98 results about "Function point" patented technology

The embodiment of the invention provides a test case sample cutting method, device and system and a storage medium, and relates to the technical field of network security testing. The method comprises the following steps: constructing an industrial control system attack tactical library; wherein the tactical library comprises classified and arranged attack techniques and corresponding security attributes; performing information analysis and semantic analysis on the test case sample to generate structured data of the test case sample and / or function points in the test case sample; and cutting the test case sample according to the security attribute and / or the structured data and / or the function point to obtain a test fragment corresponding to the security attribute and / or the function point. According to the method, classification-based attack techniques and security attributes are cut by constructing a tactical library, key information can be accurately extracted and test intentions can be understood through information analysis and semantic analysis, redundant tests are avoided, cut test fragments can concentrate on specific security attributes or function points, the test coverage range is more accurate, and the test efficiency is improved. And the distributed security test effect is improved.

The invention provides a communication protocol consistency test method and system. Key function points are extracted by analyzing a target protocol document; based on the key function points, a predefined first prompt template is applied to generate a test case prompt, a large language model is guided to generate a standardized test case corresponding to each key function point, and the first prompt template comprises k few-sample examples; dynamically retrieving a related code context from a pre-constructed long-term memory library through a retrieval enhancement generation mechanism, generating a code generation prompt by applying a predefined second prompt template based on the standardized test case and the related code context, and generating an executable test code based on the code generation prompt; and performing iterative optimization on the executable test code through the large language model, and generating a new code generation prompt based on a code execution result of the previous iteration and the retrieved related code context in each iteration. The test case can be automatically generated and dynamically adapted, and the test coverage rate, efficiency and flexibility are improved.

The embodiment of the invention discloses an evaluation model training method. According to the method, a standard operation program text is disassembled into function points, then each function point is realized in a code mode and in a mode of calling a large model, the two realization modes are tested by utilizing test data, and applicability indexes of the two realization modes to the function points are determined based on test results. And utilizing the applicability index data to train an evaluation model which can quantitatively judge whether the function point is suitable for being realized by using a code or a large model according to the description of the function point. The evaluation model training device and the data processing method and device provided by the embodiment of the specification also have the above beneficial effects.

The invention relates to the field of data processing, and provides a software cost method and system based on dynamic configuration and hierarchical analysis. The method comprises the following steps: dynamically loading corresponding configuration parameters and algorithms by evaluating a method identification field; constructing a standardized cost parameter configuration system, including configuring an estimated function point reference value, an estimated function point weight coefficient and a scale adjustment factor; based on the evaluation method, a tree budget configuration table is preset, hierarchical node design is adopted, a budget tree is constructed, and a tree budget configuration and cost declaration / evaluation header is formed; transferring the configuration right of the tree budget configuration and the cost declaration / evaluation header to the back end, so that the back end dynamically loads a preset header template according to the enabled cost standard, and synchronously injects field attribute rules and calculation formula metadata; obtaining an unstructured document uploaded by a user, and analyzing the unstructured document and the header template by adopting a large language model to obtain software cost details; and generating an evaluation report through the expert review software cost details.

The invention discloses an FPGA test case automatic generation system and method based on a large language model. The system comprises a demand input module, a demand structuring module, a large language model case generation module, a case confirmation module, a verification execution module and a closed-loop optimization module. The large language model can automatically analyze the unstructured demand document and extract key information such as function points, input and output, boundary conditions and the like, and manual one-by-one interpretation is not needed. A big language model is guided through Prompt Engineering to dismantle complex requirements into test key points which cannot be subdivided, and it is ensured that all logic branches are covered by tests. The large language model can dynamically generate diversified test cases based on test key points, including a normal process, an abnormal process and an edge scene. And in combination with FPGA design specifications, historical error cases and other plug-in knowledge bases, the large language model can generate test cases closer to actual hardware behaviors.

The embodiment of the invention provides a resource optimization method and system based on function point measurement software scale evaluation, and belongs to the technical field of software measurement. The method comprises the steps of selecting an evaluation mode based on current demand scene information, if the current demand scene information is matched with a historical scene, calling a precipitated function point evaluation baseline and generating a baseline value through consistency verification and increment measurement adjustment, and if the current demand scene information is not matched with the historical scene, entering a function point identification process and generating a function point identification result; determining a function point scale based on the baseline value or the function point identification result and outputting a corresponding workload result; based on the function point scale and the workload result, generating evaluation data for resource allocation in combination with historical scheduling data and a resource allocation relationship; and outputting a resource allocation suggestion based on the evaluation data. According to the scheme, the accuracy of software scale evaluation is improved, and executable resource allocation suggestions are generated.

