125 results about "Regression testing" patented technology

A method is provided for optimizing regression testing in a software development environment. The method includes analyzing source code to create a structural dependency graph that maps dependencies between code elements; identifying changes in the source code between a current version and a previous version; mapping the identified changes onto the structural dependency graph to determine affected code elements; selecting a subset of regression tests based on the affected code elements identified in the dependency graph; and executing the selected subset of regression tests to validate the changes in the source code.

The invention provides a DFT test task management method and device, electronic equipment and a storage medium, and belongs to the technical field of chip design verifier.The DFT test task management method comprises the steps that a data model is constructed on the basis of a design module list and a test step list, the data model is used for indicating testability design DFT test steps of all design modules, and the test steps of all the design modules are stored in the test step list; the data model comprises a plurality of DFT test tasks, attributes of each DFT test task comprise a selection state, and the selection state comprises a selected state and a non-selected state; based on the interactive input, determining at least one DFT test task of which the selection state is selected as an executable DFT regression object; and according to the DFT regression object, driving a DFT test task to be executed. According to the method, the DFT test tasks are normalized through the data model, only the DFT test tasks need to be selected for making the test plan, efficient management of the DFT test tasks is achieved, and the regression test efficiency is improved.

The invention provides a front-end regression test method, a program product, electronic equipment and a storage medium. The method comprises the following steps: acquiring user behavior data of a user in a to-be-tested application program; based on the element positioning information, performing semantic annotation on the user behavior data through a predefined rule and / or a semantic understanding model to obtain semantic information; based on the network request data, grouping the labeled user behavior data, and screening out a test case corresponding to a single page path for a user behavior data group; restoring the test environment to an initial state; determining a target element corresponding to the interactive operation data in the test case by adopting an element positioning algorithm; and in the initial state, executing a corresponding interaction operation based on the target element, and completing test playback. Therefore, the test script has higher adaptability to local change of the front-end page, the large-scale failure risk of the test case caused by the change of the page structure is reduced, and the stability and reliability of the test are enhanced.

In the DevOps process, testing teams use automated testcases to test a product in a regression testing running daily, which generate thousands of log files per run, in various distributed environment with different formats. Solutions to errors depend on SMEs and the impact of solution leads to rework of defect / errors and high degree of heterogeneity. This leads to huge bottleneck in automation of DevOps process leading to loss of productivity and agility. Present disclosure addresses the challenges by providing systems and methods that auto capture the log files of different formats efficiently in a scalable, extendible, and plug-able way. The system then mines and parses the log files based on given identifiers to standardize and de-duplicate to create unique error records with detail description including cause, position, module, timestamp, etc. The system predicts the solutions leveraging the database containing solutions and errors by using a modified Smooth Inverse Frequency technique.

The invention provides an automatic simulation test system and method for a semiconductor EAP system, and belongs to the field of semiconductor manufacturing, and the method specifically comprises the steps: defining a test scene through test case coding; constructing a test environment by using the equipment simulation module and the external system simulation module; driving a test process of the tested EAP program through an automatic execution engine and generating real-time output data corresponding to the tested EAP program; and comparing the real-time output data generated by the automatic execution engine with an expected result, and generating a test report. According to the processing scheme, behaviors of equipment and an external system are truly simulated in a software simulation mode, an actual production scene is accurately restored in a test link, dependence on a physical environment is reduced, and test coverage is improved; and moreover, the test scene is solidified through codes and configuration files, so that the versioning management and one-key automatic regression test of the test cases are realized, the test efficiency is remarkably improved, and the quality of secondary development is guaranteed.

The invention discloses a test system and method for generating capability evaluation based on a large model, and the method comprises the steps: S1, carrying out threat modeling, and generating a test case, including classifying a threat scene and generating an automatic test case, the generation content of the test case including generation of an adversarial sample and generation of a privacy test case; s2, a multi-dimensional test is executed, the multi-dimensional test comprises a dynamic test engine and real-time defense detection, and test indexes of the dynamic test engine comprise a sensitive information leakage rate, a malicious instruction execution rate and a prejudice index; s3, performing vulnerability diagnosis, including analyzing attention weight and tracing privacy leakage; and S4, performing verification and iterative repair, including collecting vulnerability samples, performing mixed training, adjusting a loss function and performing regression testing. Through threat modeling and attack scene classification, various potential attacks can be identified and covered, test comprehensiveness is ensured, neglected potential safety hazards can be found, and test effectiveness is improved.

The invention provides a regression test method and device, a storage medium, electronic equipment and a product. The regression test method comprises the following steps: acquiring credit investigation service data generated by a credit investigation system in a process of executing an actual credit investigation service, the credit investigation service data comprises input request parameters input by the data demander to the credit investigation system, original data returned by the data provider to the credit investigation system, actual output request parameters sent by the credit investigation system to the data provider and actual credit investigation data returned by the credit investigation system to the data demander; after business change is executed on the credit investigation system, inputting the input request parameter into the credit investigation system to obtain an analog output request parameter, and inputting the original data into the credit investigation system to obtain analog credit investigation data; and according to the deviation between the actual output request parameter and the analog output request parameter and the deviation between the actual credit investigation data and the analog credit investigation data, determining whether the credit investigation system successfully completes the business change.

