62 results about "Software requirements" patented technology

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.

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 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 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 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 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.

Disclosed are various embodiments provisioning a data processing unit in a host machine. There can be multiple data processing units within the host machine with varying hardware or software requirements for an installation image that can be utilized to provision the device. Multiple installation images can be generated for different data processing units having varying requirements in a heterogeneous environment.

The invention relates to a software demand analysis system and method based on a knowledge base and deep learning, and the system comprises a function list generation module which is used for calling a demand analysis knowledge base to retrieve received software function demand information, under the guidance of the first cue word template, a required software function list is generated through a preset large language model, and the software function requirement information represents software functions wanted by the user; the function detail generation module is used for calling a demand analysis knowledge base to retrieve various software functions in the list according to the software function list, and extracting and assembling through a preset large language model under the guidance of a second cue word template to generate software function details; and the function demand generation module is used for generating a function demand specification through a preset large language model under the guidance of the software function details and the third cue word template. Through the method and the device, the problem of how to improve the generation quality of the demand document in the software demand project is solved.

The invention discloses a knowledge collaborative multi-agent-based function demand mining method, and relates to the technical field of software development and artificial intelligence, and the method comprises the following steps: carrying out correlation classification on software demand texts, and screening out function demand texts; constructing a potential demand mining agent, inputting a function demand text for multi-dimensional analysis, and mining by using a large language model to generate candidate function demands; constructing a text knowledge base; comparing the function demand text with a text knowledge base, and retrieving similar demand texts; based on semantic difference detection, recognizing texts with similar demand texts and function demand texts not existing, and recording the texts as candidate function demands; constructing a potential demand integration agent, and integrating the generated candidate function demands into a candidate set; and selecting candidate function requirements in the candidate set, combining the candidate function requirements with the function requirement text, and generating and outputting a final requirement text. And finally, potential function requirements required by software development are efficiently, accurately and automatically mined.

The invention relates to a case elementary flow generation method based on a large language model and an enhanced relational graph attention neural network, belongs to the technical field of software demand engineering, and solves the problems of inaccurate information extraction, poor field adaptability and neglect of demand context in the prior art. The method comprises the specific steps of obtaining a demand text corresponding to a use case; performing semantic core word analysis on the demand text by using a large language model to obtain a core word set and a corresponding relationship between core words; based on the core word and the corresponding relation, utilizing a trained enhanced relation graph attention neural network to carry out context relation perception, and carrying out matching prediction on core word features obtained through perception and features in an action object feature library to obtain an action and object set of a basic flow corresponding to the use case; and on the basis of the sequence of the action and the object set, the elementary stream of the use case is generated, so that the field adaptability and the context information relationship are enhanced, and the extracted elementary stream information is more accurate.

The application discloses an embedded system integration test case reuse method and system, which is essentially based on existing software assets to reuse test cases: firstly, based on existing software requirements and test cases, a tracking chain between the existing requirements and test cases is constructed; next, requirement change analysis is performed on new requirement activity diagram information; based on the change analysis result, combined with the requirement-test case tracking chain, change influence range analysis is performed to establish a test case reuse and generation scheme; finally, the test case reuse and generation scheme is executed. The method not only establishes the tracking relationship of the existing requirements and test case assets, but also reduces the execution cost of the downstream test task caused by the requirement change through reuse, and improves the test efficiency of the integration test.

This invention proposes a knowledge mapping system and analysis method for software reliability requirements, belonging to the field of software reliability requirements analysis. This method constructs a standardized requirements modeling system comprising an external cross-linking interface model, a functional logic model, a functional combination model, and a state scenario model to achieve a formal representation of software requirements. It then decomposes and summarizes individual functional requirements, identifies potential failure modes based on a pre-defined classification and comparison system, and establishes a three-layer mapping system of software functional requirements – failure modes – reliability requirements. This completes the forward derivation and transformation of reliability requirements, outputting standardized analysis results. This invention achieves standardized and traceable processing of software reliability requirements analysis, providing prerequisite input and logical basis for the development of highly reliable software, ensuring system stability and task success.

The invention discloses a software requirement classification method and system based on user feedback, and the method comprises the steps: receiving user feedback text data, preprocessing the data, inputting the preprocessed user feedback text into a RoBERTa model, and learning through a pre-training technology to obtain an initial model; the preprocessed text is input into the initial model, a classification result is obtained through forward propagation of the model, and the classification result comprises a specific category label or a classification probability; the classification result is used as the input of an Adapter, a target classification space is used as the output of the Adapter, and the Adapter is constructed; performing adjustment by adopting an Adapter low-parameter fine adjustment method to obtain a target classification model; and classifying the user feedback by using the target classification model, and outputting a classification result. According to the method and the device, the dependence on the annotation data is reduced, the generalization ability of the model is improved, meanwhile, only the parameters specific to the task are trained, the computing power overhead during training is reduced, and the classification accuracy and efficiency are improved.

The invention belongs to the technical field of electromechanical management, and discloses an MBSE-based electromechanical integrated management system air conditioner control software design method, which comprises the following steps of: 1, analyzing the requirements of benefit-critical people to obtain helicopter air conditioner control related use cases; step 2, according to the obtained use case, developing an activity diagram layer by layer to obtain a function which needs to be realized by the electromechanical integrated management system; step 3, according to the architecture of the electromechanical integrated management system, carrying out lane activity diagram development on functions needing to be realized by the electromechanical integrated management system; 4, docking with an environment control system, and combining the functions obtained in the steps 1-3 to obtain software requirements; 5, building a software model according to the software requirements; 6, performing model testing on the software control model; 7, the MBSE model and the software control model are combined to achieve model in-loop test verification; and 8, generating an air conditioner control software source code. According to the method, the problems of low software development readability and inheritance of a traditional electromechanical integrated management system are solved, and the readability is enhanced and the system is more visual.

A method includes identifying configuration information of a server being deployed, which includes a configuration and software requirements, and the server is managed by a management server through a management controller controlling a host hosting the server. The method includes retrieving a recommended setup of hardware and software for the server based on the configuration information and retrieving, from a deployment tracking module, a recommended deviation. The method includes creating a deployment file based on the recommended setup and deviation, and transmitting the deployment file to the management controller, which uses the deployment file to configure the server. The deployment tracking module monitors firmware, drivers and / or software deployments of servers for problems and software deployments, monitors websites / databases associated with firmware, drivers and / or software deployed on the servers for updates, analyzes information from monitoring the deployments and updates from the websites / databases, and manages recommended deviations from recommended setups.

This invention discloses a method for quantitative analysis and evaluation of software function points based on concept understanding, relating to the fields of software engineering and cost assessment. The method includes the following steps: standardizing and preprocessing the original software requirements document to generate a structured dataset labeled with function point tags; constructing a hierarchical prompting engineering framework based on the structured dataset, performing two-stage function point reasoning using a large language model, and outputting an initial function point list; post-processing the initial function point list, including format validation and semantic disambiguation, to generate a standardized function point list; and evaluating model performance using multi-dimensional quantitative indicators based on the standardized function point list, and dynamically optimizing the prompting engineering framework and model reasoning process based on the evaluation results. This method improves the automation level, consistency, and accuracy of the software function point analysis process through concept-guided intelligent reasoning, quantitative closed-loop evaluation, and standardized post-processing.