169 results about "Requirements analysis" patented technology

The invention discloses a structured text code generation and review method, which comprises the following steps of: receiving a control task demand input by a user, supporting natural language, structured form or graphical process input, performing deep semantic analysis by utilizing a demand analysis module, identifying control conditions, control actions and constraint factors, and generating and reviewing a structured text code. The task is converted into a plurality of control units through the SCoT chain; the SCoT chain reader generates a semantic vector according to a task demand, the AST reader generates AST representation through a grammar rule structure and a hierarchical relationship, and the decoder predicts a next grammar rule and generates an ST code in combination with the SCoT chain and AST features; and verifying grammar and logic of the ST code through an interactive automatic review and repair mechanism, if compiling errors occur, analyzing errors by the teacher model and providing repair suggestions, and performing code repair by the student model according to guidance until the code conforms to an expected function and passes compiling.

The invention discloses a document review method and device based on the full life cycle of science and technology projects and a medium, belongs to the technical field of document review, and solves the problem of how to improve the accuracy of normative review of science and technology project documents. According to the method, project document content is sequentially decomposed into field type analysis, specification requirement analysis and content specification analysis on the basis of the thinking chain technology, each item of analysis depends on the result of the previous item of analysis, and a complete path of conventional review is constructed step by step; the method comprises the following steps: analyzing whether a conflict and a logical conflict exist between a current to-be-audited project document and a historical document or not by utilizing a retrieval generation enhancement technology, and obtaining a plurality of fragments associated with to-be-audited fragments of the document from the documents in different life cycles; and ranking of possible useful fragments is provided for the large language model, an examination result is given, logic conflicts and contradictions among the documents are identified and solved, and the examination accuracy is improved from the aspects of consistency and logicality of the documents to be examined and historical documents.

The invention provides a software demand defect detection method based on a large language model and a satisfiability problem solver, and the method comprises the steps: constructing a domain knowledge base, guiding the large language model to extract key elements in a demand text through combining with a cue word project, and recognizing imperfect and ambiguous defects; and meanwhile, the demand is converted into a logic expression, and logic inconsistency is detected by using an SAT solver. According to the method, incremental updating of the knowledge base is supported, efficient retrieval and comparison are achieved through vectorization and Hash coding technologies, experiments show that the method is remarkably superior to a traditional technology in demand detection in the fields of finance and the like, defects can be accurately positioned, correction suggestions can be provided, and the efficiency and accuracy of demand analysis are effectively improved.

The invention relates to the technical field of artificial intelligence, in particular to a visual large screen development method and system based on a multi-modal large model, and the method comprises the following steps: a demand analysis step, an intelligent generation step, a visual arrangement step, a configuration management step and an operation support step. The method has the beneficial effects that the system can synchronously analyze natural language instructions, business data parameters and visual reference examples through a multi-modal semantic alignment engine, and a design scheme with both function completeness and aesthetic consistency is generated. In scenes of smart city situation awareness, industrial equipment real-time monitoring and the like, a user only needs to input demand descriptions of'displaying energy consumption trends and abnormal point locations of all regions in recent half a year 'and the like, a complete large screen scheme including a thermodynamic map, a time sequence broken line graph and a 3D alarm mark can be automatically generated, and the development period is shortened by more than 70% compared with a traditional mode.

The invention provides a power centralized control center data verification and backup method and device, and the method comprises the steps: obtaining hardware resource information corresponding to an operating system, and constructing a thread resource pool; the method comprises the following steps: connecting data sources of an electric power centralized control center, classifying and rating the data sources, and carrying out real-time demand analysis by adopting a parameterized mixed time algorithm to obtain a data task queue with a priority mark; monitoring the load state of an operating system and the length of a task queue, performing resource evaluation by applying an online distributed queue length estimation algorithm, dynamically creating a working thread and allocating resources; based on a thread resource allocation scheme, executing parallel data verification by adopting a sub-exponential algorithm on an independent set; and evaluating a backup demand according to the data verification result set, determining a backup strategy, and executing parallel data backup. According to the method, the characteristics of a domestic operating system are fully utilized, efficient verification and backup of the data of the electric power centralized control center are achieved, and the system resource utilization rate and the data safety are improved.