The invention discloses a business demand processing method, device and equipment based on RPA and an intelligent agent, and relates to the technical field of computers, and the method comprises the steps: disassembling a target business demand based on business demand data, and obtaining a plurality of demand function points with a first execution sequence, the plurality of demand function points comprise a first function point corresponding to a rule fixed task and a second function point corresponding to a rule change task; determining an RPA component matched with the first function point and an intelligent agent component matched with the second function point; and according to the first execution sequence, calling the RPA component to execute the corresponding rule fixed task, and calling the agent component to execute the corresponding rule change task, thereby obtaining a processing result of the target business demand. According to the method, the RPA and the intelligent agent are combined for business demand processing, so that repeated work with fixed rules can be solved, scenes with changeable rules and needing flexible processing can be coped with, and the execution success rate and the execution efficiency can be improved.

The invention provides a model-based defect detection method and related equipment. According to the invention, the code semantic understanding information and the code dependency association relationship of the code are determined through the code of the first application program, and the function point associated with the demand can be obtained through the business demand information corresponding to the first application program; matching the function points with nodes of a function tree of the first application program based on a first model to obtain a first matching relationship between the function points and the nodes of the function tree, a second matching relation between the function point and the code of the first application program is determined in combination with page information of the node of the function tree, interface calling information and the code dependency association relation, and the accurate corresponding relation between the natural language requirement and specific code implementation is achieved; and code defect detection can be carried out on the basis of the second matching relationship in combination with code semantic understanding information, so that detection of defects such as incomplete function implementation and business logic errors in codes of the first application program is realized.

The invention discloses a test sequence optimization method and device, equipment and a storage medium. Comprising the steps of obtaining function point related data, and generating a function point test sequence based on an upper confidence bound algorithm; defining a global resource occupancy matrix, and according to the function point test sequence, sequentially importing the function points, traversing and querying the global resource occupancy matrix, and generating a parallel scheduling task; and executing the parallel scheduling task, and monitoring resource conflict conditions and test failure information in real time. By comprehensively considering related data of the function points, intelligent sorting of the function points is achieved, and the problems that in a traditional sorting method, exploration and utilization are difficult to balance and global dynamic optimization is lacked are solved. By reasonably distributing parallel tasks, resource conflicts are avoided, the utilization rate of limited test resources is improved, and efficiency reduction caused by unreasonable resource planning is reduced. Resource conflicts are found and processed in time through real-time monitoring, the conflicts are prevented from influencing the test process, test failures can be quickly responded, and the test efficiency is improved.

The invention discloses a test script generation method, system and equipment based on a large model and a medium, belongs to the technical field of software testing and artificial intelligence, and aims to solve the technical problems of how to automatically generate high-quality and high-coverage test scripts, improve the generation efficiency and quality of the test scripts and reduce the test cost. According to the technical scheme, the method comprises the steps that a test case is prepared, specifically, product functions are refined into specific function points or test points according to function point carding and demand analysis results, the detailed test case is designed, and a serial number is compiled for the test case; analyzing the test case: analyzing the test case through the large model; the analysis result is obtained through langchain and executed step by step, and DOM tree information is analyzed before execution of each step; and generating a test script: operating the browser by langchain to return to the DOM tree, and generating an actually effective test script according to the control information of the DOM tree.

The invention provides an IT system construction workload evaluation method and system, a medium and equipment, and belongs to the technical field of computer software, and the method comprises the steps: receiving IT system construction project information, and carrying out the analysis and decomposition to form function points; calculating an estimated workload by adopting a workload quantification model, and storing the estimated workload; according to the actual workload consumption condition, the workload data are adjusted and verified, and an actual workload summary sheet is generated; counting experts of corresponding technical field knowledge to form an expert database; and carrying out random extraction to form a review group, reviewing the adjusted workload, generating a review opinion, and confirming the review opinion to form final workload data. According to the method, the workload is split according to the function points for pre-estimation, filling and summarizing are performed according to the actual workload generated in the actual development process, then an expert performs review, and unified confirmation / complaint is performed; the workload management work is visualized, transparent, standardized and normalized, and the project settlement efficiency is improved.

