77 results about "Software analytics" patented technology

The invention relates to the technical field of computer systems, in particular to a computer software analysis system, which comprises a dependency construction module, which is used for extracting key fields and checking function interface association when source code records are compared on the basis of debugging breakpoints and program component information, reviewing version differences and identifying conflict references, and establishing a database; invalid calls are screened through error mark comparison, a function call chain and a version label are integrated, a code snippet reference index is constructed, and a dependency path index is generated. According to the method and the device, when source code records are compared, key field extraction and function interface checking are introduced, version differences are examined, conflict references are identified, and invalid calls are screened, so that the software analysis process is more accurate, and the accuracy of fault diagnosis is improved. In the function calling process, the number of times of cross calling is counted, repeated path sources are checked, interleaved annular calling can be rapidly positioned, the deviation position of an error segment is defined, and repeated influences of cyclic calling on software performance are avoided.

According to the safety coprocessor hybrid encryption method based on the SM2 / 3 / 4 domestic cryptographic algorithm, a novel hybrid encryption system based on the SM2 / 3 / 4 and considering encryption safety, efficiency and key management convenience is constructed on the basis of the characteristics of the SM2 algorithm, the SM3 algorithm and the SM4 algorithm, and the encryption / decryption and signature / verification process is achieved. And aiming at the efficiency problem of a domestic SM algorithm, an encryption / decryption and signature / verification scheme is designed and realized through pure software analysis and software and hardware (SW / HW) collaboration, so that optimal division of software and hardware is realized, and the algorithm efficiency is greatly improved.

The invention discloses a simulation analysis method and system based on an electromagnetic compatibility test, and relates to the field of electromagnetic compatibility testing, and the method comprises the steps: building a hardware three-dimensional simulation model for a hardware environment with electromagnetic compatibility to be tested, and obtaining hardware environment data; establishing a multi-device heat balance model, and dynamically adjusting temperature values and distances between the plurality of components and between the component groups; based on FDTD and MoM algorithms, the electromagnetic compatibility of the hardware environment data is analyzed; establishing an electromagnetic compatibility dynamic adjustment model, and dynamically optimizing the stability of to-be-tested electromagnetic compatibility hardware configuration and software analysis; and optimizing and adjusting the electromagnetic compatibility dynamic adjustment model in combination with actual design feedback. The method has the advantages that through multi-physics field coupling simulation and dynamic feedback optimization, collaborative design of hardware layout, heat balance and electromagnetic compatibility is achieved, the compliance rate of an electromagnetic compatibility test is remarkably improved, and the research and development cost is reduced.

Embodiments facilitate software analysis by machine learning (ML) models, through extensible software analysis architecture (ESAA) or software analysis work allocation (SAWA). Pluggable ESAA ML modules include a vetted prompt which is actionable for software analysis, with a vetting certification. Some ML modules contain computational cost information such as a token count or model round trip time. Tools are tailored to ML analyzers to control background execution, availability offerings, and results displays. SAWA determines how well a software analyzer meets a prompt's software analysis requirements, and an ML planning model generates an analysis plan that balances software analysis workloads among ML analyzers and non-ML analyzers. ML analyzers are favored for summarization, task decomposition, task scheduling, and source code change review, while non-ML analyzers are otherwise favored. Non-ML analyzers gather control flow, data flow, internal structure, and similar context which is then supplied to an ML analyzer.

A computer-implemented system analyzes program and data flows in a software system comprising code written in multiple programming languages using a generative large language model (LLM) directed by programming-language-specific prompts. The LLM identifies functional components within the code, generating labeled graph nodes that include a node type, a node name, and dependency information. A graph construction computer system processes the labeled graph nodes to generate a directed graph, where nodes represent functional components and directed edges represent dependencies. The system stores the graph in a database and provides a web-based interface for visualization, allowing users to explore, query, and analyze program and data flows across the software system. The system enables automated, language-agnostic dependency mapping, facilitating software analysis, debugging, and modernization.

