383 results about "Functional requirement" patented technology

The invention relates to the technical field of software development management, in particular to an internet software development management system and method. The method comprises the following steps: collecting an original function demand set and carrying out function clustering analysis; extracting and classifying demand function features and generating independent demand units; carrying out dependency analysis on the independent demand units; constructing a dependency relationship set and a demand logic structure; the method comprises the following steps: generating a demand framework matrix, carrying out organization network simulation to obtain a demand connection network, carrying out code reverse evolution according to the demand connection network, carrying out basic parameter matching to obtain evolution basic parameters, carrying out a pressure simulation test on the evolution basic parameters to generate a pressure test result, and capturing resource pressure defects based on the pressure test result. And optimizing and adjusting the evolution basic parameters to generate optimized development parameters. According to the invention, a more efficient Internet software development management method is realized.

An integrated development environment (IDE) for uses a generative artificial intelligence (AI) model to generate industrial control code in accordance with functional requirements provided to the industrial IDE system as natural language prompts. The system's generative AI model leverages both a code repository storing sample control code and a document repository that stores device or software manuals, program instruction manuals, functional specification documents, or other technical documents. These repositories are synchronized by digitizing selected portions of document text from the document repository into control code for storage in the code repository, as well as contextualizing control code from the code repository into text-based documentation for storage in the document repository.

An integrated development environment (IDE) for designing, programming, and configuring aspects of an industrial automation system uses a generative artificial intelligence (AI) model and associated neural networks to generate portions of an industrial automation project in accordance with functional requirements provided to the industrial IDE system in intuitive formats, such as spoken or written plain language text. The system uses generative AI to translate plain language requests or functional specifications into industrial control code, human-machine interface (HMI) applications, device configuration settings, or other aspects of an industrial control project.

An integrated development environment (IDE) for designing, programming, and configuring aspects of an industrial automation system uses a generative artificial intelligence (AI) model and associated neural networks to generate portions of an industrial automation project in accordance with functional requirements provided to the industrial IDE system in intuitive formats, such as spoken or written plain language text. The system uses generative AI to translate plain language requests or functional specifications into industrial control code, human-machine interface (HMI) applications, device configuration settings, or other aspects of an industrial control project.

An integrated development environment (IDE) leverages a generative AI model to generate industrial control code in accordance with specified functional requirements, which can be provided to the industrial IDE system as intuitive natural language spoken or written text. The industrial IDE can also analyze written code in response to natural language prompts submitted against the code, generate answers to user-submitted questions about the code, and offer recommendations for improving the code in response to specific questions or requests submitted by the user.

The invention relates to the technical field of metal plates, and discloses a security and protection electronic equipment metal plate assembly and mold collaborative research and development method which comprises the following steps: establishing a three-dimensional parameterized model of a metal plate assembly based on functional requirements and installation environment constraints of security and protection equipment, and synchronously generating a corresponding mold initial structure parameter library; according to the collaborative research and development method for the metal plate assembly and the die of the security and protection electronic equipment, the metal plate forming process is dynamically simulated through a multi-physics field coupling simulation platform, and material stress distribution data, a springback predicted value and a die abrasion trend curve are obtained in real time; according to the collaborative research and development method for the security electronic equipment metal plate assembly and the mold, the core technical indexes of shortening the mold development period, improving the first-pass yield of products and reducing the accidental shutdown rate of the mold are achieved, and the effect of a full-life-cycle collaborative management and control system from design optimization to intelligent operation and maintenance is formed.

Provided in the embodiments of the present application are an automated software testing method, system and apparatus, and a storage medium. The method comprises: in response to acquiring a function requirement of software or a target function requirement selected by a user, processing the function requirement or the target function requirement on the basis of a test case generation model, so as to generate at least one test case expressed by a natural language (S310); on the basis of a preset condition, obtaining test information of the test case from the test case (S320); on the basis of the test information, constructing a test script corresponding to the test case, and executing the test script to obtain an execution result (S330); and processing the execution result on the basis of an execution result determination model, and determining an execution state of the test case corresponding to the execution result (S340).

An integrated development environment (IDE) leverages a generative AI model to generate industrial control code in accordance with specified functional requirements, which can be provided to the industrial IDE system as intuitive natural language spoken or written text. The industrial IDE can also analyze written code in response to natural language prompts submitted against the code, generate answers to user-submitted questions about the code, and offer recommendations for improving the code in response to specific questions or requests submitted by the user.