The application provides a dead loop processing method and device, electronic equipment and storage medium, a preset script function is run, and the number of instructions executed when the preset script function is run is monitored; if the number of instructions is greater than a preset number threshold, a function call stack when the preset script function executes instructions is acquired and recorded; the number of times that the function call stack is recorded within a preset time period is determined, if the number of times recorded satisfies a preset condition, the function call stack is determined as a dead loop stack; the dead loop stack is interrupted to remove the current dead loop. Through monitoring the number of instruction executions and the number of times that the function call stack is recorded, the method can realize fault positioning to the function point level, greatly shortening the dead loop positioning time; meanwhile, after the existence of a dead loop problem is found, the method automatically removes the dead loop, improving the server dead loop troubleshooting efficiency.

The invention provides a research and development cost evaluation method, device and equipment. The method comprises the following steps: determining an initial function point scale of a to-be-evaluated software project; obtaining an updated function point scale according to the demand change coefficient corresponding to the software project and the initial function point scale of the software project; the demand change coefficient is used for calibrating the influence of software demand change on the software scale; determining a function point unit price of the software project and an adjustment factor of software project research and development cost; and determining the research and development cost of the software project according to the updated function point scale, the function point unit price of the software project and the adjustment factor of the research and development cost of the software project. The method provided by the embodiment of the invention effectively improves the accuracy of the project research and development cost estimation result.

The invention relates to a software function point identification method fusing a large model and multiple clustering analysis, and solves the problems of subjective deviation, inconsistent naming and low auditing efficiency caused by function disassembly depending on artificial experience in traditional function point measurement and calculation. The method comprises the following steps: inputting a design scheme, and constructing a document level semantic tree; obtaining feature information described by corresponding function points in the semantic tree, and analyzing the feature information to determine candidate function points; fusing the candidate function points according to semantic tree hierarchy alignment; and carrying out differentiation processing on the candidate function points, and carrying out duplicate removal on the similarity frequency according to the candidate function points to obtain the function points. According to the method, based on construction and analysis of a document hierarchy semantic tree, feature positions and large model reasoning ability are combined, and accurate extraction and auditing of function points are achieved. And differentiation is formed by adopting multiple clustering, and a co-cooperation relation matrix is constructed through clustering cross validation, so that the function point de-duplication accuracy is greatly improved.

This application provides a functional verification method applicable to the fields of artificial intelligence or big data technology. The method includes: acquiring a preset knowledge graph, the knowledge graph including markers indicating differences between functional points in a first system and functional points in a second system, the differences including difference types; acquiring first system test cases corresponding to the differences; based on the difference types, executing a corresponding test case generation strategy on the first system test cases to obtain second system test cases; calculating the functional coverage of the second system with respect to the first system; and, if the functional coverage is greater than a preset coverage threshold, performing regression testing verification based on the second system test cases. This application also provides a functional verification device, equipment, storage medium, and program product.

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 kind of virtualization system upgrade test method, device and medium, it is related to virtual machine field.The application includes: obtaining the configuration information of virtualization system;According to upgrade influence function point, create virtual machine;After upgrade, the basic function and upgrade influence function of virtual machine are verified.Compared with the previous upgrade test of all architecture deployed in virtualization platform, only the basic function and upgrade influence function of virtual machine are verified in the method of the application after upgrade, in the case of guaranteeing the key function after upgrade, greatly reduce the workload of upgrade test, improve the efficiency of test;In addition, compared with the upgrade verification in the environment of empty load, virtual machine is created according to upgrade influence function point in the method of the application before upgrade, more close to simulate real upgrade test scene;According to upgrade influence function point, virtual machine is created to realize targetedly, avoid blindly creating virtual machine and ensure the creation of core parameters.

The invention discloses a database offline evaluation method, device and equipment, a medium and a product. The method comprises the following steps: in response to a database offline evaluation request, determining a grammar file used for describing grammar for data to be transferred out of a database, and determining a to-be-evaluated database file and a preset tag configuration file; constructing an abstract syntax tree and a traversal device according to the syntax file, the database file and a preset tag configuration file, and traversing the abstract syntax tree by adopting the traversal device to determine a target function point contained in the database file; and for each target function point contained in the database file, performing a function execution operation or a rewriting operation, and recording a compatibility condition of the target function point to generate an offline evaluation report. According to the technical scheme, the preset tag configuration file independent of the evaluation tool is used for describing the related information of the function points, the adaptation degree of the evaluation scheme can be improved, and efficient and accurate database offline evaluation is achieved.

