95 results about "Software requirements" patented technology

The invention relates to an incidence relation determination method and device, computer equipment, a storage medium and a computer program product. Relates to the technical field of software engineering. The method comprises the following steps: constructing a code knowledge graph based on a source code of a to-be-processed project, and constructing a demand knowledge graph based on a demand document of the to-be-processed project; mining historical data of the to-be-processed project, establishing a tracking link between the code knowledge graph and the demand knowledge graph, and generating a unified knowledge graph; receiving a query request of a user, and performing retrieval in the unified knowledge graph based on the query request to obtain structured context information; and obtaining enhanced prompt information based on the structured context information and a preset prompt template, sending the enhanced prompt information to the large language model, and outputting target result information corresponding to the query request based on the large language model. By adopting the method, the efficiency of determining the incidence relation between the software requirement and the source code can be improved.

The invention discloses a software requirement modeling method and device based on a natural language, equipment and a medium, and relates to the field of software requirement modeling. According to the software demand modeling method and device based on the natural language, the equipment and the medium, through automatic demand analysis and model generation, the manual workload is greatly reduced, and meanwhile, errors caused by manual understanding deviation are reduced; close connection among the steps is ensured by sharing intermediate representation and a unified data model, output of the previous step provides structured information for input of the next step, and information loss or distortion is avoided; a demand provider is allowed to participate in a model confirmation process through an iterative demand acquisition and modeling framework of man-machine cooperation, and the quality of a demand model is continuously improved; by means of the model consistency analysis technology based on the data flow dependency relationship, the problem of inconsistency between the requirement specification and the software model can be automatically detected, and the software product quality is improved.

This invention relates to systems and methods for real-time dynamic classification and orchestration of test automation components in distributed DevOps environments. The system features an Auto Identify Automation (AIA) engine that leverages supervised learning, Multi-Modal Artificial Intelligence (AI), and Generative AI technologies. It includes a Smart Scenario Designer interface that allows users to author test scenarios using handwriting and voice inputs, which are processed in real-time by AI-driven handwriting recognition, voice recognition, and Natural Language Processing (NLP). The system dynamically suggests relevant automated components via a smart bubble pane, facilitating rapid scenario creation. The architecture is tool-agnostic and scalable, with a Shared Workbench Engine that supports real-time collaboration and conflict resolution. The system continuously adapts and improves, ensuring that the automation suite remains consistent, up-to-date, and aligned with evolving software requirements, enabling efficient and user-friendly management of complex test automation processes.

The invention relates to the technical field of software engineering and information processing, in particular to a semantic verification method and device based on a large model.The method comprises the steps that a source code file and a corresponding software requirement and design document are obtained, code semantic representation is generated based on grammar analysis and static program analysis, and a semantic verification result is obtained; based on text analysis and business flow chart structure identification, generating a design demand semantic representation; respectively inputting the code semantic representation and the design demand semantic representation into a pre-training language large model to generate a code implementation logic description and a design demand logic description; and performing semantic consistency verification on the two types of logic descriptions to obtain a semantic inconsistency result, determining a code position in the source code file based on the semantic inconsistency result, and outputting a scanning report. According to the invention, the automation degree and the rechecking performance of consistency checking of requirements can be improved, and the leak detection and reworking cost can be reduced.

The invention discloses an embedded system integration test case multiplexing method and system, and the method is characterized in that the multiplexing of a test case is carried out based on the existing software assets: firstly, based on the existing software requirements and the test case, an existing requirement-test case tracking chain is constructed; performing demand change analysis on the new demand activity graph information; performing change influence range analysis based on a change analysis result in combination with a demand-test case tracking chain, and determining a test case reuse and generation scheme; and finally, executing the test case multiplexing and generating scheme. According to the method, the tracking relation between existing requirements and test case assets is established, meanwhile, the execution cost of downstream test tasks caused by requirement change is reduced through multiplexing, and the test efficiency of integration testing is improved.

The invention discloses a multi-agent system for knowledge-driven automatic software architecture design, and belongs to the technical field of computer aided design, and the multi-agent system comprises an analysis agent, a modeling agent, a design agent and an evaluation agent which are constructed based on a large language model, the analysis agent is used for extracting, screening and classifying requirements which influence the software architecture design from a software requirement specification and generating a requirement document; the modeling agent is used for generating a software architecture view according to a demand document and an external knowledge base; the design agent is used for generating a software architecture document according to the demand document and the software architecture view; and the evaluation agent is used for evaluating and analyzing the software architecture according to the demand document, the software architecture view and the software architecture document to generate an evaluation and analysis report. According to the method, through cooperation and interaction between the intelligent agents and prompt of external knowledge, the reliability, practicability and creativity of software architecture design can be effectively enhanced.

