example, the user selects the file "Software A.exe" and clicks the upload button. At this time, the device sends the file to the server.

[0902] 2. Initial analysis

[0903] The server stores the uploaded file in temporary storage and performs an initial analysis to determine its type and structure. Specifically, the server analyzes the metadata and header information of the received "Software A.exe" file to confirm that it is an executable file. At this stage, the server also obtains the file's size, creation date and time, hash value, etc.

[0904] 3. Decompilation

[0905] The server selects an appropriate decompiler and decompiles the received file. Specifically, it converts the binary code of "Software A.exe" into high-level source code (e.g., C++) using a decompilation tool (e.g., IDA Pro or Decompiler). The server performs this process asynchronously and stores the results in temporary storage.

[0906] 4. Static and Dynamic Analysis

[0907] The server analyzes the decompiled source code using a static analysis tool (such as SonarQube or CppDepend). Specifically, it identifies function call relationships and inter-module dependencies. It also performs dynamic analysis as needed, running the program in a simulator or sandbox environment to closely observe its operating characteristics. This allows it to understand things like memory usage, CPU load, and network communication patterns during runtime.

[0908] 5. Operation of the Emotion Engine

[0909] The server runs an emotion engine to detect user emotions in real time. When a user operates the system, facial expressions and voice are captured through the device's camera and microphone. Specifically, the server analyzes the camera images and identifies the user's emotional state using a facial expression recognition algorithm (e.g., OpenFace or Microsoft Face API). Voice data is also analyzed to evaluate emotions based on the tone and content of the voice.

[0910] 6. Generating and Providing Specification Documents

[0911] The server automatically generates a specification document based on the analysis results. Specifically, it integrates the results of the analysis tools and creates a document that includes a system overview, module configuration, function roles, library dependencies, etc. This document is generated in formats such as Markdown, PDF, and HTML, making it easy for users to access.

[0912] Finally, the server provides the generated specification document to the user. Specifically, it generates a download link for the document and notifies the user. The user can click this link to download the document to their device. The download link is provided via a secure protocol (e.g., HTTPS) to ensure safe and fast access.

[0913] Prompt Sentence Examples

[0914] How can the system automatically analyze unknown product files and generate detailed specification documents? Please also provide details on the specific steps from file upload to document submission, the tools used, and the analysis process.

[0915]

[0916] How can an emotion engine be used to improve the user experience? Give an example of how you can detect and respond to frustrations that users may experience while interacting with a system.

[0917] Through the above process, users can easily obtain detailed specification documents, and the emotion engine can improve the user experience.

[0918] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0919] Step 1: File Upload

[0920] The user selects the system product file to be analyzed from their own device and uploads it to the server via a dedicated website or application.

[0921] Input: System product file (e.g. Software A.exe)

[0922] Specific operation: The user clicks the upload button and the device sends the file to the server.

[0923] Output: The file uploaded to the server.

[0924] Step 2: Initial analysis of the file

[0925] The server temporarily stores the received files and performs an initial analysis to determine their type and structure.

[0926] Input: A file uploaded to the server

[0927] What happens: The server parses the metadata and header information to determine the file type (e.g., executable).

[0928] Output: File type, metadata (e.g. size, creation date, hash value)

[0929] Step 3: Decompile

[0930] The server selects the appropriate decompiler and performs the decompilation of the file.

[0931] Input: The initial parsed file and its metadata

[0932] Specific operation: The server uses a decompilation tool (e.g., IDA Pro, Decompiler) to convert the binary code into high-level source code (e.g., C++).

[0933] Output: Decompiled source code

[0934] Step 4: Static and Dynamic Analysis

[0935] The server analyzes the decompiled source code using static and dynamic analysis tools.

[0936] Input: Decompiled source code

[0937] Specific operation: The server identifies function call relationships and module dependencies using static analysis tools (e.g., SonarQube, CppDepend), and if necessary, uses dynamic analysis tools to examine runtime behavior.

[0938] Output: Analysis results (e.g., function call graph, module dependencies, behavioral characteristics)

[0939] Step 5: Detecting user emotions with the emotion engine

[0940] The server detects user emotions in real time.

[0941] Input: Camera image and audio data from the user device

[0942] How it works: The server analyzes camera images and uses facial expression recognition algorithms (e.g., OpenFace, Microsoft Face API) to identify emotional states. It also analyzes audio data and assesses emotions based on tone and content.

[0943] Output: User's emotional state (e.g., annoyed, frustrated, satisfied)

[0944] Step 6: Generate the specification document

[0945] The server generates a specification document based on the analysis results and the user's emotional state.

[0946] Input: Analysis results and user's emotional state

[0947] What it does: The server integrates the results of the analysis tools and creates a document that includes an overview of the system, module structure, function roles, library dependencies, etc.

[0948] Output: Generated specification document (e.g. Markdown, PDF, HTML)

[0949] Step 7: Provide documentation

[0950] The server provides the generated specification document to the user.

[0951] Input: Generated specification document

[0952] Specific operation: The server generates a download link for the document and notifies the user. The user clicks on this link to download the document to their device.

[0953] Output: User downloaded specification document

[0954] (Application example 2)

[0955] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0956] Currently, when the specifications of a system product are unknown, analyzing them and generating specification documents is extremely time-consuming, and the process can be frustrating for users. Furthermore, there is a lack of a way to detect in real time the stress or frustration felt by on-site workers regarding system operation or interfaces, and provide optimal feedback accordingly. This leads to issues such as reduced work efficiency and a worsening user experience.

[0957] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0958] In this invention, the server includes means for receiving a system product file, means for analyzing the received file, means for generating a specification document based on the analysis results, and means for recognizing the user's emotional state and adjusting the system operation and user interface. This not only automates the generation of the specification document, but also makes it possible to provide real-time feedback according to the user's emotions.

[0959] "System product files" are executable files and configuration files necessary for the operation of a particular system, such as software or control programs.

[0960] "Analysis" is the process of interpreting the contents of a file or program to understand its structure and behavior.

[0961] A "specification document" is a document that describes in detail the behavior, functions, design, dependencies, etc. of a system or software.

[0962] "User" means the ultimate user who operates or utilizes the system.

[0963] "Means for receiving" refers to the function or method for receiving system product files from users.

[0964] "Means of analysis" refers to a method for interpreting the received file and clarifying its internal structure and operation.

[0965] "Means for generating" refers to a method for automatically creating a specification document based on the analysis results.

