126 results about "Function point" patented technology

The invention provides an automatic software testing method and system based on artificial intelligence. The method comprises the following steps: analyzing a software demand document by using an NLP technology, converting the software demand document into structured data, extracting a key function point, and identifying a software function point; generating a test case covering all function points through a deep learning model in combination with historical test data training; automatically executing a test operation, analyzing a test result, analyzing a test log by using a machine learning algorithm, identifying and classifying potential defects by using a data mining and pattern recognition technology, and generating a repair suggestion report; and analyzing feedback data in the test process, dynamically adjusting a strategy according to a test result by using a reinforcement learning algorithm, and optimizing a test case and the strategy. According to the invention, intelligent analysis of test data, automatic generation of test cases and automatic execution of a test process are realized; flexible configuration and expansion can be carried out according to the actual condition of software; the test efficiency and quality are improved, and the test cost and manpower consumption are reduced.

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 relates to a software function point extraction and element identification method and system, equipment and a medium. According to the method, the natural language processing capability of the large language model and the precise classification capability of the text classification model are combined, so that precise extraction and element recognition of function points in the software requirement document can be realized. And by introducing structured text segmentation, an object attribute cleaning strategy, a cue word optimization extraction scheme, a mechanism of secondary supplemental extraction of ILF function points and a correction optimization strategy based on a heuristic rule, the integrity and accuracy of function point extraction and recognition can be remarkably improved, the situation of mistaken extraction or omission is reduced, and the recognition efficiency is improved. And a solid data basis is provided for software scale automatic estimation.

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 provides an improvement method and device for user feedback and a computer readable storage medium. In the scheme, an initial knowledge graph is constructed, and nodes of the initial knowledge graph comprise function points, key problems and improvement suggestions; obtaining user feedback information, analyzing the user feedback information by using a large language model, and updating the initial knowledge graph according to an analysis result to obtain an updated knowledge graph; according to relevant information of the updated knowledge graph, characteristic parameters of a large language model are adjusted, an adjusted large language model is obtained, the adjusted large language model is applied to analysis to obtain improvement suggestions corresponding to user feedback information, and the relevant information comprises a first data pair and a second data pair; the first data pair comprises user feedback information and a function point corresponding to the user feedback information, and the second data pair comprises a key problem associated with the function point and an improvement suggestion corresponding to the key problem. According to the scheme, the problem of relatively low efficiency of user feedback analysis in the prior art is solved.

The invention discloses a method and system for reversely generating a design book through codes driven by a large language model, and relates to the field of software engineering. According to the method, code engineering is analyzed through a grammar analysis technology and a big language model, the incidence relation of visible explicit and implicit codes is mined, and a knowledge graph is formed. And function points are mined from a project by applying heuristic search in combination with a vector clustering technology. And relying on the knowledge graph, a summary design book and a detailed design book are reversely generated for code engineering by utilizing a large language model, so that the technical difficulty of maintenance and migration of a software system is reduced in an auxiliary manner.

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 relates to the technical field of PLC programming language testing in the field of industrial automation control, in particular to an IEC 61131-3-based PLC programming software language function full coverage testing method, which comprises the following steps: establishing a structured test table based on functions of five PLC programming languages; based on the content of the structured test table, a plurality of different function points to be tested are determined, and a test program complete set is determined based on the function points to be tested; the test program complete set is iteratively updated according to a test standard; importing the test program complete set into to-be-tested PLC programming software, and testing grammar analysis, compiling results and runtime behaviors to obtain test data; generating a technical list based on the test data; according to the invention, the test comprehensiveness of the PLC programming language 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 provides a service demand analysis method and device and a computer readable storage medium, and the method comprises the steps: obtaining all dialogue voice data discussed by a service demand, and converting all dialogue voice data into corresponding dialogue text documents; generating a preliminary demand document based on all dialogue text documents; performing information extraction on the preliminary demand document by using a big and small language model according to a set demand template to obtain specific information, and filling the specific information to a position corresponding to the set demand template to obtain a demand document; and performing function point analysis on the demand document by using the big and small language models to generate a function demand specification. The problem that in the prior art, work such as collection and summarization, key point extraction, induction analysis and content checking of massive multi-source heterogeneous original documents consumes a large amount of time cost is solved.

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 method for automatically generating a test case from a product demand document by a knowledge base, which is characterized by comprising a PRD document analysis and function point extraction module, a knowledge base construction and calling module, a test case generation module and a test case generalization module, the PRD document analysis and function point extraction module is used for converting a PRD document into a structured Markdown format by utilizing a large language model; the knowledge base construction and calling module constructs a structured knowledge base by analyzing historical PRD and test case data; the test case generation module generates test cases covering a normal scene, a boundary scene, an abnormal scene and a concurrent scene; and the test case generalization module is used for generating diversified and non-repeated test cases. Compared with the prior art, the method has the advantages that an efficient and comprehensive solution is provided for software testing automation, the method is particularly suitable for function testing, boundary testing, abnormal testing and concurrent testing in the software development process, and the application prospect is good.

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 discloses a data processing method and a related device, and when a to-be-processed task for a target function point is received, if a task queue is empty and the to-be-processed task is matched with a current state, the to-be-processed task is written into the task queue. And if the task queue is not empty and the to-be-processed task is matched with the target state of the target function point after the last task in the task queue is executed, writing the to-be-processed task into the task queue. Finally, the target function point can be called according to the queue sequence to execute the tasks in the task queue, and the queue sequence can be used for indicating the receiving sequence of the tasks in the task queue. Visibly, based on the current state and the condition of the task queue, the to-be-processed tasks which can be correctly executed are screened and written into the task queue, so that the tasks can be correctly executed according to the queue sequence, execution errors are avoided, the queue length is reduced, and the response speed is increased. As the sequence can be adjusted to be a correct sequence, out-of-order calling can be supported, and the logic complexity of a service side is prevented from being increased.

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.

The invention discloses a bipartite graph-based software test range determination method and a related product. According to the scheme, a change file between two version codes and a corresponding change line number are obtained; and determining a change function to which the change line number belongs. Function points corresponding to the change function are determined by calling the link, and the affected frequency of each function point is determined. And constructing a bipartite graph model according to the incidence relation between the change function and the function point. And solving the bipartite graph model to generate a minimum function point set. And sorting the minimum function point set according to the affected frequency, and generating a target test set with a test priority. According to the technical scheme, the code change analysis is combined with the bipartite graph model, the affected frequency is quantified by calling link analysis, and the test priority is sorted according to the affected frequency. And the test efficiency is obviously improved on the premise of ensuring the test sufficiency.

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 application belongs to the technical field of software analysis, and provides a function point extraction processing method and system. The method obtains data sets by collecting requirement analysis texts, software design texts and system design texts available through public channels, and performs function point labeling to establish a knowledge base. According to the established knowledge base, the KMP algorithm is used to perform string matching between the function points in the knowledge base and the texts to be processed, so as to extract the function points contained in the texts to be processed and determine the category labels of the function points. The texts to be processed are input into a pre-constructed automatic extraction model, and the function points contained in the texts to be processed and the categories to which the function points belong are output. The function points extracted based on the knowledge base and the function points extracted using the automatic extraction model are sorted, evaluated and calculated to screen the function points. The application realizes a faster and more effective automatic extraction process of function points, and effectively avoids the problem of missing function points.

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.