The invention relates to a method and a device for integrating multi-version demand documents and computer equipment, and relates to the technical field of computers, and the method in one embodiment comprises the following steps: obtaining multi-version demand documents of a target system, and sorting the multi-version demand documents based on the latest update time of the demand documents to obtain a demand document sequence; structural analysis is conducted on the demand documents of all the versions, the content of the demand documents is disassembled into structural knowledge units, and each knowledge unit comprises an independent function point and corresponding attribute information; determining knowledge units describing the same function point in the demand document of each version, and associating the knowledge units describing the same function point in the demand document of each version based on the demand document sequence to form a knowledge unit change chain; and generating an integrated demand document based on the knowledge unit change chain of each function point. By adopting the scheme of the embodiment, the management efficiency of multi-version demand documents is improved.

The invention provides a software effectiveness measurement method and device, equipment and a storage medium, and belongs to the technical field of software development. The method comprises the following steps: processing data generated in a software research and development process into efficiency measurement data; identifying a data function and an interaction function of a reconstruction system associated with the demand of the software according to the efficiency measurement data; analyzing the data function and the interaction function to obtain the number of required function points, and determining the contribution proportion of the data function to the required function points according to the total number of newly added and transformed fields required for realizing the data function; determining the contribution proportion of the interaction function to the required function points according to the number of logic processing units for realizing the interaction function; calculating an efficiency evaluation index value changing along with the function point number according to the required function point number; and generating an efficiency measurement result of the software based on the efficiency evaluation index value. According to the method, more accurate software effectiveness measurement is realized.

The invention relates to the technical field of customized software identification, and particularly discloses a customized software function point identification and diagnosis system based on a big data technology, which comprises a total data acquisition module, an intelligent data preprocessing module, a function feature extraction module and a dynamic weight adaptive identification module, an abnormal mode diagnosis module and a decision support and optimization suggestion module; through an online element learning algorithm in the dynamic weight adaptive recognition module, the system can quickly update weight parameters based on a very small number of fault samples, large-scale off-line training is not needed, and high recognition performance can be kept in a new project or new version scene. The few-sample rapid adaptation capability effectively solves the generalization bottleneck of a traditional model in the face of frequent iteration and scene diversity, and the model deployment and optimization period is remarkably shortened.

The invention relates to a mobile application rapid development system based on a low-code platform. The system is divided into a middle platform layer, an engine layer, a design layer and a service layer. The middle platform layer provides universal capability support, the engine layer encapsulates core compiling and rendering logic, the design layer provides a visual interaction interface, and the business layer bears a specific application scene; the front end and the rear end are separated, the rear end takes a function point as atomic particle packaging service logic, the front end takes a view as a unit to organize an operation flow, and communication is realized through RESTful API; splitting system functions into independent services by adopting a micro-service architecture; component libraries are abstracted for the PC terminal and the mobile terminal, and function multiplexing is achieved through modular design; and finally, the system performance is improved through distributed cache optimization. The rapid efficiency and reliability of the mobile application are effectively improved.

The application discloses an AI auxiliary-based plug-in automatic generation method and device, which comprises the following steps: receiving a natural language plug-in function requirement input by a user; performing deep semantic understanding and intention recognition on the requirement by using a large language model, and analyzing the requirement into a structured plug-in specification, including a function point list, a data structure definition, an interface calling plan and a plug-in function type; selecting an adaptive template from a preset template library according to the plug-in function type, and automatically constructing a plug-in basic engineering skeleton; calling an AI model to generate a business logic code containing an API calling placeholder on the skeleton; referring to a main system API definition document, automatically generating adaptive code and replacing the placeholder, and forming a complete code engineering; automatically packaging and deploying the engineering to a sandbox test environment, generating simulation data based on the data structure to perform automatic testing and capture errors; and after the testing, automatically registering the plug-in to a main system plug-in market or a plug-in library, so that the automatic generation and release of the plug-in are realized.