[0966] The "means for providing" is a method or function for presenting the generated specification document to the user.

[0967] An "emotional state" is a psychological state that indicates a user's current mood or feelings.

[0968] "Means for recognizing and adjusting emotional states" refers to a method or function that uses sensors such as cameras and microphones to detect a user's emotions in real time and changes the system's behavior or interface based on the results.

[0969] "Decompilation" is the process of converting binary or intermediate form code into high-level source code.

[0970] "Static analysis" is the process of analyzing a program's source code and structure without executing it.

[0971] The present invention is a system that automatically analyzes files of a system product, generates specification documents, and further includes a function for recognizing user emotions and adjusting the operation of the system. Specific embodiments of the present invention will be described below.

[0972] File upload and initial analysis

[0973] Users upload system product files to the server using a dedicated website or application. The uploaded file is stored in temporary storage, where its metadata and structure are initially analyzed. For example, if a file such as "control program.exe" is uploaded, it is identified as an executable file and its physical characteristics are identified.

[0974] Decompilation and Static Analysis

[0975] The server uses a decompiler to decompile the received file. The decompiled code is converted into a high-level language and then analyzed using a static analysis tool. Static analysis reveals the function call relationships and inter-module dependencies. For example, "control program.exe" is converted into C++ source code, and the function connections are analyzed from that code.

[0976] Generate specification documents

[0977] Based on the results of decompilation and static analysis, the server automatically generates a specification document that details the system overview, module structure, function roles, library dependencies, etc. The generated specification document is provided to the user via a download link.

[0978] Emotion recognition and system behavior adjustment

[0979] The emotion engine uses sensors such as cameras and microphones to recognize the user's emotional state in real time. For example, it can analyze a worker's facial expressions and tone of voice to detect irritation or fatigue. Based on the detected emotional state, the server adjusts the system's behavior and interface. If the worker is irritated, the robot's movement speed can be slowed down, improving safety and work efficiency.

[0980] Hardware and software used

[0981] 1. Hardware

[0982] Camera (e.g. Logitech C920): Used to capture the facial expressions of the workers.

[0983] Microphone (e.g. Blue Yeti): Used to capture the worker's tone of voice.

[0984] 2. Software

[0985] dlib library: Used for face detection and landmark extraction.

[0986] EmotionRecognition library: Used to analyze and determine emotions from facial expressions.

[0987] Decompiler library: Decompiles robot control systems and programs.

[0988] Specific examples

[0989] In factories, when workers interact with robotic control systems, the system analyzes their emotions in real time, for example, if it detects that a worker is feeling frustrated, it can adjust the robot's movement speed to improve work safety and the experience.

[0990] Prompt Sentence Examples

[0991] "Write a program to run an application that analyzes the robot control system in a factory and generates specification documents. We will also use a camera and microphone to capture the emotions of workers. Write a program to adjust the robot's behavior according to the worker's emotional state."

[0992] In this way, a system can be constructed that simultaneously generates specification documents and optimizes the user experience.

[0993] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0994] Step 1:

[0995] A user uploads a system product file to the server using a dedicated website or application. The input is the system product file, and the output is that the file is transferred to the server and stored in temporary storage. The server then confirms that the file has been sent.

[0996] Step 2:

[0997] The server performs pre-processing to analyze the uploaded file. Here, it obtains the file's metadata and header information and identifies the file type and structure. The input is the uploaded file, and the output is information about the file type and structure. The server uses this information to prepare for the next decompilation process.

[0998] Step 3:

[0999] The server selects an appropriate decompiler and decompiles the file. The input for decompilation is the file type and structure information obtained in the previous step, along with the actual file itself. The output is high-level source code. For example, binary code is converted into C++ source code. The server saves the converted source code and prepares it for static analysis.

[1000] Step 4:

[1001] The server analyzes the decompiled source code using a static analysis tool. The input is the decompiled source code, and the output is the analysis results, such as function call relationships and inter-module dependencies. The server obtains these analysis results and uses them to generate a specification document.

[1002] Step 5:

[1003] The server automatically generates a specification document based on the analysis results. The input is the static analysis results, and the output is a specification document that describes the system overview, module configuration, function roles, library dependencies, etc. The server generates a link so that the user can download this specification document.

[1004] Step 6:

[1005] The user clicks on the provided link to download the generated specification document. The input is the download link for the specification document, and the output is the specification document downloaded to the local machine. The server verifies that the document was downloaded correctly.

[1006] Step 7:

[1007] The server activates an emotion engine and recognizes the user's emotional state in real time. The input is the user's facial expression and tone of voice captured by a camera or microphone, and the output is the user's emotional state. The server analyzes this data and determines the user's emotional state.

[1008] Step 8:

[1009] The server adjusts the system's behavior and interface based on the user's emotional state. The input is the user's emotional state output from the emotion engine, and the output is the adjusted system behavior and interface. For example, if the user is irritated, the server will adjust the robot's movement speed to slow down. The entire system is adjusted to perform optimally according to the user's emotional state.

[1010] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1011] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1012] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1013] [Fourth embodiment]

[1014] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1015] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1016] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1017] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1018] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1019] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1020] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1021] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1022] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1023] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1024] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1025] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1026] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1027] The present invention relates to a system that automatically analyzes a system product and generates a specification document when the specifications of the system product are unknown. This system is designed so that a user can upload the system product and ultimately obtain the automatically generated specification document.

[1028] A specific embodiment for implementing the system will be described below.

[1029] File upload procedure

[1030] A user selects a system product file from their device and uploads it to the server through a dedicated website or application. For example, a user selects a file called "Software A.exe" and sends it to the server. In this step, it is important that the file is sent correctly to the server.

[1031] Initial analysis of the file

[1032] The server stores the system product file received from the user in temporary storage and performs an initial analysis to determine the file type and structure. For example, it identifies that the received "Software A.exe" is an executable file and its structural physical characteristics. At this stage, the file's metadata and header information are analyzed.

[1033] Decompiling and Parsing

[1034] The server then selects an appropriate decompiler to decompile the received file. The decompilation process converts binary code or intermediate code into high-level source code. For example, the server converts the binary code extracted from "Software A.exe" into C++ source code, revealing the code's logic and internal structure.

[1035] The server then uses static analysis tools to analyze the decompiled source code. This analysis clarifies the function call relationships and inter-module dependencies in the source code. If necessary, dynamic analysis is also performed to observe runtime behavior, thereby obtaining operational characteristics that cannot be determined by static analysis alone.