The invention provides an end-to-end intelligent system development method and system based on an AI large model. The method comprises the following steps: S1, receiving a system demand described by a user through a natural language; s2, analyzing the requirements through an AI large model and converting the requirements into formalized specifications; s3, automatically generating a system architecture and dividing components; s4, generating each component code in a recursive manner; s5, dynamically detecting and repairing the generated code problem; s6, automatically integrating all components to form a complete system; and S7, continuously optimizing the system based on system feedback or user feedback. According to the method, work of multiple stages such as demand analysis, architecture design, module division, code writing and testing is automatically completed, distributed integration and smart contract are performed, distributed integration verification is performed through a block chain smart contract and a graph database, data consistency, interface matching and security among components are ensured, the integration process is optimized, and the integration efficiency is improved. Cross-domain cooperation is achieved, and the development efficiency is high.

The invention provides a mock platform construction method oriented to a travel saas platform. The mock platform construction method comprises the following steps: demand analysis: determining a target and a demand of a Mock platform; environment preparation: ensuring that the Java environment of the target SaaS platform meets the operation of the java byte code instrumentation technology; integration of a java byte code instrumentation technology: the java byte code instrumentation technology is integrated into an SaaS platform; according to the invention, a Java byte code instrumentation technology is utilized to construct a software as a service (SaaS) platform interface Mock platform which is powerful in function, flexible and easy to use, and the Mock platform can dynamically perform Mock on the interface of the SaaS platform without restarting an application, so that the development and test efficiency is greatly improved, and the development cost is reduced. And the Mock platform also has the characteristics of non-invasiveness, dynamic plugging, class isolation, flexible AOP support, self-definition, real-time monitoring and fault simulation, easiness in integration and use, safety, fault positioning and performance optimization.

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 circuit board module deformation testing system and method for SMT automatic patch forming, and belongs to the technical field of circuit board deformation testing, and the system comprises a warping judgment execution demand analysis module, a first execution strategy determination module, a second execution strategy determination module and a support sinking adjustment module. The circuit board warping and supporting structure deformation risk can be accurately quantified, the Z-axis compensation value, the mounting speed, the pressure and other parameters are dynamically adjusted, mounting deviation caused by circuit board deformation is compensated in real time, the element mounting precision is controlled within the preset range, meanwhile, through hot spot area tracking and supporting sinking graded adjustment, the element mounting precision is improved, and the element mounting precision is improved. The stress concentration risk is reduced, the problems of poor welding, element breakage and the like caused by aggravation of deformation are avoided, the stability of the SMT mounting process is improved, the deformation-related reject ratio is reduced, and the consistency and reliability of the mounting quality of the circuit board are improved.

The invention relates to the technical field of electromechanical cloud management and control, in particular to an electromechanical converter cloud edge collaborative management and control system which comprises a cloud edge collaborative management and control center, an edge management module, a task division module, a dynamic distribution module, a distribution evaluation module, a collaborative management module and an execution feedback layer. According to the method, analysis is preliminarily carried out from the angle of historical data processing capability of the edge node so as to preferentially match the equipment end, and meanwhile, division processing is carried out according to the task quantity and the task type, so that the tasks submitted by the equipment end are reasonably distributed to the edge node and the cloud server, and the efficiency is improved. Analysis is deeply carried out from a single-point angle and an overall angle through an information feedback mode, that is, rationalized and targeted management is carried out on the edge nodes from the single-point angle, so that the resource dynamic allocation performance of the edge nodes is improved, collaborative management demand analysis is carried out on collaborative performance data from the overall angle, and the resource dynamic allocation performance of the edge nodes is improved. The collaborative management efficiency among the equipment end, the edge end and the cloud server is improved.