The invention discloses an intelligent and automatic test case generation method based on a large language model, and relates to the technical field of large language model application, and the method comprises the following steps: collecting a software demand description file and an interface standardization file of a project, carrying out semantic analysis and mapping, generating a logic constraint set, and establishing a path mapping table; inputting the path mapping table into a large language model, generating a test scene and assertion, and executing semantic drift detection; when semantic drift is detected, a drift report is generated, a reverse correction process is executed, a patch prompt is generated, and the generation chain is executed again; and after the semantic distance of the prompt chain is detected to reach a convergence state, outputting a stable test case set. According to the method, the generation structure is controlled through the deterministic prompt sequence, so that the stability and controllability of test scene and assertion generation are realized; and through semantic drift detection and a reverse correction mechanism, real-time correction of semantic offset of the prompt chain is realized, and the accuracy and stability of the test case are improved.

Embodiments of the present disclosure relate to applications, platforms, architecture, etc. for automating software requirement verification. In particular, one or more generative language model (GLM) prompts may be generated based at least on program information that describes a software program and based on requirement information that corresponds to a requirement of the software program. Based on such prompts, the GLM may be able to automatically identify segments of the software program information that relate to the requirement. Further, based on the identified segments and the GLM prompts, the GLM may be able to automatically create (e.g., based on one or more additional prompts) testing architecture that may be used to verify whether the software program satisfies the requirement.

The invention provides an automobile software demand document collaborative correction method and system, which are used in the field of software development, and the method comprises the following steps: receiving a demand document input by a user, carrying out grammar detection on the demand document through a semantic analysis engine, and integrating a rule engine and a large language model in the semantic analysis engine; and according to a grammar detection result, marking various grammar errors existing in the demand document through marks of different vision, and synchronously triggering AI automatic correction. Through the scheme, the software requirement document writing and checking efficiency can be improved, and the automobile software development cost can be reduced.

The invention relates to the field of software requirement modeling, and discloses a software requirement modeling method and system based on an artificial intelligence large model.The method comprises the following software requirement modeling steps that firstly, functional structure modeling is conducted, and then functional module modeling is conducted; for each last-stage function module obtained after checking and revising the function structure, function module modeling is carried out one by one according to the following steps: step 1, data structure modeling; step 2, system function modeling; 3, modeling a user interface; through the method, natural language processing and knowledge reasoning capabilities of the artificial intelligence large model can be integrated in a software demand modeling process, collaborative modeling of the artificial intelligence large model and people is realized, intelligent modeling is realized, and the efficiency and quality of software demand modeling are remarkably improved.

The invention discloses an intelligent demand analysis and man-hour evaluation method and system, and belongs to the technical field of computer vision and artificial intelligence. Analyzing the multi-modal demand document containing the text, the picture and the table to generate structured demand data; based on the structured demand data and the system module description, performing module-level splitting on the demand to generate a module task set; retrieving an associated system implementation context for each task in the module task set based on a multi-dimensional knowledge base; fusing the structured demand data, the module task set and the system implementation context to generate a fine-grained technical task; based on a historical case index, calculating reference working hours for the fine-grained technical task; and cross-module cooperative correction and personalized correction based on the ability of the task executor are sequentially performed on the reference working hours to obtain final evaluation working hours, so that automatic deep analysis and accurate and personalized working hour evaluation of software requirements can be realized.

The embodiment of the invention provides an automobile software demand formal conversion and test case generation method and system, electronic equipment and a storage medium, seven core field grammar frameworks including an application range, a trigger condition, a test object, an operation to be executed, a time sequence constraint, a demand type and a generation rule are constructed, time sequence constraints clearly quantify time parameters, demand types cover external input and the like, and a rule is generated to define mapping logic of demands and use cases; the method comprises the following steps: constructing a formalized conversion engine based on AI, automatically converting a natural language demand into a core field through text cleaning, domain model element extraction, element-field incidence matrix mapping and grammar and domain suitability verification, and if verification is not passed, generating a repair suggestion by the AI and performing iterative adjustment; and building a field enhancement cue word containing module test logic, safety standards and the like based on the core field, and inputting a large model subjected to automobile electronic corpus fine adjustment to generate a stepwise use case.