[1036] Generate specification documents

[1037] Based on the analysis results, the server automatically generates a specification document, which contains detailed information such as the system overview, module configuration, function roles, and library dependencies. For example, the generated document might explain what libraries "Software A" uses and how each module works together.

[1038] Providing results

[1039] Finally, the server provides the generated specification document to the user. Specifically, it provides the user with a download link that the user can click to download the document. This download link is designed to be provided to the user safely and easily.

[1040] By going through the above process, users can obtain detailed specification documents of the original system product and use them for its operation and maintenance. This invention enables efficient system analysis and document generation, achieving a significant reduction in time and effort compared to conventional manual analysis work.

[1041] The processing flow will be explained below.

[1042] Step 1: Select the file

[1043] The user selects the file of the system product that he / she wants to reverse engineer on the terminal. For example, the user selects "Software A.exe".

[1044] Step 2: Uploading files

[1045] The user uploads the selected file to the server by clicking the "Upload" button on a dedicated website or application, and the device sends the file to the server.

[1046] Step 3: Receive the file

[1047] The server receives the file sent from the device and stores it in temporary storage. The server then verifies that the file was received correctly.

[1048] Step 4: Initial analysis

[1049] The server performs an initial analysis of the received file to determine its type and structure, checking metadata and header information to determine whether the file is an executable or library.

[1050] Step 5: Decompile

[1051] The server selects the appropriate decompiler based on the format of the file. The decompiler is used to convert the binary code into high-level source code, for example, converting "Software A.exe" into C++ source code.

[1052] Step 6: Static Analysis

[1053] The server analyzes the decompiled source code using static analysis tools to identify the code structure, function call relationships, and module dependencies.

[1054] Step 7: Dynamic analysis (if necessary)

[1055] The server emulates the execution environment of the software based on a specific scenario or use case, and uses debugging and monitoring tools to observe its behavior at runtime.

[1056] Step 8: Generate the specification document

[1057] The server automatically generates a system specification document based on the results of static and dynamic analysis, which contains detailed information such as module configuration, function roles, and library dependencies.

[1058] Step 9: Saving the Document

[1059] The server stores the generated specification document in a storage and makes it accessible to users.

[1060] Step 10: Generate a download link

[1061] The server generates a download link to the saved specification document and provides it to the user, who then downloads the document via this link.

[1062] Step 11: Retrieving Documents

[1063] The user clicks on the download link provided by the server to download the generated specification document to the terminal.

[1064] Example 1

[1065] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1066] In conventional systems, when the specifications of a system product are unknown, analyzing it and generating specification documents requires a significant amount of time and effort. Furthermore, because the analysis work is performed manually, the analysis results often lack accuracy and consistency. Therefore, there is a demand for an automated analysis system that can quickly and accurately obtain detailed system product specifications and use them for operation and maintenance.

[1067] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1068] In this invention, the server includes means for receiving an uploaded system product file, means for initially analyzing metadata and header information of the received file, means for decompiling the file based on the analysis results, means for statically analyzing the decompiled code, means for performing dynamic analysis based on the static analysis results, means for integrating the dynamic analysis results to generate a specification document, and means for providing the generated specification document to a user, thereby enabling detailed specifications of the system product to be obtained quickly and accurately.

[1069] "Uploading" is the act of a user sending a data file from their computer or device to a remote system such as a server or cloud service.

[1070] A "system product" is a software or hardware product that is designed to have specific functions and capabilities and is provided for use by users.

[1071] "File metadata" is information that is not contained in the file itself but that describes its contents and characteristics, such as the file's creation date and time, size, and author information.

[1072] "Header information" is data at the beginning of a file that defines the file's type, structure, and other important attributes.

[1073] "Initial analysis" is the initial analysis process for understanding the basic attributes and structure of received data or files.

[1074] "Decompilation" is the process of converting program code written in machine language or intermediate language into source code in a high-level language.

[1075] "Static analysis" is a technique for analyzing a program's code to find errors, potential bugs, and security vulnerabilities without running the program.

[1076] "Dynamic analysis" is a technique for analyzing problems and operating characteristics by observing the behavior and performance of a program while it is being executed.

[1077] A "specification document" is a technical document that describes in detail the structure, functions, operating conditions, dependencies, etc. of a system or software product.

[1078] "Providing" means preparing and making available a particular service or product so that it can be easily accessed by users.

[1079] This invention relates to a system that automatically analyzes a system product and generates a specification document when the specifications of the system product are unknown. This system is designed so that a user can upload the system product and ultimately obtain the automatically generated specification document.

[1080] A specific embodiment for implementing the system will be described below.

[1081] File upload procedure

[1082] The user selects the system product file from their device and uploads it to the server via a dedicated website or application. Specifically, the user opens a browser, accesses the target site, clicks the "Upload" button to display a file selection dialog, selects the file to be analyzed (e.g., "Software A.exe"), and clicks the "Submit" button again to begin uploading.

[1083] Initial analysis of the file

[1084] The server stores the file uploaded by the user in temporary storage and performs an initial analysis to determine the file's type and structure. During this stage, the server analyzes the file's metadata (e.g., creation date and file size) and header information (e.g., file format and entry point). Based on this, the server can determine that the file is an executable file and the platform it is intended for.

[1085] Decompilation and Static Analysis

[1086] The server uses a decompiler such as Ghidra or IDA Pro to decompile the file, converting the binary code into high-level source code that can be understood by humans. For example, the binary code for "Software A.exe" is converted into C++ source code. The server then performs static analysis using SonarQube or Cppcheck. Specifically, the server analyzes the code's function call relationships, inter-module dependencies, variable usage, and other aspects to identify code quality and security issues.

[1087] Dynamic Analysis

[1088] If necessary, the server performs dynamic analysis. Using tools such as Valgrind or QEMU, the server runs the program to be analyzed and observes its operating characteristics. Specifically, the server monitors the program's memory usage, CPU usage, and frequency of I / O operations to detect bugs or abnormal behavior that occur during execution. This allows the server to understand operating characteristics that cannot be determined by static analysis alone.

[1089] Generate specification documents

[1090] Based on the analysis results, the server automatically generates a specification document. This document contains detailed information such as an overview of the system, module configuration, function roles, and library dependencies. The server uses a text generation engine to generate a document describing the analysis results in natural language. Diagrams and tables are also added to this document to make the content easier to understand visually.

