289 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) 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.

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 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 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 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.

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 cloud native security configuration system and method based on container analysis and LLM, and the system comprises a mirror image static analysis module which is used for compiling a Linux kernel and a standard library source code to extract intermediate representation, and tracking and constructing a double-layer mapping relation library from the system call to the container capability; the dynamic binary extraction module is used for executing the container mirror image and extracting a binary file of a core function; the mirror image static and dynamic association module is used for executing two-stage static binary file analysis and extracting function requirements required by system calling and mirror image for loading during container running; and the cue word construction and model fine adjustment module is used for constructing cue words, performing fine adjustment on the LLM model and generating a minimum privilege function limitation configuration file of the container. According to the method, static analysis and runtime analysis are combined, the container mirror image is thoroughly checked, the function, which is specified by a user and exceeds the original definition of the mirror image, of the LLM model is finely adjusted through the cue word, and privileged function security configuration is generated according to specific requirements.

A human-machine interface (HMI) development system leverages a generative AI model to assist in development of HMI projects in accordance with specified functional requirements, which can be provided to the development system as intuitive natural language spoken or written text. The system can formulate and implement HMI project edits during design time based on analysis of this natural language design input. After the HMI project is deployed as a runtime application, the system can also receive and process natural language requests to modify the runtime HMI in accordance with described modification criteria.

The invention provides a communication module function extension method and system applying dynamic loading, and relates to the technical field of communication, and the method comprises the steps: firstly, determining a dynamic loading trigger condition space containing function requirements, module resources and external environment trigger conditions, and collecting data to generate a trigger condition matching data set; then screening adaptive function modules from a preset function module library, and matching corresponding information based on different triggering conditions to generate an adaptive function module set; then carrying out cooperative adaptation processing on the adaptation function module and the communication module to generate a cooperative adaptation result; dynamically injecting a module based on a collaborative adaptation result and constructing a function extension calling architecture; and finally, collecting operation interaction data to generate a communication module function extension running chart, thereby realizing flexible, efficient and stable extension of the communication module function, and improving the adaptive capacity and competitiveness of the communication module.

The invention discloses a demand development method, device and equipment. The method comprises the following steps: calling a demand analysis agent to analyze a natural language demand into a structured function demand unit comprising an input specification, an output specification and an execution constraint; the calling code generation agent generates source codes corresponding to the development requirements according to data type definitions and function calling specifications in the structured function requirement unit and the local project code library; calling a code test agent to generate and execute a test case based on the source code and the structured function demand unit; and after determining that a software deployment condition is met based on a test result, calling a code deployment agent to generate a deployment script and configuration information, and submitting the deployment script and the configuration information to a deployment execution engine to complete automatic deployment. According to the application, end-to-end automatic development from natural language requirements to application deployment can be realized.

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 object generation method and apparatus, a computing device, a storage medium and a program product. The method comprises the steps of determining a function demand of a to-be-developed target object; under the condition that it is determined that the function requirement can be met on the basis of a basic universal function module of the basic universal function library, according to the basic universal function module of the basic universal function library, a target function module corresponding to the function requirement is determined, the number of occurrence times of the functional modules in the multiple functional modules of the multiple development objects reaches a preset condition; under the condition that it is determined that the function requirement cannot be met based on the basic universal function module of the basic universal function library, determining an independent customized function module of the to-be-developed target object according to the function requirement; generating a target object according to the target function module and / or the independent customization function module; by separating the target function module from the independent customized function module, maintenance and updating can be performed more intensively and efficiently, and the maintenance workload can also be reduced.

A human-machine interface (HMI) development system leverages a generative AI model to assist in development of HMI projects in accordance with specified functional requirements, which can be provided to the development system as intuitive natural language spoken or written text. The system can formulate and implement HMI project edits during design time based on analysis of this natural language design input. After the HMI project is deployed as a runtime application, the system can also receive and process natural language requests to modify the runtime HMI in accordance with described modification criteria.

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 provides a method for developing a tool function for an intelligent agent through computing power of an intelligent computing center, and relates to the technical field of intelligent computing centers, intelligent computing centers and computing power infrastructures, and the method comprises the following steps: S1, a manufacturing intelligent agent receives task information provided by a user through an interactive interface and used for developing the tool function for a target intelligent agent; s2, the manufacturing agent determines development requirements of the tool function according to the task information, and the development requirements at least comprise function requirements of the tool function; and S3, the manufacturing agent automatically generates a code of the tool function of the target agent according to the development requirement of the tool function. In the invention, through the manufacturing agent running in the intelligent computing center, the process of communicating with the user, confirming the development demand, automatically completing the development of the tool function of the target agent and replacing the manual development of the tool function code can be realized, so that the development cost is effectively saved, the intelligent computing center can provide sufficient computing power resources, and the development efficiency is improved. And the development efficiency is greatly improved.

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 an adaptation and cutting method and system based on an electric power terminal equipment swan operating system, and the method comprises the steps: firstly carrying out the adaptation between the function demands and performance requirements of the electric power terminal equipment and the type of the swan operating system and the type of a chip; then, a service management center, an equipment event monitor and an application incubator process are started in sequence through an initialization script, system service adaptation is achieved, hardware nodes needing to be clipped are removed based on a layered clipping strategy, customized function clipping can be conducted on the swan mongolian operating system according to different electric power application scenes, then drive adaptation is conducted, and the operation efficiency of the swan mongolian operating system is improved. According to the method, the power terminal equipment is ensured to stably and efficiently operate under the selected swan-gap operating system, and finally old application transplantation and new application deployment on the power terminal equipment are realized, so that efficient operation and function customization of the power terminal equipment under the swan-gap operating system can be realized; and the overall performance and reliability of the power Internet of Things system are greatly improved.

The invention provides a difference detection and authority early warning method for Chrome extension over-authorization, and belongs to the technical field of browser extension security. The method comprises the following steps: firstly, extracting an authority set declared in Chrome extension and an actually called API set through a static analysis technology, then establishing an authority-API incidence matrix, and identifying the difference between an authority application and an actual function demand through a difference comparison algorithm. Besides, the invention also innovatively designs a permission early warning mechanism based on the risk level, and develops a corresponding Permission Guard, and the Permission Guard can monitor the Chrome extension installed by the user in real time, and prompts the danger level of the user permission and the extension information of permission abuse. Through experimental verification, in a data set containing 199058 extension samples, 98072 extensions with permission applications inconsistent with actual behaviors are successfully detected through the method, and the effectiveness and practicability of the method are verified.

The invention relates to the technical field of Internet of Things equipment management, in particular to a multi-equipment heterogeneous protocol operation method and system based on an Internet of Things platform. By constructing an analysis and adaptation framework of a protocol analysis engine, a dynamic object model library and a rule mapping engine, flexible expansion and interoperability of a communication protocol between Internet of Things equipment and a platform are realized, the development efficiency is improved, and the operation and maintenance cost is reduced. Dynamic access of multiple devices and multiple protocols is supported, and the access threshold is lowered. The dynamic physical model library supports versioning management, and adaptive physical models can be dynamically bound according to different equipment models and function requirements. The configuration process of the physical model is simplified, and the problem of protocol adaptation explosion caused by static physical model configuration is eliminated. The rule mapping engine realizes bidirectional data conversion between a heterogeneous protocol and a physical model through a Grouping script, a data interaction link between multi-protocol equipment is opened, and the cooperative work capability between the equipment is improved.