The invention discloses an open source component analysis method based on a static program, and relates to the technical field of software analysis. Project source codes are input and analyzed, a semantic calling graph is obtained, and hierarchical management is conducted on the semantic calling graph; carrying out topological sorting on the layered semantic calling atlas to obtain a component check sequence; and comparing the semantic call maps corresponding to the new version and the old version of the to-be-upgraded component, performing software detection operation on the to-be-upgraded component, and outputting a conflict report. According to the method, a layered semantic calling graph is constructed and contains rich context information, so that analysis can go deep into the level of whether behaviors and semantics of the method are changed or not, topological sorting is carried out on component dependency relationships, a component checking sequence is provided, the problem that a conflict is repaired in reality is solved, and the method is more practical. By means of the method, it is guaranteed that before any component is checked, all the components on which the component depends are analyzed and confirmed, and orderliness and certainty of the analysis process are guaranteed.

This software analysis device comprises: a first calculation unit configured to calculate, for each of one or more first character strings representing, in a natural language, the content of a change performed on a source code of software, the degree of association with a second character string representing, in a natural language, the content of a change to be performed on the software; a second calculation unit configured to calculate, for each location of the source code having been changed in relation to the content of the change represented by the first character string, the total sum of the degrees of association related to all of the first character strings corresponding to the location; and an output unit configured to output information indicating the location in a mode corresponding to the total sum, thereby enabling acquisition of a portion related to a character string expressed in a natural language from a source code.

An object of the invention is to quickly specify a version of software that causes a defect even when update histories of a plurality of pieces of software are managed separately. In a software analysis system according to the invention, when a performance degradation of second software is detected by a performance test, a version updated by merging first software is specified or a version where reference information of the first software is changed from that before is specified among past versions of the second software, thereby specifying a candidate in the first software which is a cause of the degradation (see FIG. 4B).

The invention relates to the technical field of maintenance planning, and particularly discloses a landscape greening maintenance planning method and system based on big data, and the method comprises the steps: constructing a maintenance region model, and updating the maintenance region model based on a shot image; rasterizing the maintenance area model, and determining greening parameters in each grid area; and clustering the grid areas based on the greening parameters, synchronously determining the demand precision of each type of grid areas, obtaining the real-time information of each grid area, feeding back the real-time information to the management end, and receiving a maintenance scheme which is fed back by the management end and contains a maintenance target. According to the method, the landscape model is constructed based on the BIM model, the landscape model is updated based on a large amount of image data, the real-time performance of the landscape model is extremely high, software analysis is performed on the landscape model, a maintenance target can be determined, a more targeted maintenance task can be generated, and the labor workload is greatly reduced under the condition that the maintenance effect is almost unchanged.

The invention provides an abnormal log analysis method and device, and relates to the technical field of software analys.The method comprises the steps that an Android device log information set is obtained, the log information set comprises multiple pieces of original log information, format standardization processing is conducted on each piece of original log information, and the original log information is obtained; obtaining a first log set comprising a plurality of pieces of log information with uniform formats; a second log set is obtained through screening according to the first log set, the second log set does not comprise redundant log information in the first log set, and the second log set comprises missing fields of the log information in the first log set; classifying multiple pieces of log information in the second log set to obtain a third log set; sorting each piece of log information in the third log set according to the time sequence and the category label to generate a plurality of log information sequences; and sending the plurality of log information sequences to a local server, and obtaining an abnormal log report and a repair suggestion corresponding to the abnormal log report according to the plurality of log information sequences.

A computer-implemented system analyzes program and data flows in a software system comprising code written in multiple programming languages using a generative large language model (LLM) directed by programming-language-specific prompts. The LLM identifies functional components within the code, generating labeled graph nodes that include a node type, a node name, and dependency information. A graph construction computer system processes the labeled graph nodes to generate a directed graph, where nodes represent functional components and directed edges represent dependencies. The system stores the graph in a database and provides a web-based interface for visualization, allowing users to explore, query, and analyze program and data flows across the software system. The system enables automated, language-agnostic dependency mapping, facilitating software analysis, debugging, and modernization.

The invention discloses a malicious software analysis and identification method and device. The method comprises the steps of performing data extraction on a to-be-detected code running in a sandbox, and determining an application program editing interface calling sequence; performing feature processing on the application program editing interface calling sequence through a pre-constructed multi-head attention map network, and determining a feature extraction map; performing feature extraction on the application program editing interface calling sequence through a preset multi-dimensional word embedding method, and determining a target semantic chain embedding vector; and malicious code identification is carried out according to the feature extraction graph and the target semantic chain embedding vector through a pre-constructed identification network, and a target identification result is determined. According to the method, the common features of the malicious behaviors can be captured by fusing the features of different levels, and accurate classification and detection of the malicious software behaviors are realized, so that the robustness and accuracy of malicious software detection are improved.

