20 results about "Functional specification" patented technology

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.

A large language model (LLM) system includes a personal AI agent, an enterprise AI agent, and a public AI agent. A method for operating the LLM includes: executing a first action plan to obtain a first integrated answer and a first integrated score based on a first query using the personal AI agent; and executing a second action plan to obtain a second integrated answer and a second integrated score based on a second query using the enterprise AI agent. A method for applying the LLM system includes: transforming a bitmap of a block diagram into a scalable vector graphics and integrating a semantic tag into the scalable vector graphics; training the large language model by using the scalable vector graphics integrated with the semantic tag and using a functional specification document; and generating a structured text description of the block diagram using the large language model which is trained.

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.

The invention relates to an application management system and method based on a micro-front-end framework, and the method comprises the steps: integrating a micro-front-end technical framework qiankun, achieving the dynamic registration, route monitoring and resource loading of sub-applications through a main application module, building a user management and authority management interface in a system configuration module, enabling a manager to complete the personnel configuration only through the interface, and enabling the system to be convenient to use. And related data can be synchronized to the API gateway, so that binding of the application front end and the application configuration is realized, and application development management is facilitated. According to the invention, a whole set of micro-front-end architecture system covering the full-life-cycle management function of the sub-applications is established, unified functions of application creation, version management, authority management, automatic construction, deployment and the like are provided, the research and development mode and process of the applications in the system are standardized, the complexity and cost of maintenance of the sub-applications in the system are reduced, and the development efficiency of the system is improved. And the stability, maintainability and safety of the system are improved.

The invention relates to a test case generation model training method and a test case generation method, and the method comprises the steps: carrying out the first-stage reinforcement learning training of a preset model through employing a first training data set, and obtaining a first target model; wherein the first training data set comprises a first function specification sample of a plurality of function points and a first standard test case, and the preset model is used for generating a first prediction test case according to the first function specification sample; in the first-stage reinforcement learning training process, a target reward value is adopted to guide a prediction model to optimize a generation strategy, and the target reward value is determined according to a correctness reward rule, a format reward rule and a coverage rate reward rule according to a first function specification sample, a first standard test case and a first prediction test case. On the basis, the test case generation model obtained through training can reverse multiple test scenes such as a test scene, a test scene corresponding to a market problem and a test scene corresponding to a boundary condition.

The embodiment of the invention relates to the technical field of document processing, and discloses a function specification document design method and device, electronic equipment and a storage medium. The method comprises the following steps: after a function model is debugged, decomposing a model structure and a logical relationship of the function model to determine a chapter structure of a function specification document; designing a cover template, and obtaining data source information of the functional model; compiling files corresponding to the cover template and the functional structure based on the data source information and the chapter structure; and compiling and generating a function specification document based on all files. According to the method and the device, the problems of low efficiency and high error rate of a mode of manually compiling the function specification document are at least solved, the compiling efficiency of the function specification document is favorably improved, and the design error risk is reduced.

The application discloses a hardware-in-loop simulation method of a vehicle body domain controller under an AUTOSAR architecture, and the main idea of the application is that a standardized mapping relationship database of a HIL cabinet hardware channel is established based on standardized interface definition of an AUTOSAR basic software layer, and a hardware corresponding relationship configuration file template is constructed; in combination with different function specifications, a subsystem simulation model is built for each function module, a three-layer decoupling architecture is constructed, and dynamic binding of test software and the hardware channel is realized; then, based on actual hardware interfaces and software function definitions, a simulation test bench is built and verification is completed; finally, automatic test cases are generated based on the function specifications, and each subsystem function test of the vehicle body domain controller is carried out in the current test environment. The application significantly shortens the development cycle of the test bench, improves the flexibility and expandability of the test environment, and optimizes the whole life cycle test verification capability.

This application provides an automated code repository generation method, electronic device, and program product, relating to the field of software design and development. The method includes: acquiring functional specification information; generating corresponding functional subtrees based on the functional specification information; clustering nodes in the functional subtrees into multiple functional modules based on the cohesion principle, and generating a modular functional diagram; mapping the functional modules in the modular functional diagram to file structures, generating an enhanced file structure diagram; modeling data flows between functional modules and file sequence dependencies within functional modules based on the enhanced file structure diagram to generate a repository planning diagram; and generating code files using a test-driven development process based on the topological order determined by execution dependencies to form a code repository. This method enhances consistency assurance from high-level functional planning to low-level code implementation, improving the modular quality and maintainability of the code repository generation process.

This invention relates to the field of computer technology and discloses a method and system for predicting new product categories in a centralized procurement platform. The method involves defining demand placeholders containing functional specifications on the buyer's client side, which are then anonymously aggregated by the server and matched against the functional profiles of candidate new products. When a match is found to be successful, a simulation suggestion is sent to the source client, and weighted intention signals generated by the client based on the user's selected tiered intention levels are obtained. Finally, the server calculates one or more weighted intention signals based on the weight coefficients corresponding to each intention level to obtain the total weighted predicted demand and procurement risk coefficient for the candidate new products. This invention resolves the contradiction between the accuracy of demand forecasting and the protection of user business privacy. While effectively protecting data privacy, it quantifies user subjective intentions, significantly improving the accuracy and reliability of forecasts and providing the platform with an objective basis for procurement decisions.