The invention relates to the technical field of computer data processing, in particular to an intelligent model system for automatically generating a standard protocol interface, which comprises the following steps: acquiring demand information input by a user through a demand acquisition module and converting the demand information into standardized demand parameters; the protocol knowledge base module outputs a compliance rule set according to the target protocol type, and the interface generation module automatically generates an interface source code, a configuration file and an interface document according to the standardized demand parameters and the compliance rule set. The verification module verifies and optimizes the generated interface, and the self-learning module updates system analysis logic and rule content according to a verification result. The system adopts a natural language processing and structured analysis double-path fusion technology to realize accurate analysis of requirements, realizes intelligent matching of protocol rules through a protocol knowledge graph, completes automatic generation of codes based on a symbol reasoning and neural code generation technology, forms a complete closed loop of requirement analysis, protocol adaptation, code generation and verification optimization, and realizes automatic analysis of the requirements. And the interface development efficiency and quality are effectively improved.

The invention discloses a development management system and method for an API interface, and relates to the technical field of software engineering. The system comprises: an intention understanding and design engine, which analyzes a multi-modal service demand into a structured API development task; the agents collaboratively develop a network, and the multiple AI agents are dispatched to generate API specifications, codes, test cases and deployment configurations in parallel; the API ecological dynamic map construction module is used for automatically constructing and updating a dynamic map of dependency and data flow direction between APIs based on a generated product; a continuous learning and evolution engine analyzes the atlas and operation data to identify optimization points and generate or execute evolution policies. All the modules form a closed loop, and output of the evolution engine is fed back to the intention understanding engine to optimize subsequent design. The corresponding method comprises the steps of demand analysis, intelligent collaboration, atlas construction and closed-loop optimization. According to the method, automatic development, intelligent collaboration and continuous architecture optimization of the API are realized, and the development efficiency and the system maintainability are improved.

The invention relates to the technical field of automatic programming, in particular to a front-end and back-end code generation and deployment system based on a text AI model, and the system comprises a demand analysis module, a code generation module, an environment adaptation module, a task scheduling module and a process optimization module. According to the method, through the intelligent task scheduling and environment adaptation strategy, the efficiency and accuracy of front and rear end code deployment are remarkably improved, the task execution path and time interval are optimized, the resource utilization rate of the system is increased, the priority and execution area of task deployment are accurately matched, redundant calculation and resource waste are reduced, and the task deployment efficiency is improved. The execution efficiency of distributed tasks is accelerated, an intelligent adaptive script identifies and adjusts environment differences in real time, the problems caused by environment configuration differences are solved, the code deployment automation and precision are improved, resource allocation and task scheduling path selection are optimized, the system can quickly meet the complex deployment requirement, and the deployment efficiency is improved. And efficient completion and quick response of tasks are ensured.

Methods and systems are described that use artificial intelligence (AI)-based natural language processing (NLP) techniques to rapidly analyze, merge, and / or identify relationships between systems engineering artifacts (e.g., system requirements, system architecture descriptions, research requirements, risk assessments, etc.) to accelerate systems engineering program management, technical capability development, and acquisition initiatives associated with systems engineering projects.

The invention provides a car insurance intelligent quotation system based on multi-dimensional data analysis, and the system comprises the following modules: a front-end configuration management module which carries out the rule configuration at a business front-end configuration interface, and obtains an electronic form; the intelligent analysis module is used for extracting keywords in the electronic form by adopting OCR (Optical Character Recognition) and preprocessing data to obtain data I; and the scheme matching module takes the data I as the input of a transformer model, outputs a scheme with a high matching degree and predicts an insurance conversion rate corresponding to the scheme. Intelligent quotation is performed by fusing multi-source heterogeneous data, a dynamic configuration rule engine and a machine learning algorithm, a vehicle-user-driver protection three-dimensional data association model is constructed, an end-to-end intelligent quotation system from data acquisition, demand analysis to scheme recommendation is realized, and quotation accuracy and customer conversion efficiency are remarkably improved.