The invention discloses a lightweight design method for a thin-wall structure containing a flow channel based on additive manufacturing, and belongs to the technical field of additive manufacturing, and the lightweight design method comprises the following steps: S100, analyzing functional requirements, and constructing a functional requirement model containing the flow channel; s200, a printing direction and additive manufacturing constraint conditions are set, topological optimization is executed on the function demand model, and a preliminary topological structure is obtained; s300, carrying out geometric reconstruction on a topological optimization result to obtain a three-dimensional model suitable for additive manufacturing; s400, carrying out parameter optimization design; s500, the section shape and size of the runner are optimized based on fluid performance requirements; and S600, additive manufacturing manufacturability inspection is conducted on the structure with the section shape and size optimized. And S700, the model obtained after additive manufacturing manufacturability optimization is analyzed and checked. The technical problems that in the prior art, the design requirement of a thin-wall structure containing a runner cannot be met, and the forming quality and the section shape of the inner surface of the runner are difficult to accurately control can be solved.

The invention provides a code generation method and device. Comprising the following steps: in response to a code generation request, performing code demand identification on input prompt information to obtain a structured code demand identification result; the code demand identification result comprises a function demand and first context information; the first context information comprises context description content of the function demand in the code demand identification result; determining second context information based on the function demand and the first context information; the second context information comprises complete environment description content of the function requirement; generating a candidate code based on the function demand and the second context information; and performing code optimization on the candidate code to obtain a target code. According to the method, the target code is generated based on the second context information, and the second context information comprises the complete environment description content of the function requirement, so that the code generation system can generate the code according to the complete context information, and the code generation accuracy is improved.

An integrated development environment (IDE) for designing, programming, and configuring aspects of an industrial automation system uses a generative artificial intelligence (AI) model and associated neural networks to generate portions of an industrial automation project in accordance with functional requirements provided to the industrial IDE system in intuitive formats, such as spoken or written plain language text. The system uses generative AI to translate plain language requests or functional specifications into industrial control code, human-machine interface (HMI) applications, device configuration settings, or other aspects of an industrial control project.

An integrated development environment (IDE) leverages a generative AI model to generate industrial control code in accordance with specified functional requirements, which can be provided to the industrial IDE system as intuitive natural language spoken or written text. The industrial IDE can also analyze written code in response to natural language prompts submitted against the code, generate answers to user-submitted questions about the code, and offer recommendations for improving the code in response to specific questions or requests submitted by the user.

The invention provides an ultra-high performance concrete proportion design method based on an intelligent algorithm and functional requirements. The method comprises the following steps: S1, constructing an ultra-high performance concrete performance prediction database; s2, automatically selecting key variables based on function requirements; s3, training and predicting a machine learning model based on function requirements; and S4, optimal design of the ratio of the ultra-high performance concrete. According to the unsupervised anomaly detection method based on the isolation forest, the database is preprocessed, and the ultra-high performance concrete proportion design key variables are selected through the automatic variable selection method, so that rapid mapping from the mixing amount of each component of the ultra-high performance concrete to each function demand index is realized; through the particle swarm optimization (PSO), the ultra-high performance concrete with specific function requirements is subjected to proportioning design, and finally the ultra-high performance concrete proportioning value closest to the function requirement index is obtained, so that the problems of time and labor consumption, low efficiency and resource waste are solved.

The invention discloses a hardware design method and device, equipment, a storage medium and a program product, and the method comprises the steps: analyzing a function demand of target hardware according to design description information corresponding to the target hardware through a first intelligent agent, and generating function point information, performing module division processing based on the function correlation of each function point in the function point information to obtain module function information, and generating design description information of each sub-module and connection relation information among the sub-modules based on the module function of each sub-module indicated by the module function information; hardware design codes of the corresponding sub-modules are generated based on the design description information of the sub-modules through the second intelligent agent; through a third agent, according to the design description information and the connection relation information of each sub-module and the hardware design code of each sub-module, a hardware design code of the target hardware is obtained through combination; the accuracy of generating hardware design codes (namely RTL design codes) of large-scale complex hardware can be improved.

The invention relates to the technical field of code pre-configuration, in particular to a demand-oriented code pre-configuration method, system and equipment and a storage medium. Matching a plurality of performance function number sequences from the code function library according to the function requirements of the target scene; performing function demand sample frequent mining on the target scene to obtain a function demand input parameter and a function demand output identifier set; inputting the function demand input parameters into a plurality of function number sequences to obtain a plurality of function demand prediction outputs; traversing the plurality of function demand prediction outputs for outlier analysis to obtain a plurality of output prediction outlier factors; traversing the plurality of performance function number sequences to carry out calculation power demand prediction to obtain a plurality of expected calculation power; and based on the plurality of expected computing power and the plurality of output prediction outlier factors, sorting the plurality of performance function number sequences to obtain a target performance function number sequence, and executing code pre-configuration. The code development efficiency is improved, and the code practicability is enhanced.