[1091] Providing results

[1092] Finally, the server provides the generated specification document to the user. Specifically, the server generates a download link for the user and sends a notification email containing the link. The user can easily download the document by clicking the link. This download link is secure and designed to be user-friendly.

[1093] As a concrete example, the following scenario can be considered.

[1094] If a user has a file called "SoftwareB.exe" that they want to analyze, they can use a prompt statement like this:

[1095] "Please upload the following file and automatically generate its specification document: Software B.exe"

[1096] Through these efforts, users can quickly and accurately obtain detailed specification documents and use them for operation and maintenance. This system significantly reduces the time and effort required compared to conventional manual analysis work.

[1097] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1098] Step 1: Upload a file

[1099] The user selects a system product file from their device and uploads it to the server via a dedicated website or application. Specifically, the user opens a browser, accesses the target site, and clicks the "Upload" button to display a file selection dialog. Next, the user selects the file to be analyzed, such as "Software A.exe," and clicks the "Submit" button again to begin uploading. The input is the target file on the user's device, and the output is the uploaded file saved on the server.

[1100] Step 2: Initial analysis of the file

[1101] The server stores the file uploaded by the user in temporary storage and performs an initial analysis to determine the file's type and structure. Specifically, the server analyzes the file's metadata (e.g., creation date and time, file size) and header information (e.g., file format, entry point). The input is the uploaded file, and the output is the analysis results, including the file's metadata and header information.

[1102] Step 3: Decompile

[1103] The server decompiles the file using an appropriate decompiler (e.g., Ghidra, IDA Pro) and converts the binary code into high-level source code that can be understood by humans. Specifically, the server converts the binary code of "Software A.exe" into C++ source code. The input is a file containing the initial analysis results, and the output is the decompiled source code.

[1104] Step 4: Static Analysis

[1105] The server uses a static analysis tool (e.g., SonarQube, Cppcheck) to analyze the decompiled source code. Specifically, the server analyzes the code's function call relationships, inter-module dependencies, variable usage, etc. to identify code quality and security issues. The input is the decompiled source code, and the output is the static analysis results.

[1106] Step 5: Dynamic Analysis

[1107] If necessary, the server performs dynamic analysis. Using a dynamic analysis tool (e.g., Valgrind or QEMU), the server executes the program to be analyzed and observes its operating characteristics. Specifically, the server monitors the program's memory usage, CPU usage, and frequency of I / O operations to detect bugs or abnormal behavior that occur during execution. The input is the static analysis results and decompiled source code, and the output is the dynamic analysis results.

[1108] Step 6: Generate the specification document

[1109] The server automatically generates a specification document based on the analysis results. Specifically, the server uses a text generation engine to generate a document that details the system overview, module configuration, function roles, library dependencies, etc. This document also includes diagrams and tables. The input is the static and dynamic analysis results, and the output is a specification document.

[1110] Step 7: Delivering the results

[1111] The server provides the generated specification document to the user. Specifically, the server generates a download link for the user and sends a notification email containing this link. The user can easily download the document by clicking the link. The input is the specification document, and the output is providing the download link to the user.

[1112] This system allows users to quickly and accurately obtain detailed specification documents and use them for operation and maintenance.

[1113] (Application example 1)

[1114] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1115] Factory robots have complex software systems, and analyzing them and creating specification documents requires a great deal of effort and time. Furthermore, when detailed analysis of unknown system products is required, conventional methods are inefficient and may hinder production efficiency. Furthermore, accurately understanding software functions and dependencies requires advanced expertise. To solve these problems, a system is needed that can easily and quickly analyze software and automatically generate specification documents.

[1116] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1117] In this invention, the server includes means for receiving a system product file, means for analyzing the received file, means for generating a specification document based on the analysis results, means for providing the generated specification document to a user, means for analyzing the factory robot software, means for static analysis for extracting software functions and dependencies, and means for providing the generated specification document in PDF format, thereby enabling a user to easily and quickly analyze the factory robot software and obtain the results as a detailed specification document.

[1118] "System product file" means an electronic file containing software or program code for a factory robot.

[1119] "Analyzing" refers to the process of analyzing the contents and structure of a file in detail using analytical tools.

[1120] A "specification document" is a document created based on the analysis results that describes the functions and dependencies of the factory robot software.

[1121] "Providing to users" refers to the process of providing the generated specification document to users in a form that is easily accessible to them.

[1122] "Factory robot" is a general term for robots used in automated factories.

[1123] A "software function" is a set of operations or calculations performed by a factory robot's software.

[1124] "Dependencies" refer to the relationships between libraries and modules that are required for software to function.

[1125] "Static analysis" is a technique for analyzing software structure, code functions, dependencies, etc. without running the software.

[1126] "PDF format" is an abbreviation for Portable Document Format, and is a file format for saving and displaying specification documents in a visually easy-to-read format.

[1127] The present invention provides a system that allows a user to upload a software file for a factory robot, analyzes the file on a server, and automatically generates a detailed specification document. Specific embodiments are described below.

[1128] System Program

[1129] The program of this system consists of the following major components:

[1130] 1. File upload interface

[1131] An interface for users to upload factory robot software files, which can be provided as a smartphone application or web application.

[1132] 2. Initial Analysis Module

[1133] The server receives the uploaded file and analyzes the file type and structure.

[1134] 3. Decompilation Module

[1135] It decompiles the received files, converting the binary code into high-level source code.

[1136] 4. Static Analysis Module

[1137] It analyzes decompiled source code and extracts software functions and dependencies.

[1138] 5. Document Generation Module

[1139] Based on the analysis results, a detailed specification document is automatically generated in PDF format.

[1140] 6. Result Delivery Module

[1141] Provide the generated specification document to the user and send a download link.

[1142] Natural language explanations

[1143] First, a user uses a smartphone or computer to upload the factory robot's software file to the server via a dedicated interface. The server first stores the received file in temporary storage. Next, the initial analysis module analyzes the file type and structure. For example, if a file named "RobotControlV2.0.exe" is received, it will identify it as an executable file. This analysis uses metadata and file header information.

[1144] Next, the decompilation module uses a decompiler tool to convert the file into high-level source code, for example, C++ source code, and the static analysis module analyzes the source code for functions and dependencies, extracting functions and libraries such as "function1" and "lib1."

[1145] Based on these analysis results, the document generation module automatically generates a specification document in PDF format. Finally, the generated specification document is provided to the user as a download link via the result provision module.