The invention discloses an optimization method and system for processing energy consumption of an intelligent machine tool, and belongs to the technical field of processing equipment control, and the method comprises the steps: obtaining operation data of the current intelligent machine tool during operation and material data on a conveying line, building a state switching demand analysis model, and generating a state switching demand index; according to the state switching demand index, whether the intelligent machine tool needs to operate at the lowest power or not is judged, and the operation state of the intelligent machine tool is adjusted to operate at the lowest power through the control end; according to the material fault end position, the material arrival prediction time is generated, a machine tool starting opportunity analysis model is established, the intelligent machine tool starting time is generated, and the intelligent machine tool is started through the control end; according to the method, precise shutdown decision and start-stop opportunity optimization can be realized, invalid idle energy consumption and frequent start-stop loss can be reduced, energy consumption saving and equipment service life maintenance are balanced, and the energy utilization efficiency is effectively improved on the premise that the machining efficiency is guaranteed.

The invention relates to the technical field of software testing, in particular to an AI-based low-code intelligent test generation system which comprises a demand analysis module, a test path generation module, a test script conversion module, an execution environment management module and a result analysis module. A test path of the test path generation module is supplied to the test script conversion module and the result analysis module, a test script generated by the test script conversion module is sent to the execution environment management module, and an execution result of the execution environment management module is fed back to the result analysis module; and an optimization suggestion generated by the result analysis module is sent to the test path generation module and the test script conversion module. Through cooperation of multiple modules, full-process automation of low-code testing is achieved, testing paths and scripts are dynamically optimized, testing efficiency and coverage pertinence are improved, manual intervention and the error rate are reduced, and dynamic adaptation and execution stability of a testing scheme are ensured.

The invention provides a unified computing power management and control platform and method.The computing power management and control platform is integrated with a plurality of intelligent computing centers in different position areas through a unified northbound interface, a resource management module abstracts physical resources of the intelligent computing centers into virtual resource data, and a unified resource pool is constructed; the data acquisition module receives operation monitoring data of each intelligent calculation center and preprocesses the operation monitoring data; the resource sensing module is used for constructing a dynamic resource portrait for the uniform resource pool based on the preprocessed operation monitoring data; the task sensing module performs resource constraint and service quality demand analysis on a calculation task submitted by a user, and constructs a task portrait; the resource scheduling module forms a resource scheduling decision result according to the dynamic resource portrait and the task portrait; and the resource arrangement module performs resource scheduling and calculation task allocation according to the resource scheduling decision result. The overall utilization rate of the heterogeneous computing power cluster is remarkably improved, and the island effect of a traditional resource pool is broken through.

This application is applicable to the field of software development technology and provides a code review optimization method, including: parsing the requirement description to generate the requirement analysis results; preprocessing the software code to obtain the static analysis results; running the software code, dynamically analyzing the running software code to obtain the dynamic analysis results; using a deep learning model to integrate the requirement analysis results, static analysis results and dynamic analysis results to identify the vulnerabilities of the software code; generating a comprehensive vulnerability feature library based on historical vulnerability data and expert knowledge; performing risk assessment and vulnerability evolution prediction on the vulnerability points to obtain the analysis risk score and security threat points within a preset time, and generating a code optimization strategy. This application can optimize according to the actual problems encountered by developers during the development process, ensure that code modifications are directly targeted at specific problems, improve the accuracy and efficiency of optimization, and at the same time have a predictive function, thereby improving code security.

The present invention relates to a method for converting a Simulink-StateFlow model into a NuSMV model, which includes the following steps: conducting a requirements analysis on the system to be evaluated and constructing a Simulink-StateFlow model; extracting program statements, custom function statements, and logical sequence relationships in the model, and respectively constructing a program statement data table, a custom function data table, and a logical sequence data table; integrating the model program and sequence to generate a model information table; analyzing the Matlab programming language and constructing Matlab syntax rules; processing the program statements in the model information table according to the syntax rules and parsing them into an abstract syntax tree; processing the abstract syntax tree to determine an algorithm for converting it into NuSMV statements; and processing the model information table according to the conversion algorithm to generate a NuSMV model. The present invention greatly improves the efficiency and accuracy of the NuSMV tool for model checking of the Simulink-StateFlow model, and realizes the safety verification of the Simulink requirements model of the control system.