The invention discloses a software demand analysis method based on a knowledge graph, which comprises the following steps of: importing a multi-source demand text to generate a locatable demand text fragment; loading a domain demand ontology, an SHACL / OWL rule template, a term library, a synonym list and a unit and dimension specification library; generating a candidate entity set, a candidate relation set and a candidate triple set, and attaching an evidence fragment; mapping from the relation type to the clause cluster is established, and an OGG-TM model is initialized; outputting a confirmation triple set and a revised candidate entity set; synonymous normalization, unit specification and threshold specification, cross-document entity merging and identifier mapping; reasoning and consistency verification are carried out; and generating a version identifier, and executing limited incremental learning. According to the method, the knowledge graph and the OGG-TM model are fused, demand semantic analysis and self-learning closed loop are achieved, and high precision and traceability are achieved.

The invention discloses a construction method and device of an index data chain, a storage medium and an electronic device, and relates to the technical field of smart home, and the construction method of the index data chain comprises the following steps: determining a plurality of hierarchical demands in a software demand management system; configuring a unique identification code for each hierarchical demand in the plurality of hierarchical demands; based on the plurality of unique identification codes, constructing an index data chain among the plurality of hierarchical demands, the index data chain comprising demand nodes respectively corresponding to the plurality of hierarchical demands, embedding a unique identification code of a first hierarchical demand corresponding to a first demand node in a second demand node corresponding to the first demand node, the first demand node and the second demand node are any two adjacent demand nodes in the index data chain. By adopting the technical scheme, the problem that dynamic association among multi-level requirements cannot be realized in the related technology is solved.

The invention relates to an automatic construction method of a software demand database, which comprises the following steps of: S1, constructing a software demand model expressed by an entity registration book, and generating a demand design document; step S2, processing the demand design document in the step S1; and S3, automatically generating database contents based on the demand design document processed in the step S2. Compared with the prior art, the method has the advantages that the software requirements are standardized and structured, the standardization and accuracy of requirement writing are improved, the database content is automatically generated, and the software research and development efficiency is improved.

The invention provides an embedded software automatic testing method and system based on a model, and relates to the technical field of embedded software testing. The method comprises the steps of obtaining a software demand design project, obtaining a software interface design project, constructing a software test model, automatically decomposing the test model, automatically generating test data, automatically generating a test script, automatically performing test execution and automatically generating a test document. The system comprises a software requirement design engineering analysis module, a software interface design engineering analysis module, a software test model generation module, a test model automatic decomposition module, a test data automatic generation module, a test script automatic generation module, a test execution module and a test document generation module. According to the method, demand design, interface design and a software test platform are integrated together, resources are shared, integrated management of software design and software test is achieved, and the efficiency and quality of software test demand analysis are improved.

The application discloses a kind of deviation degree evaluation method and system between software requirement and code development, it is related to software engineering analysis technical field, including: the chapter title in software requirement specification, table and list item content are matched with functional requirement, according to the matching result, to the corresponding text content, extract the subject and action of function and the object and condition of action, and get requirement function point sentence according to set sentence pattern rule assembly;After extracting syntax unit and function call relationship from code generation, it is matched with the word in the preset code feature library, and the code function point sentence is obtained;According to requirement function point sentence and code function point sentence, calculate deviation degree, combined with preset deviation threshold, obtain evaluation result.Through the difference between code and expected requirement target, objectively evaluate code development deviation degree, solve the problems, such as inefficient collaboration, quality out of control and requirement disconnection, existing in large-scale code development.

The application discloses a kind of software evaluation method, device, equipment and storage medium, and specifically discloses: receiving the software requirement document uploaded by user, and the software requirement document is parsed, and target analysis data is extracted;Target analysis data includes function item description, data element type and file reference type;Based on function item description and interface image associated with function item description, a multi-modal fusion analysis technique is used to classify the function items, resulting in a classification result;The function items are checked for duplicates, resulting in a first inspection result, and the data element types and file reference types are checked for form, resulting in a second inspection result;Form checking includes illegal character checking and character duplication checking;According to the classification result, the first inspection result and the second inspection result, a function point analysis table is generated, and a software evaluation report is generated based on the function point analysis table.

The application discloses a software design and development method and a terminal, a detailed design document corresponding to an architecture design document is generated according to software requirements, a corresponding core class code is generated according to a core class diagram of the detailed design document, and an engineering code is obtained by directly developing based on the core class code by a developer; if the engineering code does not match the core class in the detailed design document, the core class diagram and the corresponding design document are re-generated, thereby greatly improving the consistency of software design and software development; if the engineering code matches the core class of the detailed design document, the engineering code is submitted to a code warehouse, the submitted document is ensured to be correct and reliable, and the design document is ensured to be well landed in the development stage.