[1146] Specific examples

[1147] For example, if a factory production manager needs to analyze the software for a factory robot called "RobotControlV2.0.exe" and find out the detailed specifications of the libraries and internal modules it uses, he or she might enter the following prompt into the system:

[1148] Analyze the factory robot software "RobotControlV2.0.exe" and generate a detailed specification document of the libraries and internal modules it uses. The following file was uploaded from a smartphone.

[1149] This invention enables users to efficiently and accurately analyze factory robot software and obtain detailed specification documents without requiring specialized knowledge, significantly improving factory production and maintenance efficiency.

[1150] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1151] Step 1:

[1152] The user uploads the factory robot's software file to the server through a dedicated interface. As input, the user selects the executable file "RobotControlV2.0.exe" on their smartphone or computer and presses the upload button. This action sends the file to the server. As output, the file is accurately saved in temporary storage on the server side.

[1153] Step 2:

[1154] The server passes the received file to the initial analysis module, which analyzes the file type and structure. As input, the uploaded "RobotControlV2.0.exe" file is provided. The server reads the file header and metadata and identifies it as an executable file. As output, the file type and basic structure information are obtained.

[1155] Step 3:

[1156] The server uses a decompilation module to convert the parsed files into high-level source code. As input, it is provided with the binary code of the executable file "RobotControlV2.0.exe". The server runs the decompiler tool and converts the binary code into "C++" source code. As output, it gets the decompiled high-level source code.

[1157] Step 4:

[1158] The server uses a static analysis module to analyze the decompiled source code and extract software functions and dependencies. As input, the decompiled source code is provided. The server runs a static code analysis tool to extract function definitions (e.g., "function1", "function2") and dependent libraries (e.g., "lib1", "lib2"). As output, the functionality and dependency information of the source code is obtained.

[1159] Step 5:

[1160] The server uses a document generation module to automatically generate a specification document in PDF format based on the analysis results. The analysis results of the software's functions and dependencies are provided as input. The server uses a PDF generation library (e.g., ReportLab) to generate a PDF document containing the software's detailed specifications. The output is a specification document in PDF format.

[1161] Step 6:

[1162] The server provides the generated specification document to the user through the result delivery module and sends a download link. The generated PDF document is provided as input. The server generates a secure download link and displays it on the user's interface or sends it by email. The user can then download the specification document by clicking the provided download link. As output, the user gets a specification document that details the analysis results.

[1163] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1164] This invention relates to a system that automatically analyzes a system product and generates specification documents when the specifications are unknown. Furthermore, by combining it with an emotion engine that recognizes the user's emotions, it aims to improve the user experience. This system automates the entire process from receiving files to analyzing them, generating documents, and providing them to the user, enabling flexible responses according to the user's emotional state.

[1165] A specific embodiment for implementing the system will be described below.

[1166] Initial file upload and analysis

[1167] A user selects a system product file from their device and uploads it to the server through a dedicated website or application. For example, a user selects a file called "Software A.exe" and sends it to the server. In this step, it is important that the file is sent correctly to the server.

[1168] The server stores the file received from the user in temporary storage and performs an initial analysis to determine the file type and structure. For example, it identifies that the received file "Software A.exe" is an executable file and its physical structural characteristics. At this stage, the file's metadata and header information are analyzed.

[1169] Decompilation and Static Analysis

[1170] The server then selects an appropriate decompiler to decompile the received file. The decompilation process converts binary code or intermediate code into high-level source code. For example, the server converts the binary code extracted from "Software A.exe" into C++ source code, revealing the code's logic and internal structure.

[1171] The server then uses static analysis tools to analyze the decompiled source code. This analysis clarifies the function call relationships and inter-module dependencies in the source code. If necessary, dynamic analysis is also performed to observe runtime behavior, thereby obtaining operational characteristics that cannot be determined by static analysis alone.

[1172] The role of the emotional engine

[1173] The emotion engine recognizes the user's emotional state and adjusts the system's behavior and user interface based on the results. For example, if a user is feeling irritated or dissatisfied while using the system, the emotion engine will detect this and improve the user experience by increasing the system's response speed and simplifying operation procedures.

[1174] The emotion engine analyzes the user's facial expressions and tone of voice through sensors such as cameras and microphones to evaluate their emotional state in real time, allowing the system to reflect the user's current emotional state.

[1175] Generate and provide specification documents

[1176] Based on the analysis results, the server automatically generates a specification document, which contains detailed information such as the system overview, module configuration, function roles, and library dependencies. For example, the generated document might explain what libraries "Software A" uses and how each module works together.

[1177] Finally, the server provides the generated specification document to the user. Specifically, it provides the user with a download link that the user can click to download the document. This download link is designed to be provided to the user safely and easily.

[1178] By going through the above process, users can obtain detailed specification documents of the original system product, which can be used for its operation and maintenance.Furthermore, the introduction of an emotion engine enables flexible responses according to the user's emotional state, improving the overall user experience.

[1179] The processing flow will be explained below.

[1180] Step 1: Select the file

[1181] The user selects the file of the system product to be reverse engineered from his / her own terminal. For example, the user selects "Software A.exe".

[1182] Step 2: Uploading files

[1183] The user clicks the "Upload" button on a dedicated website or application to upload the selected file to the server, and the device sends the selected file to the server.

[1184] Step 3: Receive the file

[1185] The server receives the file sent from the device and stores it in temporary storage. The server then verifies that the file was received correctly.

[1186] Step 4: Initial analysis

[1187] The server performs an initial analysis of the received file to identify its type and structure. It checks the metadata and header information to determine whether the file is executable or library format. For example, it determines that "Software A.exe" is an executable file.

[1188] Step 5: Decompile

[1189] The server selects the appropriate decompiler based on the file format. The decompiler is used to convert the binary code into high-level source code. For example, from "Software A.exe", it generates C++ source code.

[1190] Step 6: Static Analysis

[1191] The server analyzes the decompiled source code using static analysis tools to identify the code structure, function call relationships, and module dependencies, thereby revealing the internal structure and interrelationships of the source code.

[1192] Step 7: Dynamic analysis (if necessary)

[1193] The server emulates the execution environment of the software based on a specific scenario or use case, and uses debugging and monitoring tools to observe its behavior during runtime, thereby obtaining runtime characteristics that cannot be obtained through static analysis.