An integrated development environment (IDE) for designing, programming, and configuring aspects of an industrial automation system uses a generative artificial intelligence (AI) model and associated neural networks to generate portions of an industrial automation project in accordance with functional requirements provided to the industrial IDE system in intuitive formats, such as spoken or written plain language text. The system uses generative AI to translate plain language requests or functional specifications into industrial control code, human-machine interface (HMI) applications, device configuration settings, or other aspects of an industrial control project.

An integrated development environment (IDE) leverages a generative AI model to generate industrial control code in accordance with specified functional requirements, which can be provided to the industrial IDE system as intuitive natural language spoken or written text. The industrial IDE can also analyze written code in response to natural language prompts submitted against the code, generate answers to user-submitted questions about the code, and offer recommendations for improving the code in response to specific questions or requests submitted by the user.

The invention provides a customer service knowledge base construction method and device and a computer readable storage medium. In the scheme, first information including function requirements, performance indexes and business rules of a target product is extracted from a requirement document of the target product, and second information including interface elements, interface element attributes and interface layout information of the target product is extracted from a prototype graph of the target product; inputting the first information and the second information into a pre-trained GPT large model for analysis to obtain a target knowledge point of the target product; generating customer service knowledge base entries according to the target knowledge points, and obtaining a customer service knowledge base formed by the customer service knowledge base entries; and if it is monitored that the version of the demand document and / or the prototype graph is updated, updating the customer service knowledge base according to the updated demand document and / or the updated prototype graph. According to the scheme, the problem of limitation of construction of the customer service knowledge base in the prior art is solved, wherein the limitation comprises low accuracy, low automation degree and update lag.

The invention relates to the technical field of core board testing, in particular to a core board cross-platform function testing and verifying method which comprises the following steps: building a testing environment of a plurality of operating systems and hardware platforms through a virtualization technology or actual hardware, automatically generating a cross-platform compatible testing script based on core board function requirements, supporting multi-platform operation, and verifying the core board cross-platform function. Executing the test scripts in parallel on the platforms, recording and analyzing running logs and outputting results; functional consistency on different platforms is verified through a Hash comparison algorithm, it is ensured that the core board has the same function under the multi-platform environment, performance testing is conducted on all the platforms, performance bottlenecks are recognized, and optimization is conducted through an adjusting and optimizing tool; and finally, verifying the repairing effect through fault positioning and regression testing, and automatically generating a test report. According to the method, the efficiency of cross-platform testing of the core board, the accuracy of function verification and the effect of performance optimization are improved, and the method is suitable for core board testing and optimization scenes in a complex multi-platform environment.

The invention discloses a test case recommendation method and device, electronic equipment, a medium and a product. The method comprises the following steps: when it is monitored that a function demand is changed, obtaining change content; constructing a dynamic knowledge graph according to the change content; wherein the dynamic knowledge graph stores an association relationship among a function requirement, a test scene and a test case; collecting test environment state data; and outputting a to-be-recommended test case set according to the test environment state data and the dynamic knowledge graph. According to the method, the problems of low test case generation efficiency, incomplete coverage and inconsistency with requirements caused by frequent change of function requirements can be solved.

The invention discloses a synchronization unit verification method and device of a digital circuit, equipment and a medium, and relates to the technical field of computers, and the method comprises the steps: embedding an assertion statement rule and an assertion coverage rate evaluation rule in a synchronization unit; the assertion statement rule is used for monitoring the operation state and signal characteristics of the synchronization unit in the data synchronization process, the assertion statement rule is implemented in a parameterization mode to adapt to the function requirements of different circuit units, and the assertion coverage rate evaluation rule is used for counting the execution condition of the assertion statement rule; executing front-end simulation verification of the synchronization unit by utilizing the plurality of test cases, and judging whether a violation condition which is not consistent with the assertion statement rule exists in a case execution result or not: if not, calculating an execution coverage rate of the assertion statement rule based on an assertion coverage rate evaluation rule; and evaluating whether the synchronization unit passes the front-end simulation verification according to the execution coverage rate. According to the method, the possibility of omission of problems due to incomplete verification is reduced, and the execution coverage rate is improved.

The invention provides a multi-agent-based code conversion system and method. The method comprises the following steps: preprocessing an input source code; performing block processing on the source code to obtain source code blocks, obtaining variable information and array size information of the blocks corresponding to the source code, and integrating the variable information and the array size information into complete variable information; fusing the code description file, the code blocks of the source codes and the variable information of the blocks corresponding to the source codes to generate target code blocks; debugging and checking the target code blocks in combination with the source code blocks; the code description file is used for guiding the intelligent agent to establish a jumping type relation in the code conversion process, and it is ensured that the generated target code better meets the actual function requirement of hardware; a block identifier is inserted into a long code to divide the long code into a plurality of blocks, so that the limitation on long code conversion is relieved; codes of different styles can be output by simply adjusting the cue word of the intelligent agent; through multiple times of debugging verification, the conversion quality of the target code is ensured.