The invention discloses a software source code security verification method and system of a rail transit trackside subsystem, computing equipment and a computer readable storage medium. The method comprises the following steps: S1, based on a software demand security verification report, extracting a tracking relationship between security demands and software demands, and automatically generating a security demand-software demand tracking table lt; sSRgt, SSRgt; ; s2, based on an SCADE model annotation file in the software source code, a function annotation block and a walking reading result of the software source code, extracting a tracking relation between the software requirement and the software source code, and automatically generating a software requirement-software source code verification table lt; an SRCodegt (SRCodegt ; s3, splicing a table lt by taking a software demand ID field as a key; sSRgt, SSRgt; and a table lt; an SRCodegt (SRCodegt A comprehensive verification conclusion field is added in the spliced table, and a software source code security verification table lt is obtained; swSCSVR < gt > is carried out; ; the comprehensive verification conclusion field is used for storing a final conclusion generated by a software security engineer according to a code walk-by-read result.

The invention discloses a software engineering implementation method, and the method comprises the steps: business modeling: anchoring a demand source, and converting a business demand into a landing model; the software requirement specification specification is used for solidifying a requirement standard and forming a specification document based on the business modeling result; summary design: constructing a technical framework, joining demands and development, and macroscopically planning a system architecture; the framework is converted into an executable scheme, and coverage integration, implementation and development are achieved. According to the software engineering implementation process, a standardized'business modeling driving type 'specification is taken as a core, a five-level process model and a data model are used for constructing a business architecture core framework, full-link connection of'business demand-data logic-IT design-landing implementation' is broken through by means of a structured view, and complex processes / functions are deconstructed and split into micro-service interface-level granularity, micro-service interface-level granularity, micro-service interface-level granularity and micro-service interface-level granularity. Accurate correspondence and decoupling of the service component and the IT component are achieved, and finally efficient landing of the service architecture in the IT architecture is guaranteed.

The application provides a kind of embedded software requirement security verification method by means of failure data, which includes: establishing software requirement model, formalizing model description of software requirement, carrying out the patternization processing of failure data, explicitly failure data mode information, establishing the mapping relationship between software requirement model and failure data, carrying out the security verification of software requirement model, obtaining software requirement security verification result, the elements of the software requirement model include function input interface, function output interface and function processing process.The application is driven by failure data and security verification rules, and focuses on the key information that can easily cause engine control software to run failure, which can significantly improve work efficiency and quality, and ensure that potential failure modes and system hazards in software requirements are fully identified.

The invention discloses a software demand quality evaluation data processing method and device, equipment and a medium, and the method comprises the steps: obtaining an initial software demand text, and recognizing a candidate demand text containing a predefined defect indication word through semantic analysis; for each candidate text, matching or generating a high-quality demand text corresponding to semantics from a historical demand library or a domain knowledge library, and constructing a difference sample pair; and labeling the sample pair input into the arbitration system based on the large language model, and automatically generating a quality label corresponding to the demand text. And generating a high-quality evaluation data set based on all the labeled difference sample pairs. According to the technical scheme, automation of data set construction can be achieved, the structural design can effectively reveal context ambiguity of the demand text, and a reliable reference is provided for training and evaluating a high-precision demand quality detection model. The method can be widely applied to the technical field of software.

The invention belongs to the technical field of embedded software testing, and relates to a generator controller software verification method for airworthiness standards. The method comprises the following steps: performing software review and analysis; constructing a layered test environment; designing a test case and a test procedure, and performing review; performing test ready review; executing software testing in the layered testing environment; performing software demand coverage analysis for ensuring that a bidirectional traceability relationship exists between the test case and the software demand; software structure coverage analysis in the aspects of statement coverage, judgment coverage, MC / DC coverage, data coupling and control coupling is carried out; and establishing bidirectional tracing data between the test cases and the software requirements, between the test regulations and the test cases and between the test results and the test regulations, and performing test result review to form a software verification result. According to the method, the airworthiness standard process is quantified, the depth, efficiency and compliance of airborne software verification are remarkably improved through a layered test environment and an intelligent algorithm, and high safety is effectively guaranteed.

The invention relates to an interpretable software test demand generation and evaluation method, belongs to the technical field of software testing, and solves the problems that the generation process is non-traceable and the generation quality is poor in the generation process of the existing software test demand. The method comprises the following steps: acquiring a software demand description document, compiling logic based on a preset test demand, decomposing the software demand description document into a plurality of functional units, and generating identification information of a corresponding test subitem for each functional unit; based on the software demand description corresponding to each functional unit, obtaining a test type of each test subitem; based on the test type of each test subitem and the corresponding software demand description, obtaining a test description of each test subitem; based on the identification information of each test subitem and the test description, obtaining a test demand of each test subitem; and performing quality evaluation on the test demand of each test subitem, and optimizing the test demand of each test subitem based on an evaluation result to obtain a software test demand.