[1194] Step 8: Emotion Recognition with the Emotion Engine

[1195] The server uses an emotion engine to analyze the user's facial expressions and voice from sensors such as cameras and microphones installed on the user's device, and recognizes the user's emotional state in real time, for example, identifying whether the user is feeling anxious or irritated.

[1196] Step 9: Adjust your system to your emotions

[1197] The server dynamically adjusts the system's behavior and user interface based on the analysis results of the emotion engine. For example, if the user is frustrated, the server can speed up the system's response or simplify the operation procedure, thus improving the user experience.

[1198] Step 10: Generate the specification document

[1199] The server automatically generates a system specification document based on the results of static and dynamic analysis. The document contains details such as an overview of the system, module configuration, function roles, and library dependencies. For example, the generated document might explain which libraries "Software A" uses and how each module works together.

[1200] Step 11: Saving the Document

[1201] The server stores the generated specification document in a storage and makes it accessible to users.

[1202] Step 12: Generate a download link

[1203] The server generates a download link to the saved specification document and provides it to the user, who can then download the document via this link.

[1204] Step 13: Retrieving Documents

[1205] The user clicks the download link provided by the server to download the generated specification document to their device, allowing them to use detailed system information obtained as a result of the analysis.

[1206] Example 2

[1207] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1208] Conventional system analysis methods require a great deal of time and effort to understand the detailed specifications of a system product, and analyzing the product is particularly difficult when specifications are not available. Furthermore, there is no mechanism to reduce the emotional stress that accompanies user operations, which can lead to a poor user experience.

[1209] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1210] In this invention, the server includes means for receiving a system product file, means for temporarily storing the received file and initially analyzing its type and structure, means for decompiling the initially analyzed file, means for statically and dynamically analyzing the decompiled source code, means for detecting the user's emotional state, means for generating a specification document based on the analysis results and the user's emotional state, and means for providing the generated specification document to the user. This makes it possible to automatically obtain detailed specifications of the system product and flexibly respond to user emotions.

[1211] "System product" refers to a comprehensive product that is composed of various software and hardware and provides functions for a specific purpose.

[1212] "File" refers to a collection of digital data that records components of a system product.

[1213] "Temporary storage" refers to the practice of temporarily storing data for access or processing.

[1214] "Initial Analysis" refers to the process of initial data analysis to determine file type and structure.

[1215] "Decompilation" refers to the process of converting binary code or intermediate form code into high-level source code.

[1216] "Static analysis" refers to a technique for evaluating program behavior by analyzing the syntax and structure of the source code without executing it.

[1217] "Dynamic analysis" refers to a method of observing and analyzing the operating characteristics of software while it is running.

[1218] "Emotional state" refers to an emotional response that reflects a user's current state of mind or psychology.

[1219] A "specification document" refers to a document that describes the detailed specifications, structure, and operating characteristics of a system product.

[1220] "Providing" refers to the act of providing generated information or services to users in an accessible form.

[1221] This invention relates to a system that automatically analyzes a system product and generates specification documents when the specifications are unknown. Furthermore, by combining it with an emotion engine that recognizes the user's emotions, it aims to improve the user experience. This system automates the entire process from receiving files to analyzing them, generating documents, and providing them to the user, enabling flexible responses according to the user's emotional state.

[1222] Hardware and Software Use

[1223] To implement the system, the following hardware and software must be used:

[1224] Server: A server equipped with a high-performance processor and a large amount of memory is used. The server stores files, performs analysis, generates documents, and processes the emotion engine.

[1225] Terminal: A computer or mobile device used by a user to upload files or download generated documents.

[1226] Website or application: Used as an interface for users to upload files.

[1227] Decompiler: For example, using IDA Pro or Decompiler, converting binary code into high-level source code.

[1228] Static analysis tools: For example, SonarQube or CppDepend are used to analyze the source code.

[1229] Emotion engine: Software that uses a camera and microphone to analyze a user's facial expressions and tone of voice to assess their emotional state.

[1230] Process example

[1231] 1. File Upload

[1232] The user selects the system product file they want to analyze from their device and uploads it to the server via a dedicated website or application. For example, the user selects the file "Software A.exe" and clicks the upload button. At this time, the device sends the file to the server.

[1233] 2. Initial analysis

[1234] The server stores the uploaded file in temporary storage and performs an initial analysis to determine its type and structure. Specifically, the server analyzes the metadata and header information of the received "Software A.exe" file to confirm that it is an executable file. At this stage, the server also obtains the file's size, creation date and time, hash value, etc.

[1235] 3. Decompilation

[1236] The server selects an appropriate decompiler and decompiles the received file. Specifically, it converts the binary code of "Software A.exe" into high-level source code (e.g., C++) using a decompilation tool (e.g., IDA Pro or Decompiler). The server performs this process asynchronously and stores the results in temporary storage.

[1237] 4. Static and Dynamic Analysis

[1238] The server analyzes the decompiled source code using a static analysis tool (such as SonarQube or CppDepend). Specifically, it identifies function call relationships and inter-module dependencies. It also performs dynamic analysis as needed, running the program in a simulator or sandbox environment to closely observe its operating characteristics. This allows it to understand things like memory usage, CPU load, and network communication patterns during runtime.

[1239] 5. Operation of the Emotion Engine

[1240] The server runs an emotion engine to detect user emotions in real time. When a user operates the system, facial expressions and voice are captured through the device's camera and microphone. Specifically, the server analyzes the camera images and identifies the user's emotional state using a facial expression recognition algorithm (e.g., OpenFace or Microsoft Face API). Voice data is also analyzed to evaluate emotions based on the tone and content of the voice.

[1241] 6. Generating and Providing Specification Documents

[1242] The server automatically generates a specification document based on the analysis results. Specifically, it integrates the results of the analysis tools and creates a document that includes a system overview, module configuration, function roles, library dependencies, etc. This document is generated in formats such as Markdown, PDF, and HTML, making it easy for users to access.

[1243] Finally, the server provides the generated specification document to the user. Specifically, it generates a download link for the document and notifies the user. The user can click this link to download the document to their device. The download link is provided via a secure protocol (e.g., HTTPS) to ensure safe and fast access.

[1244] Prompt Sentence Examples

[1245] How can the system automatically analyze unknown product files and generate detailed specification documents? Please also provide details on the specific steps from file upload to document submission, the tools used, and the analysis process.

[1246]

[1247] How can an emotion engine be used to improve the user experience? Give an example of how you can detect and respond to frustrations that users may experience while interacting with a system.