The invention relates to the technical field of computers, and discloses a test case generation method and device, equipment and a medium, and the method comprises the steps: receiving a software test demand through a demand analysis agent, extracting a test point of the software test demand, and constructing a target knowledge graph according to the test point; generating an initial test case based on the test target knowledge graph through the case generation agent; executing the initial test case through the execution verification agent to obtain a test result; the test result comprises validity judgment and judgment basis of the initial test case; and in response to the test result, judging that the initial test case is an invalid test case, optimizing strategy parameters of each agent in the agent system based on the judgment basis through the evolutionary learning agent, and generating a new test case. The application can respond to the change of the test demand in real time, automatically adjust the test strategy, and improve the test quality and efficiency.

This application discloses a method and system for audit data analysis requirements parsing based on metadata relationship graphs. By acquiring audit text, metadata relationship graphs, audit rule bases, business-level templates, and business benchmark data, the audit text undergoes semantic flow parsing and is mapped to the metadata relationship graph. A field strength correlation graph is generated through propagation calculation. Activated nodes are selected based on field strength thresholds and their relationships are expanded using the audit rule base to construct activated subgraph data. Based on the business-level templates, the activated subgraphs are reconstructed into a tree-like parsing structure and pruned according to field strength to generate a pruned parsing tree. Finally, node perturbation coefficients are calculated based on the business benchmark data and hierarchically aggregated according to the tree structure to generate an audit requirement perturbation graph. This transforms the traditional audit data analysis process, which relies on manual experience, into an automated and intelligent graph calculation process, significantly improving the accuracy, comprehensiveness, and efficiency of audit data analysis.

The invention belongs to the technical field of vehicle-road cloud integrated systems, and discloses a method for analyzing functional requirements of a vehicle-road cloud integrated system based on LLM, and the method comprises the following steps: S1, collecting and preprocessing basic data; s2, structured extraction of VRCIS requirements: semantic analysis is performed on the design requirement document based on LLM, a data structure is converted, and functional requirements and non-functional requirements are extracted; s3, constructing a VRCIS demand and benefit-critical person matrix: based on the output of the S2, mapping the function demand of each VRCIS benefit-critical person and the system design key dimension, and generating a standardized quantization matrix which can be identified by a machine; s4, quantitative analysis of demand priorities: identifying the demand priorities through quantitative analysis by utilizing the benefit-critical person matrix constructed in the S3 and fusing cost-benefit analysis; and S5, outputting a demand analysis result. The method is high in analysis efficiency, and the problems that in the analysis process, demand decomposition is not in place, the demand priority is not clear, and a general demand template cannot fully express VRCIS complexity are solved.

This invention relates to the technical fields of data quality, data management, and data governance. Specifically, it relates to a method for simultaneously conducting data governance within a newly built business information system. This method establishes a general data management standard covering data specifications, database specifications, and process specifications; builds a supervisory standard that runs through the entire process of project requirements analysis, design, development, deployment, and operation and maintenance; and integrates these two types of standards into the technical requirements of the newly built business system project. Data governance is implemented step-by-step at each stage of the project, thus avoiding data quality problems from the source of business system construction. This avoids the additional costs and schedule risks of traditional post-event governance, ensures that the system data format is uniform, secure, and compliant, and can seamlessly integrate with the enterprise's existing data governance system, solving the problems of data silos, redundancy, and inconsistency in multi-system parallel scenarios.