The invention discloses a software demand tracking and management method based on a demand chain, which comprises the following steps: carrying out standardized expression and entry disassembly on demands in an original demand book to obtain demand entries, and adding demand identifiers to the demand entries to obtain standardized demand baselines; establishing a demand change tracking relation among the software case model, the analysis model, the implementation model and the deployment model according to the standardized demand baseline, and constructing a demand tracking chain and a demand tracking matrix according to the demand change tracking relation; according to a preset change demand source, carrying out change influence propagation path analysis based on the demand tracking chain and the demand tracking matrix, and constructing a change influence tree; and according to the change influence tree and the demand tracking chain, demand change work is carried out according to demand change control requirements on demand entries related to the change, and a new demand tracking chain is obtained. The method is simple and easy to implement, wide in application range and fine in demand management process, the development period of software can be effectively shortened, and the development efficiency of the software is improved.

A method (600) is proposed. Method (600) includes obtaining (610) an engineering plan and a chiplet layout hardware model. Method (600) further includes estimating (630) a microsystem hardware model based on hardware requirements and a hardware dataset describing the hardware resources of the chiplet layout, and simulating (640) the estimated microsystem hardware model by electronic simulation to provide one or more hardware capabilities. Method (600) further includes obtaining (650) a chiplet layout environment model, and estimating (660) a microsystem software model using hardware capabilities and software requirements. Method (600) further includes simulating (670) the estimated microsystem software model on the chiplet layout environment model to provide one or more software capabilities, and compiling (680) the estimated microsystem hardware model, the estimated microsystem software model, one or more hardware capabilities, and one or more software capabilities into a microsystem model including one or more microsystem capabilities.

The invention relates to a software demand uncertainty identification and quantitative evaluation method, which comprises the following steps of: reversely deducing a precondition required for realizing on the basis of one or more candidate realizable schemes aiming at a target software demand to obtain a precondition set; according to the precondition set, implicit hypotheses which are not given in an explicit mode but are established by default during implementation are extracted from target software requirements, all the implicit hypotheses are marked as necessary hypotheses, replaceable hypotheses or risk hypotheses, and an implicit hypothesis set is formed; under the same group of implementation constraint conditions, performing logic consistency judgment on any two implicit hypotheses in the implicit hypothesis set; and when at least one pair of implicit hypotheses cannot be simultaneously established, judging that the target software demand has structural uncertainty caused by implicit hypothesis conflicts, and generating an uncertainty quantitative evaluation result based on the number and the type of the conflicting implicit hypotheses and the preset weight of the associated constraint term thereof.

The invention discloses an LLM-based system-level demand modeling and analysis method and platform, and belongs to the field of demand engineering and system modeling. The invention provides an LLM (Logical Language Model)-driven automatic demand behavior model construction and conflict detection method aiming at the problem that accurate modeling and consistency verification of natural language system-level software demands are difficult. According to the method, control flow logic in a demand text is recursively analyzed by simulating an expert stratified analysis process, and a behavior model is automatically generated. The modeling process comprises the steps of recognizing atomic activities, extracting a hierarchical relation and constructing a behavior model. On the basis, a system-level behavior tree is constructed based on preposition and postposition conditions of behavior nodes, a plurality of demand models are comprehensively analyzed, and behavior consistency analysis and conflict detection on the system level are achieved. According to the method, automatic expansion from the demand-level behavior model to the system-level behavior model can be realized, and an effective technical scheme is provided for automatic modeling and analysis of system-level demands.

The invention belongs to the technical field of computer software engineering, and relates to a software demand intelligent analysis and prediction method and system, and the method comprises the following steps: obtaining a user operation log of target software, and constructing dynamic task chain data reflecting the actual process of a user based on a continuous operation sequence in the user operation log; associating a behavior pattern recorded in the dynamic task chain data with a feedback text submitted by a user, performing cross validation on the feedback text, and generating a credibility score representing the authenticity of the feedback text; the potential demand value is evaluated by combining high-credibility feedback and dynamic task chain data screened out through credibility scoring; performing constraint optimization according to preset development resource evaluation data to obtain a function combination after constraint optimization; according to the method, the problem that when the reference software and the target software have a large difference in function positioning or user groups, the built function model can generate dislocation, and large deviation occurs in analysis of user behaviors is solved.