[1248] Through the above process, users can easily obtain detailed specification documents, and the emotion engine can improve the user experience.

[1249] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1250] Step 1: File Upload

[1251] The user selects the system product file to be analyzed from their own device and uploads it to the server via a dedicated website or application.

[1252] Input: System product file (e.g. Software A.exe)

[1253] Specific operation: The user clicks the upload button and the device sends the file to the server.

[1254] Output: The file uploaded to the server.

[1255] Step 2: Initial analysis of the file

[1256] The server temporarily stores the received files and performs an initial analysis to determine their type and structure.

[1257] Input: A file uploaded to the server

[1258] What happens: The server parses the metadata and header information to determine the file type (e.g., executable).

[1259] Output: File type, metadata (e.g. size, creation date, hash value)

[1260] Step 3: Decompile

[1261] The server selects the appropriate decompiler and performs the decompilation of the file.

[1262] Input: The initial parsed file and its metadata

[1263] Specific operation: The server uses a decompilation tool (e.g., IDA Pro, Decompiler) to convert the binary code into high-level source code (e.g., C++).

[1264] Output: Decompiled source code

[1265] Step 4: Static and Dynamic Analysis

[1266] The server analyzes the decompiled source code using static and dynamic analysis tools.

[1267] Input: Decompiled source code

[1268] Specific operation: The server identifies function call relationships and module dependencies using static analysis tools (e.g., SonarQube, CppDepend), and if necessary, uses dynamic analysis tools to examine runtime behavior.

[1269] Output: Analysis results (e.g., function call graph, module dependencies, behavioral characteristics)

[1270] Step 5: Detecting user emotions with the emotion engine

[1271] The server detects user emotions in real time.

[1272] Input: Camera image and audio data from the user device

[1273] How it works: The server analyzes camera images and uses facial expression recognition algorithms (e.g., OpenFace, Microsoft Face API) to identify emotional states. It also analyzes audio data and assesses emotions based on tone and content.

[1274] Output: User's emotional state (e.g., annoyed, frustrated, satisfied)

[1275] Step 6: Generate the specification document

[1276] The server generates a specification document based on the analysis results and the user's emotional state.

[1277] Input: Analysis results and user's emotional state

[1278] What it does: The server integrates the results of the analysis tools and creates a document that includes an overview of the system, module structure, function roles, library dependencies, etc.

[1279] Output: Generated specification document (e.g. Markdown, PDF, HTML)

[1280] Step 7: Provide documentation

[1281] The server provides the generated specification document to the user.

[1282] Input: Generated specification document

[1283] Specific operation: The server generates a download link for the document and notifies the user. The user clicks on this link to download the document to their device.

[1284] Output: User downloaded specification document

[1285] (Application example 2)

[1286] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1287] Currently, when the specifications of a system product are unknown, analyzing them and generating specification documents is extremely time-consuming, and the process can be frustrating for users. Furthermore, there is a lack of a way to detect in real time the stress or frustration felt by on-site workers regarding system operation or interfaces, and provide optimal feedback accordingly. This leads to issues such as reduced work efficiency and a worsening user experience.

[1288] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1289] In this invention, the server includes means for receiving a system product file, means for analyzing the received file, means for generating a specification document based on the analysis results, and means for recognizing the user's emotional state and adjusting the system operation and user interface. This not only automates the generation of the specification document, but also makes it possible to provide real-time feedback according to the user's emotions.

[1290] "System product files" are executable files and configuration files necessary for the operation of a particular system, such as software or control programs.

[1291] "Analysis" is the process of interpreting the contents of a file or program to understand its structure and behavior.

[1292] A "specification document" is a document that describes in detail the behavior, functions, design, dependencies, etc. of a system or software.

[1293] "User" means the ultimate user who operates or utilizes the system.

[1294] "Means for receiving" refers to the function or method for receiving system product files from users.

[1295] "Means of analysis" refers to a method for interpreting the received file and clarifying its internal structure and operation.

[1296] "Means for generating" refers to a method for automatically creating a specification document based on the analysis results.

[1297] The "means for providing" is a method or function for presenting the generated specification document to the user.

[1298] An "emotional state" is a psychological state that indicates a user's current mood or feelings.

[1299] "Means for recognizing and adjusting emotional states" refers to a method or function that uses sensors such as cameras and microphones to detect a user's emotions in real time and changes the system's behavior or interface based on the results.

[1300] "Decompilation" is the process of converting binary or intermediate form code into high-level source code.

[1301] "Static analysis" is the process of analyzing a program's source code and structure without executing it.

[1302] The present invention is a system that automatically analyzes files of a system product, generates specification documents, and further includes a function for recognizing user emotions and adjusting the operation of the system. Specific embodiments of the present invention will be described below.

[1303] File upload and initial analysis

[1304] Users upload system product files to the server using a dedicated website or application. The uploaded file is stored in temporary storage, where its metadata and structure are initially analyzed. For example, if a file such as "control program.exe" is uploaded, it is identified as an executable file and its physical characteristics are identified.

[1305] Decompilation and Static Analysis

[1306] The server uses a decompiler to decompile the received file. The decompiled code is converted into a high-level language and then analyzed using a static analysis tool. Static analysis reveals the function call relationships and inter-module dependencies. For example, "control program.exe" is converted into C++ source code, and the function connections are analyzed from that code.

[1307] Generate specification documents

[1308] Based on the results of decompilation and static analysis, the server automatically generates a specification document that details the system overview, module structure, function roles, library dependencies, etc. The generated specification document is provided to the user via a download link.

[1309] Emotion recognition and system behavior adjustment

[1310] The emotion engine uses sensors such as cameras and microphones to recognize the user's emotional state in real time. For example, it can analyze a worker's facial expressions and tone of voice to detect irritation or fatigue. Based on the detected emotional state, the server adjusts the system's behavior and interface. If the worker is irritated, the robot's movement speed can be slowed down, improving safety and work efficiency.

[1311] Hardware and software used

[1312] 1. Hardware

[1313] Camera (e.g. Logitech C920): Used to capture the facial expressions of the workers.

[1314] Microphone (e.g. Blue Yeti): Used to capture the worker's tone of voice.

[1315] 2. Software

[1316] dlib library: Used for face detection and landmark extraction.

[1317] EmotionRecognition library: Used to analyze and determine emotions from facial expressions.

[1318] Decompiler library: Decompiles robot control systems and programs.