To quickly specify a version of software causing failure even when update histories of a plurality of pieces of software are individually managed.SOLUTION: In response to detecting degradation in performance of second software by a performance test, a software analysis system relating to the present invention specifies a candidate for first software causing the degradation by specifying a past version updated by merging the first software out of past versions of the second software or specifying reference information changed from the original, of the first software.SELECTED DRAWING: Figure 4B

[Problem] The objective is to realize a technical due diligence support method that makes it easier to understand the results of software analysis. [Solution] A due diligence support method for evaluating the technical capabilities and software quality of a prospective acquisition company of a business operator, which is performed by a management terminal according to one embodiment of the present invention, wherein the control unit of the management terminal refers to information on the source code disclosed by the developer of the prospective acquisition company, performs an analysis to evaluate the technical capabilities and quality based on the information on the source code, and generates a report evaluating the technical capabilities and quality based on the analysis results. [Selected Figure] Figure 8

The application relates to the technical field of maintenance planning, and particularly discloses a landscape greening maintenance planning method and system based on big data, which comprises the following steps: constructing a maintenance area model, updating the maintenance area model based on a photographed image; performing rasterization processing on the maintenance area model to determine greening parameters in each grid area; clustering the grid areas based on the greening parameters, synchronously determining the demand accuracy of each type of grid area, obtaining real-time information of each grid area, feeding back the real-time information to a management end, and receiving a maintenance scheme containing a maintenance target fed back by the management end. The application constructs a landscape model based on a BIM model, updates the landscape model based on a large amount of image data, the real-time performance of the landscape model is extremely high, software analysis is performed on the landscape model, the maintenance target can be determined, more targeted maintenance tasks can be generated, and the manpower workload is greatly reduced while the maintenance effect is almost unchanged.

The application belongs to the technical field of software analysis, and provides a function point extraction processing method and system. The method obtains data sets by collecting requirement analysis texts, software design texts and system design texts available through public channels, and performs function point labeling to establish a knowledge base. According to the established knowledge base, the KMP algorithm is used to perform string matching between the function points in the knowledge base and the texts to be processed, so as to extract the function points contained in the texts to be processed and determine the category labels of the function points. The texts to be processed are input into a pre-constructed automatic extraction model, and the function points contained in the texts to be processed and the categories to which the function points belong are output. The function points extracted based on the knowledge base and the function points extracted using the automatic extraction model are sorted, evaluated and calculated to screen the function points. The application realizes a faster and more effective automatic extraction process of function points, and effectively avoids the problem of missing function points.

The present invention provides an embedded computer system architecture for implementing software testing, which includes a chassis, functional modules arranged in the chassis, a test interface module, and an acquisition module for acquiring data on the functional modules through the test interface module. A detachable cover plate is provided on the chassis, and the detachable cover plate is used to protect the test interface module; the test interface module includes test interfaces arranged on the detachable cover plate and is connected to the functional modules through the test interfaces; the acquisition module includes a software defect location device, a source code coverage statistical analysis device, and an object code structure coverage statistical analysis device. Without changing the functional performance of the prototype embedded computer product or the original system structure, this architecture increases the coverage rate of full acquisition of the original values of signals and CPU operation state testing by adding a generalized test interface and configurable test modules, and realizes software analysis and testing with high real-time performance, high reliability, multi-dimensions, high generality, and high test coverage rate.

The invention relates to a paleotectonic stress recovery method based on section form measurement, which comprises the following steps of: firstly, carrying out three-dimensional description on a stratum position and a fault in processed geoseismic data by utilizing petrel software in order to strengthen research on regional evolution; the method comprises the following steps: firstly, constructing an outline map, secondly, encrypting an isoline in the constructed outline map, selecting a sliding direction and displacement of a section, measuring a dip direction and a dip angle of the section, and finally, analyzing and forming ancient stress analysis by utilizing Win-sensor software through combining the measured fault dip direction and dip angle.

A system and method for automated software vulnerability detection and patching using sandboxed analysis. The system receives executable machine code files and identifies target device types for execution. A sandbox environment emulates device functionality and executes code while monitoring for suspicious behavior including memory scanning, unauthorized system access, and irregular network activity. Machine learning algorithms analyze execution patterns to detect security vulnerabilities and exploits. Upon identifying threats, the system automatically generates protective patches such as address space layout randomization and data execution prevention measures. These patches are deployed to real devices to prevent exploitation. The system uses reinforcement learning to improve patch effectiveness over time. This automated approach enables proactive cybersecurity protection by responding to emerging threats before malicious exploitation occurs.