The invention discloses a low-code automatic generation method based on AI agent collaboration, and relates to the technical field of computer processing, and the method comprises the following steps: S1, receiving a function demand description text input by a user through a natural language; s2, an input analysis agent reads and analyzes the function requirement description text, key information is extracted, and the key information comprises a key intention, an entity object and an operation constraint condition; s3, performing semantic similarity matching in a predefined model library by a model retrieval agent according to the key information, and retrieving and defining a basic generation model with closest semantics; and S4, receiving the basic generation model and the key information by an adaptive modification agent, and performing context semantic understanding enhancement on the basic generation model. According to the method, end-to-end automatic conversion from business demand description to executable codes is realized through natural language understanding and an automatic code generation technology.

The invention provides a multi-module business process automatic splicing method and system, and relates to the technical field of business process splicing, and the method comprises the steps: carrying out the modularization processing of business functions, obtaining a plurality of function module sets, and each function module set comprises a plurality of independent business function modules; performing function demand analysis based on the real-time service demand, and determining a target function demand; matching to obtain a plurality of standby function modules; compatibility and splicability analysis is carried out, N target function modules are obtained through screening, and N is larger than or equal to 0; carrying out business process analysis, and constructing a business flow chart containing a logic sequence and a dependency relationship; and based on the business flow chart, performing automatic splicing of the N target function modules to form a multi-module business flow. The technical problems that in the prior art, the development time is long and the flexibility is insufficient due to the fact that the corresponding process logic usually needs to be developed from the beginning for each new business requirement, and modular reuse is difficult to achieve are solved.

The invention relates to the technical field of software development, and provides a method and a system for generating a software development scheme. The method comprises the following steps: S1, acquiring a user demand, extracting a functional demand and a non-functional demand, and processing; s2, generating a system architecture design based on a demand analysis result, and selecting a proper technical scheme in a manner of combining a collaborative filtering model and reinforcement learning; s3, based on the architecture design and the demand analysis result, a development task is automatically generated, and resource scheduling is dynamically adjusted; and S4, generating an automatic test based on a demand, and performing intelligent analysis on a test result. And dynamically generating system architecture design and optimizing technical stack selection through a method of combining a collaborative filtering model and reinforcement learning. Collaborative filtering is associated with implicit vectors of a technology stack through user requirements, reinforcement learning optimizes decisions according to historical experience, expandability of architecture design and reasonability of technology type selection are guaranteed, different project requirements are met, and system performance is improved.

The invention provides a personalized function page generation method and system based on a large model, and belongs to the technical field of large models.The personalized function page generation method comprises the steps that firstly, function page requirement description including function expectation and style preference input by a user through a natural language is obtained, and then a requirement analysis module of the large model is called for semantic analysis; the method comprises the steps of obtaining function demand features and style preference features, then retrieving a preset component library matching page component set based on the function demand features, determining component display attributes according to the style preference features, then generating an initial function page layout according to the component set, the display attributes and a preset layout rule, and finally monitoring user interaction behavior data in real time. And a large model dynamic adjustment module is input to adjust the display attribute and the layout structure of the page component to obtain a personalized function page, so that the function page meeting the personalized requirements of the user can be efficiently and accurately generated.

The invention discloses a JavaScript language security reinforcement method based on a virtual machine technology, and belongs to the field of JavaScript languages. The method comprises the following steps: firstly, building a test system comprising a compiler, an assembler, a virtual machine and a packer; then, a developer submits the JavaScript program or the function requirement to be tested to the test system; a test system constructs a to-be-tested program by using a Yarn environment, and a compiler compiles a JavaScript source code and analyzes and converts the JavaScript source code into an intermediate representation IR; the assembler converts the IR into byte codes, and converts the relative reference address into an absolute address by generating a character string table and a lookup table; and the generated byte code is optimized. The test system submits the optimized byte code to the virtual machine, the virtual machine runs a byte code program, and after execution is completed, the test system collects an execution result of the virtual machine and compares the execution result with an expected result; and finally generating a test report and delivering the test report to developers for confirmation. According to the method, the security of the JavaScript code is enhanced through a virtualization technology, and malicious access and analysis are prevented.

An integrated development environment (IDE) leverages a generative AI model to generate industrial control code in accordance with specified functional requirements, which can be provided to the industrial IDE system as intuitive natural language spoken or written text. The industrial IDE can also analyze written code in response to natural language prompts submitted against the code, generate answers to user-submitted questions about the code, and offer recommendations for improving the code in response to specific questions or requests submitted by the user.