The embodiment of the invention provides a software development method, system and equipment. A demand analysis agent analyzes a function specification file according to a demand analysis rule set and outputs a demand document; the software design agent analyzes the demand document according to a software design rule set and outputs a software design document; analyzing the demand document and the software design document by a code generation agent according to a code generation rule set, and outputting an application layer code; the software test agent analyzes the demand document and the application layer code according to a software test rule set to generate a code scanning result and a test case; and outputting the thinking process of the demand analysis agent, the software design agent, the code generation agent and / or the software test agent. The problem that the output result of the large reasoning model is unstable is solved by fusing the large reasoning model and the whole process of software development and analyzing the development document based on the rule set, and the software development efficiency is improved.

The invention discloses an integrated circuit design method and system, and belongs to the field of integrated circuit design, and the method comprises the following steps: obtaining function specifications and performance indexes of an integrated circuit, and determining physical parameters and manufacturing process parameters of a chip by combining the function specifications and the performance indexes with specific parameters of external equipment; historical design data are collected, a database is established, similarity matching is conducted on obtained parameters from history, a design framework is obtained, and an initial framework is generated; external data is collected in multiple channels, an early warning model is constructed, a constructed framework is evaluated, and the framework is optimized by grading; module design is further refined based on a framework and converted into a schematic diagram and a physical layout, and finally circuit functions are verified through a simulation tool and a result is output. According to the method, through historical data reuse, adaptive modification and external risk early warning, the design period is shortened, the adaptability of the design can be effectively improved, and technical lag is avoided.

Machine-leaming-aided logic synthesis using do-not-care-based backpropagation, including constructing a neural network (NN) model based on a functional specification of a circuit design, training the NN model to perform a function of the circuit design, where nodes of the neural network perform a first Boolean function (e.g., AND), and where the training comprises do-not-care-based backpropagating, which may include explicitly computing target functions at fanins of the nodes. The NN may be converted to a two-input graph having nodes that represent a second Boolean function (e.g., AND). The function of the circuit design may include a multiplier function, and the graph may include an AND-inverter graph (AIG). A Boolean patch may be constructed to correct an error in the graph.

The application discloses a retrieval method and device of application function information. It is related to the field of artificial intelligence, and the method comprises the following steps: receiving a retrieval request initiated by a requester; in response to the retrieval request, generating a reference specification set of a target application by using a first generation model, wherein the first generation model is obtained by training a first initial generation model by using an application attribute library and a technical specification library which are marked with application specification set samples of each application in a plurality of applications; generating a target specification set according to the reference specification set and a target technical document of the target application by using a second generation model, wherein the second generation model is obtained by training a second initial generation model by using application specification set samples which are marked with function specification set samples of each function in each application and function technical documents; and sending the target specification set to the requester. Through the application, the problem of low retrieval efficiency of application function-related technical specifications in the related art is solved.

The application discloses a kind of test case automatic generation method and system for vehicle controller hardware-in-the-loop test, belong to the field of automobile electronic testing technology.To solve the problem of low efficiency of test case writing, rely on manual experience and unstable problem of directly using large language model to generate results, the generation process is divided into three steps of function list generation, test scheme generation and test case file generation in series: first, input the function specification text and operating environment information into the first large language model to generate the atomized function list, then input the test behavior library and test scheme generation method library into the second large language model to generate the test scheme, finally input the test behavior implementation step library and test case writing rules into the third large language model to generate the atomized test step and convert it into a bench executable test file.The application is used for the automatic generation of test cases for vehicle controller hardware-in-the-loop test, and can efficiently and reliably realize end-to-end automatic generation.

The present disclosure discloses a method comprising parsing information associated with a plant structure and an automation project associated with an industrial plant. The plant structure comprises a list of a plurality of entities associated with the industrial plant and the automation project comprises functional specification corresponding to the plurality of entities. The method also comprises identifying a set of relationships among the plurality of entities based on the parsed information and one or more of a set of predefined rules, naming conventions, and reference data. The method further comprises generating a user interface representing a hierarchical structure of the plurality of entities and the corresponding set of relationships in a graphical manner. Each of the plurality of entities is associated with the corresponding functional specification.

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.

The invention discloses a method and a system for generating a test code of an automobile software unit. The method comprises the following steps of: 1, converting a function into a Mermaid flow chart in a normalized manner; 2, the generated flow chart is submitted to an AI model to produce a Gtest case; and step 3, performing software function testing by using the generated Gtest case. According to the method, the problems that a traditional development module depends on manpower from demand to test, the efficiency is low, and errors are prone to occurring are solved, Mermaid is introduced to serve as an intermediate logic model, manual intervention and an intelligent model are combined, and strict consistency and high quality of specifications, flow diagrams and test codes are ensured. And the automation level, quality and efficiency of automobile software development are obviously improved.

Systems and methods are provided for assisted software feature (or “requirement”) generation and for the automated or semi-automated generation of test cases therefrom. Also included are improved systems and methods for associating test cases with requirements and for modifying the test cases as the requirements are modified, added, and / or removed. These embodiments allow the cost of generating and maintaining a set of requirements and test cases and the cost of validating such a set of test cases to be reduced.

This invention relates to the field of scene selection technology, specifically a method for selecting high-value simulation scenes for autonomous driving. First, the description text of each test scene is acquired. This text is then input into a pre-trained scene parsing model to obtain the structured natural language descriptions of the test scenes output by the model. A first round of screening is performed on these structured natural language descriptions using functional specification rules. Next, the structured natural language descriptions of each test scene are clustered, and the clustering results are determined. Based on the positional relationship of each test scene's structured natural language description within the clustering results, the scenes to be tested are selected. Autonomous driving test tasks are then executed on simulation software. Based on the test results, high-value simulation scenes for autonomous driving are determined. This multi-stage screening mechanism enables accurate selection of high-value simulation scenes for autonomous driving.