The invention provides an upper computer debugging device applied to a standardized centralized terminal and a working method of the upper computer debugging device, and relates to the technical field of distribution network debugging, the upper computer debugging device comprises upper computer software and a testing tool, the upper computer software is arranged in an upper computer, and the upper computer software comprises a man-machine interaction unit and a fault judgment module; the test tool comprises a power supply module, an analog voltage and current module, an indicating lamp module and a remote signaling control module. The test tool is connected with a tested terminal through a wire harness and applies test parameters, and the upper computer is connected with the tested terminal through a network cable; the test tool is connected with the tested terminal through the wire harness, test parameters are applied, the upper computer is connected with the tested terminal through a network cable, messages are received, the upper computer analyzes the messages of the tested terminal through upper computer software, whether the current tested terminal is qualified or not can be judged, a test report is generated, the whole automatic test is achieved, and the test efficiency is improved. Manual operation errors can be greatly reduced, and equipment faults can be quickly positioned.

A method for developing or improving a process for producing a product from a material comprising steps of acquiring process data from at least two different sources for the production process and its relevant parameters by using a Data Collecting computer; using the acquired process data related to the production process to perform a Process Mapping step by using a Process Mapping computer; assigning the acquired process data related to the relevant parameters of the production process to its corresponding process parts by performing a Data Mapping step by using a Data Mapping computer; analyzing the therefore mapped process data with a specific software performed on an Analyzing computer thereby identifying and validating one or more existing characteristics related to the quality or performance of the production process; and using the identified and validated characteristics to develop the production process or improve its performance.

The application discloses a static program open source component analysis method, relates to the technical field of software analysis, and comprises the following steps: inputting project source code, parsing, obtaining a semantic call graph, and performing hierarchical management on the semantic call graph; performing topological sorting on the hierarchical semantic call graph, obtaining a component inspection sequence; comparing the semantic call graphs corresponding to the new and old versions of a to-be-upgraded component, performing a software detection operation on the to-be-upgraded component, and outputting a conflict report. The method constructs a hierarchical semantic call graph, which contains rich context information, so that analysis can be deepened to the level of whether the behavior and semantics of a method change; through topological sorting on component dependency relations, the application proposes a component inspection sequence, which solves the circular dilemma that repairing one conflict causes another conflict in reality, guarantees that the components depended on by any component to be inspected have been analyzed and confirmed before the component is inspected, and ensures the orderliness and certainty of the analysis process.

The invention belongs to the field of hydropower station debugging, discloses a multifunctional hydraulic power plant automation system debugging device and method, and aims at solving the problems that an existing debugging technology is single in function, poor in protocol compatibility, depends on artificial experience and the like. The debugging device comprises a hardware tool layer, a software analysis layer and a data interaction layer, the hardware tool layer integrates a signal test module, an intelligent diagnosis module and a communication adaptation module, the software analysis layer is provided with a multi-end adaptation and data fusion analysis engine, and the data interaction layer guarantees safe transmission of data. The debugging method comprises the steps of system initialization, equipment detection, multi-source data acquisition, data fusion analysis, intelligent diagnosis decision, debugging execution control, report generation and filing and the like. Through adaptive signal matching, digital twinning and debugging combination and integrated learning fault prediction, debugging intelligence and standardization are realized. The method can greatly shorten the debugging time, effectively improves the fault diagnosis accuracy, and guarantees the safe and stable operation of a hydraulic power plant automation system.

The application discloses a high-voltage switch cabinet fault diagnosis system, and relates to the technical field of power equipment monitoring and fault diagnosis.The system is a comprehensive diagnosis system relying on hardware collection and software analysis.The system comprises a fault information collection module, a data preprocessing unit, a multi-dimension feature extraction module, a fusion diagnosis engine and a diagnosis result output module.The application has the following innovative points: for the first time, five types of sensors, i.e.temperature sensors, partial discharge sensors, arc light sensors, electrical parameter sensors and vibration sensors, are integrated;the arc light sensors adopt a triangular redundant monitoring network;the vibration sensors compensate for the blank of mechanical fault monitoring;the system covers all types of faults of a switch cabinet, such as thermal faults, insulation faults, arc faults and mechanical faults, and greatly reduces the false negative rate.