[1319] Specific examples

[1320] In factories, when workers interact with robotic control systems, the system analyzes their emotions in real time, for example, if it detects that a worker is feeling frustrated, it can adjust the robot's movement speed to improve work safety and the experience.

[1321] Prompt Sentence Examples

[1322] "Write a program to run an application that analyzes the robot control system in a factory and generates specification documents. We will also use a camera and microphone to capture the emotions of workers. Write a program to adjust the robot's behavior according to the worker's emotional state."

[1323] In this way, a system can be constructed that simultaneously generates specification documents and optimizes the user experience.

[1324] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1325] Step 1:

[1326] A user uploads a system product file to the server using a dedicated website or application. The input is the system product file, and the output is that the file is transferred to the server and stored in temporary storage. The server then confirms that the file has been sent.

[1327] Step 2:

[1328] The server performs pre-processing to analyze the uploaded file. Here, it obtains the file's metadata and header information and identifies the file type and structure. The input is the uploaded file, and the output is information about the file type and structure. The server uses this information to prepare for the next decompilation process.

[1329] Step 3:

[1330] The server selects an appropriate decompiler and decompiles the file. The input for decompilation is the file type and structure information obtained in the previous step, along with the actual file itself. The output is high-level source code. For example, binary code is converted into C++ source code. The server saves the converted source code and prepares it for static analysis.

[1331] Step 4:

[1332] The server analyzes the decompiled source code using a static analysis tool. The input is the decompiled source code, and the output is the analysis results, such as function call relationships and inter-module dependencies. The server obtains these analysis results and uses them to generate a specification document.

[1333] Step 5:

[1334] The server automatically generates a specification document based on the analysis results. The input is the static analysis results, and the output is a specification document that describes the system overview, module configuration, function roles, library dependencies, etc. The server generates a link so that the user can download this specification document.

[1335] Step 6:

[1336] The user clicks on the provided link to download the generated specification document. The input is the download link for the specification document, and the output is the specification document downloaded to the local machine. The server verifies that the document was downloaded correctly.

[1337] Step 7:

[1338] The server activates an emotion engine and recognizes the user's emotional state in real time. The input is the user's facial expression and tone of voice captured by a camera or microphone, and the output is the user's emotional state. The server analyzes this data and determines the user's emotional state.

[1339] Step 8:

[1340] The server adjusts the system's behavior and interface based on the user's emotional state. The input is the user's emotional state output from the emotion engine, and the output is the adjusted system behavior and interface. For example, if the user is irritated, the server will adjust the robot's movement speed to slow down. The entire system is adjusted to perform optimally according to the user's emotional state.

[1341] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1342] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1343] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1344] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1345] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1346] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1347] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1348] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1349] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1350] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1351] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1352] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1353] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1354] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[1355] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1356] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1357] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1358] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1359] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1360] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1361] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1362] The following is further disclosed regarding the above embodiment.

[1363] (Claim 1)

[1364] a means for receiving system product files;

[1365] a means for analyzing the received file;

[1366] means for generating a specification document based on the analysis results;

[1367] a means for providing the generated specification document to a user;

[1368] A system including:

[1369] (Claim 2)

[1370] means for decompiling the received file;

[1371] 10. The system of claim 1.

[1372] (Claim 3)

[1373] having means for performing static analysis of the system based on the analysis results;

[1374] 10. The system of claim 1.

[1375] "Example 1"

[1376] (Claim 1)

[1377] a means for receiving uploaded system product files;

[1378] means for initially parsing metadata and header information for received files;

[1379] means for decompiling the file based on the analysis results;

[1380] A means for statically analyzing the decompiled code;

[1381] means for performing dynamic analysis based on the static analysis results;

[1382] a means for integrating the dynamic analysis results to generate a specification document;

[1383] a means for providing the generated specification document to a user;

[1384] A system including:

[1385] (Claim 2)

[1386] 10. The system of claim 1, further comprising means for decompiling the received file.

[1387] (Claim 3)

[1388] 10. The system of claim 1, further comprising means for performing static and dynamic analysis of the system based on the analysis results.

[1389] "Application Example 1"

[1390] (Claim 1)

[1391] a means for receiving system product files;

[1392] a means for analyzing the received file;

[1393] means for generating a specification document based on the analysis results;

[1394] a means for providing the generated specification document to a user;

[1395] A means of analyzing the software of factory robots;

[1396] Static analysis methods to extract software functions and dependencies,

[1397] A means of providing the generated specification document in PDF format;

[1398] A system including:

[1399] (Claim 2)

[1400] means for decompiling the received file;

[1401] 10. The system of claim 1.

[1402] (Claim 3)

[1403] having means for performing static analysis of the system based on the analysis results;

[1404] 10. The system of claim 1.

[1405] "Example 2: Combining Emotion Engines"

[1406] (Claim 1)

[1407] a means for receiving system product files;

[1408] A means to temporarily store received files and perform initial analysis of their type and structure,

[1409] means for decompiling the initially parsed file;

[1410] means for statically and dynamically analyzing the decompiled source code;

[1411] means for detecting an emotional state of a user;

[1412] means for generating a specification document based on the analysis results and the emotional state of the user;

[1413] a means for providing the generated specification document to a user;

[1414] A system including:

[1415] (Claim 2)

[1416] 10. The system of claim 1, further comprising means for analyzing received files and their metadata to determine the type and structure of the files.

[1417] (Claim 3)

[1418] 10. The system of claim 1, further comprising means for detecting the user's emotional state via a camera or microphone and adjusting the system's operation in response to the emotion.

[1419] "Application example 2 when combining emotion engines"

[1420] (Claim 1)

[1421] a means for receiving system product files;

[1422] a means for analyzing the received file;

[1423] means for generating a specification document based on the analysis results;

[1424] a means for providing the generated specification document to a user;

[1425] a means for recognizing a user's emotional state and adjusting the system's behavior and user interface;

[1426] A system including:

[1427] (Claim 2)

[1428] means for decompiling the received file;

[1429] 10. The system of claim 1.

[1430] (Claim 3)

[1431] having means for performing static analysis of the system based on the analysis results;

[1432] 10. The system of claim 1. [Explanation of symbols]

[1433] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. a means for receiving system product files; a means for analyzing the received file; means for generating a specification document based on the analysis results; a means for providing the generated specification document to a user; A system including:

2. means for decompiling the received file; The system of claim 1 .

3. having means for performing static analysis of the system based on the analysis results; The system of claim 1 .

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