This invention relates to a multi-objective trade-off optimization and decision-making method and system for electric drive controllers, including: constructing a requirements analysis model; constructing a top-level performance target analysis model; constructing a top-level system architecture design model, constructing test models for subsystems, sub-functions, and sub-modules, and designing test cases; constructing design modules, implementation path models, and corresponding simulation models for subsystems, sub-functions, and sub-modules; multi-objective trade-off optimization; prototyping and verification; building a digital twin system; and knowledge base construction and iteration. This invention enables early quantitative evaluation and automatic optimization of design schemes.

A requirements analysis system outputs an existing requirement, to which a topic is assigned, as training data. The number of first requirements, to which at least one is assigned by a topic and a sub-topic, is greater than or equal to a threshold. This training data is used to train a classification model that assigns topic candidates to at least a second requirement, described in a second document as the analysis target, and in which the number of topics is adjusted. The system receives the training data to create the classification model, feeds the second requirement into the classification model, assigns topic candidates to the second requirement, and assigns sub-topics to the second requirement for each topic candidate, in relation to the topic candidates obtained from the hierarchical dictionary.

This invention discloses a software testing requirements analysis method based on knowledge graphs, comprising the following steps: Step 1: Collecting requirements-side and verification-side data to form a test requirements analysis corpus; Step 2: Extracting semantic objects of requirements, behaviors, and assertions; Step 3: Constructing a three-domain test knowledge graph; Step 4: Generating a test assertion tension field; Step 5: Inputting the test assertion tension field into an improved Hypergraph Transformer model to obtain a test requirement tension propagation feature map; Step 6: Generating a test requirement gap map; Step 7: Obtaining the test requirement decomposition results; Step 8: Updating the three-domain test knowledge graph and the test assertion tension field based on test execution feedback. This invention employs an assertion gap tension resonance mechanism and an improved Hypergraph Transformer model to improve the accuracy of software testing requirement gap identification and decomposition.

A building system can operate to receive a requirement to implement an artificial intelligence (AI) service. The requirement can include an indication of a type of an entity, wherein the AI service is configured to generate an analytic for the entity of the type of the entity or a control setting for the entity of the type of the entity. The requirement can include a data element that the AI service is configured to operate on to generate the analytic or the control setting. The building system can operate to determine that the building system meets the requirement to implement the AI service responsive to a determination that a digital twin of the building system includes the entity of the entity type and the data element and implement the AI service responsive to a determination that the building system meets the requirement.

The invention discloses an intelligent automatic test system and a test method, and belongs to the technical field of software testing, the system comprises a hardware layer and six software modules, namely a demand analysis module, a large model processing module, a test execution module, a self-healing optimization module, a result analysis module and a knowledge base management module, which are deployed on the hardware layer. The method comprises the following steps: extracting structured data through a demand analysis module, and intelligently generating test assets by a large model core processing module; the test execution module adopts a fusion positioning technology to carry out multi-terminal automatic test; the self-healing optimization module monitors the interface change in real time and automatically corrects the script; the result analysis module identifies defects and generates a report; and the knowledge base module continuously iterates to provide support. According to the invention, full-process automatic closed loop from demand to report is realized, the problems of low efficiency, poor compatibility and high maintenance cost of the traditional test technology are solved, and the test intelligence level and the adaptive capability are obviously improved.

The embodiment of the invention provides an iOS automatic development method based on artificial intelligence, and the method comprises the steps: obtaining a development basic file, recognizing a UI design draft based on a visual recognition model, and generating a UI code; processing the demand document based on the demand analysis model, and generating a demand implementation program statement; processing the interface definition document based on an interface calling model, and generating an interface calling program statement; and inputting the UI code, the demand implementation program statement and the interface calling program statement into a template engine to obtain a test case corresponding to the specific function. On the basis of the method, tedious operations of manually interpreting design draft element attributes to write UI codes, manually analyzing demand documents to write logics and writing interface calling codes one by one in traditional development are replaced, a plurality of time-consuming development links are converted into an automatic process, the development period is greatly shortened, and the development efficiency is improved. And meanwhile, efficiency loss caused by manual operation is avoided, and the overall development efficiency of the iOS application from interface construction to function implementation is remarkably improved.