The application discloses a kind of dynamic depth analysis engine construction methods based on genetic evolution algorithm, belong to software analysis technical field, main in solving the problem of low code coverage and malicious behavior trigger rate of existing dynamic analysis technology, main scheme includes step 1: the UI level capture of being tested Android application is carried out to obtain UI component information in the tested Android application, obtain UI level information.Step 2: specified UI event trigger is realized by injecting event function.Step 3: capture software dynamic behavior characteristic data and realize malicious behavior dynamic detection using neural network model.Step 4: event function sequence is generated and screened using genetic evolution algorithm, and the injected event function is changed by feedback regulation.The application finally realizes the dynamic optimization of UI event sequence by combining with feedback regulation while detecting malicious behavior, and realizes the identification of Android malicious software based on dynamic analysis with high trigger rate.

The invention discloses a compiled binary code recognition method based on a graph network. The method comprises the following steps: acquiring a compiled binary code to be identified in a control system, performing decompilation to obtain a decompiled pseudo code and inheritance relationships of various types in the decompiled pseudo code, and constructing a member function table; constructing a software variable relation table based on the relation between the software variables of the classes; based on the software variable relation table, constructing a directed subgraph of the member function; aggregating the directed sub-graphs into a class level general graph according to the calling relationship; and performing variable semantic inference based on the class hierarchy general graph, and identifying the type and semantics of the compiled binary code so as to determine the function of the compiled binary code in the control system. According to the method, the directed subgraph and the class level general graph of the decompilation pseudo-code can be automatically constructed, then variable type semantic inference is carried out based on a graph network structure, the decompilation pseudo-code recognition problem can be systematically solved, and therefore more efficient and accurate technical support is provided for robot reverse engineering and software analysis.

Analytics dashboards for critical event management systems that include artificial-intelligence (AI) functionalities, and related software. AI functionalities disclosed include pattern recognition and predictive modelling. One or more pattern-recognition algorithms can be used, for example, to identified patterns or other groupings within stored critical events, which can then be used to improve response performance and / or to inform the generation of predictive models. One or more predictive-modeling algorithms can be used to generate one or more predictive models that can then be used, for example, to make predictions about newly arriving critical events that can then be used, among other things, to provide optimal response performance and allow users to efficiently and effectively manage responses critical events. These and other features are described in detail.

The invention relates to the technical field of software analysis, in particular to a penetrating log-based software analysis method and system, a terminal and a medium, and the method comprises the following steps: collecting log information of each level in a target application software system; the collected log information is preprocessed; storing the preprocessed log information; and outputting a service calling chain graph based on a calling chain construction algorithm, extracting performance data of each service node from the stored log information when the target application software system runs, and positioning performance bottleneck points in the target application software system based on the service calling chain graph and the performance data by adopting a performance bottleneck positioning algorithm. According to the method, the system performance can be analyzed more comprehensively and meticulously, and hidden performance bottleneck points or potential problems can be found easily.

The present application provides a kind of malware analysis system and method, belong to malware analysis field.The system includes: sample acquisition module, for utilizing multiple acquisition methods to collect malware samples, and the malware samples are stored;Threat intelligence integration module, for utilizing multiple platforms to collect threat intelligence, and the threat intelligence is integrated and stored;Automated analysis module, utilizes automated analysis tool, combines analysis process and automated process, generates the automated analysis result of malware;Result verification module, utilizes selected verification method, combines multiple verification indexes, and the credibility of automated analysis result is checked;And report generation module, generates corresponding defense measures, generates malware analysis report.The present application improves the update speed of threat intelligence and the detection efficiency of new malware, reduces the false alarm rate, improves the determination accuracy, shortens the deployment time of defense measures, and reduces the amount of manual operation.

The application relates to a software analysis method and device, computer equipment, a storage medium and a computer program product. The method comprises the following steps: obtaining request information of software to be analyzed, and sending the request information to a target address; obtaining real response traffic generated by the target address based on the request information, and generating simulation response traffic based on the real traffic; sending the simulation response traffic to the software to be analyzed, and obtaining behavior data generated by the software to be analyzed based on the simulation response traffic. The application solves the problem that malicious software analysis cannot be performed in the case of no Internet environment or loss of effectiveness of the software to be analyzed, and improves the accuracy of malicious software analysis.