This application provides an automatic cost assessment method, system, medium, and product for petrochemical software projects, relating to the field of artificial intelligence technology. In this method, the cost assessment system utilizes a large language model to perform preliminary function point identification on project documents and retrieves the names of the preliminarily identified function points using a petrochemical industry knowledge base, supplementing it with professional information such as scale and complexity from historical projects. Then, the cost assessment system iteratively corrects the function point information through interaction between the retrieved information and the preliminary function point list. Finally, the cost assessment system determines the complexity level of each function point, calculates the adjusted number of function points based on the project complexity, and then calculates various cost information and generates an assessment report based on the adjusted number of function points and a project parameter library. This method combines the preliminary identification using a large language model with professional information from an industry knowledge base, improving the accuracy of function point identification through iterative correction, thereby enhancing the reliability of cost assessment.

According to the low-code platform component and function point coverage rate measurement method and device, the storage medium and the computer equipment provided by the invention, when it is detected that a new test task is triggered, the component function point list generated during current code deployment in a low-code platform is obtained, and the pre-developed automatic test case is obtained; in the process of executing the automatic test case, marking the state of the verified function point in the component function point list as a covered state; and after the test is completed, according to the coverage state of each function point of each component in the component function point list, counting the overall component coverage rate and the single component coverage rate. According to the process, the component function point list is generated and the function point coverage state is dynamically marked, so that the component-level test coverage rate is accurately quantified, and the problem that the visual component is difficult to identify by a coverage rate tool in a low-code scene is effectively solved.

The invention discloses a method for automatically generating a front-end item package.json, and belongs to the technical field of front-end development. The method is implemented by the following steps of: entering a question and answer page, inputting basic information of an item, and obtaining basic package.json configuration; inputting a required basic component library, and obtaining basic component library dependency package configuration; inputting function points contained in the item, and obtaining function component dependency package configuration; the method comprises the following steps of: adding dependency configuration into an existing package.json; the method comprises the following steps of: acquiring a package.json file; and placing the obtained package.json file in a front-end item, and executing a dependency package installation command. According to the method, the user input can be accurately understood and analyzed, so that intelligent recommendation of the dependency package required by the front-end project is realized, and more efficient and accurate development support is provided for front-end developers.

The application provides a chip verification method and device based on test cases, and comprises the following steps: generating a script based on a to-be-verified chip running folder; obtaining at least one target folder by using a pre-constructed test case folder based on the folder generation script and test case keyword input conditions; wherein the test case folder comprises script files of multiple test cases, and the target folder is a function point test case folder related to the test case keyword or a default function point test case folder; and running a simulation command based on the target folder to obtain a test result. According to the application, multiple function point test case folders related to tests can be generated by using a script once, the simulation command is run by making the folder correspond to the function point test case one by one, the creation process of the multiple test case simulation folder is simplified, the cost is low, and the efficiency of simulation is improved.

The invention discloses a software engineering cost function point estimation method based on a large language model, and provides a more intelligent and accurate software function point estimation method by combining the natural language understanding ability of the large language model with the semantic relationship reasoning ability of a knowledge graph. Therefore, the evaluation process of the software engineering cost is optimized; not only can the accuracy of function point identification be greatly improved, but also the deviation of artificial participation can be reduced, and the dynamic change of the system can be reflected in real time; a new technical means is provided for cost estimation and resource allocation of a complex software project, and the efficiency and quality of a software development project are improved.

The invention discloses an MBD model-oriented cross-enterprise collaborative data exchange and interface generation method and system, and belongs to the technical field of computer aided design, and the method comprises the steps: analyzing a source end MBD model, extracting PMI annotation items, and calculating a semantic annotation coverage rate; analyzing a target system API, identifying MBD related function points and calculating an API function coverage rate; calculating a fidelity coefficient based on the double coverage rates and judging an interface generation strategy; constructing a dynamic mapping matrix, calculating an adaptive mapping score of each PMI item and generating an adaptive interface code; and after the interface trial operation, calculating the actual data exchange success rate and comparing the actual data exchange success rate with the fidelity coefficient, and if the deviation exceeds the tolerance, triggering a feedback mechanism to adjust parameters. According to the method, the problems of data loss and interface failure caused by data semantic loss or API (Application Program Interface) function insufficiency in cross-enterprise collaboration are effectively solved, and the fidelity of data exchange and the robustness of interface generation are improved.