The invention discloses a method and device for recommending a test case, and the method comprises the steps: obtaining a change function for code change in response to the monitored code change of a tested system; determining a to-be-recommended regression test case for testing code change according to the multi-dimensional information, the multi-dimensional information comprises a dependency relationship and a mapping relationship of a change function obtained in advance, function semantic information of the change function, function semantic information of a dependency function, a historical execution record of the regression test case, and any multiple items in importance attributes of the regression test case; the dependency function refers to a function having a dependency relationship with the change function, and the mapping relationship comprises a regression test case and a function which can be tested by the regression test case; and performing regression testing on the tested system according to the to-be-recommended regression test case.

The invention discloses a chip parameter verification method and device, equipment and a storage medium. The chip parameter verification method comprises the steps of sampling a to-be-tested parameter space of a chip to obtain a parameter point file; performing a regression test on the parameter point file to obtain verification test results, and associating each verification test result with the corresponding parameter point to obtain a data pair set; performing parameter point iteration prediction on the set through a model according to the data; and when it is determined that the predicted parameter points meet the optimization target, taking the predicted parameter points as to-be-applied target parameter points of the chip. The parameter point file is obtained by sampling from the to-be-tested parameter space, and the sampling result is used for the regression verification test, so that the number of tasks needing to be executed is reduced, the overall verification investment is reduced, fitting and prediction are carried out through the model according to the verification test result, the coupling effect and hidden defects among parameters are conveniently found, and the verification efficiency is improved. And the accuracy of the determined target parameter is improved.

The application relates to the technical field of regression testing, and discloses an automatic regression testing method and device, computer equipment and a storage medium, wherein a test page in a to-be-tested case is called, a page object corresponding to a page element address in the test page is obtained according to the page element address, a configuration parameter of the page object is obtained, a test mode is determined according to the configuration parameter, the test mode is parsed, an executable script of an operation means is obtained, and feedback data of the operation is determined as a target test report of the to-be-tested case. The application is based on a visual regression testing platform that is established in advance based on a Puppeteer framework to perform automatic testing, the to-be-tested case is subjected to automatic testing through an operation mode and a page element address, and a tester can complete the testing work without needing to master a lot of front-end script writing knowledge, so that the application is easy to operate, the workload and testing cost of the tester are reduced, and the testing efficiency is improved.

The invention provides an automatic external connection regression testing method and device, equipment and a storage medium, and belongs to the field of computer software tests.The method comprises the steps that historical external data are extracted from an external connection database in batches based on an external connection regression testing request input by a client interaction page; converting the historical external data into basic test data according to a preset rule based on test demand information input by the client interaction page; updating the basic test data into test sample data matched with the current interface of the external connection component; calling a logic code of the external connection component based on the JSP, analyzing the test sample data and forwarding the test sample data to the service component; and comparing a business result generated by the service component with an expected result, and generating a test report. Through the method provided by the invention, the limitation of a traditional scheme can be overcome, and the efficiency and quality of external connection regression testing are improved in an automatic testing mode.

A method for improving chatbot accuracy includes receiving an input test file containing chatbot interaction data, the data including utterances, intended intents, and intended responses. For each interaction, a predicted intent and response can be generated using an AI chatbot trained on prior interaction data. The method determines the similarity between the predicted and intended responses / intents by calculating the Levenshtein distance and comparing it to a predetermined threshold. Keywords from failed interactions are extracted through natural language processing to identify failure themes. Machine learning decision tree classification can analyze patterns in failed interactions to generate solution recommendations. The method can generate an interactive dashboard displaying historical performance trends, accuracy metrics for specific domains, visualizations of high-frequency keywords, and confidence distributions for failed interactions. This automated regression testing method can effectively identify and resolve chatbot performance issues while maintaining response quality.

The invention provides a test method and device, electronic equipment and a storage medium. Relates to the technical field of data processing. The method comprises the following steps: receiving a test request sent by a client, wherein the test request is used for requesting to test a data synchronization function; according to the test request, determining at least one to-be-detected index of a data synchronization function, a source database, a target database and a data synchronization mode; for each to-be-detected index in the at least one to-be-detected index, testing the data synchronization function at least once according to the to-be-detected index, the source database, the target database and the data synchronization mode to obtain a test result corresponding to the to-be-detected index; and determining a test result of the data synchronization function according to the test result corresponding to the at least one to-be-detected index. According to the test method provided by the invention, the efficiency of carrying out regression test on the data synchronization function is improved.

The system obtains an issue associated with a network and resolves the issue by suggesting a solution and receiving an approval from an AR / VR device. Based on the issue, the system creates a ticket describing the issue and obtains diagnostic information associated with the issue. Based on the diagnostic information, the system determines a fix for the issue and sends a first notification to the AR / VR device. The first notification includes a description of the issue, the fix for the issue, and a request to test the fix. Upon receiving an approval to test the fix, the system performs regression testing using the fix and determines whether the fix passed the regression testing. Upon determining that the fix passed the regression testing, the system sends a second notification to the AR / VR device requesting an approval to deploy the fix, and upon receiving the approval, the system deploys the fix.

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 invention discloses an acquisition terminal test case priority ranking method based on a fuzzy analytic hierarchy process, which comprises the following steps of: applying the fuzzy analytic hierarchy process to the field of acquisition terminal test, and quantizing fuzzy evaluation opinions of experts by triangular fuzzy through constructing a'target-criterion-scheme 'hierarchical structure; fusing a multi-expert judgment matrix by adopting a weighted geometric averaging method, and optimizing a criterion weight and performing defuzzification in combination with consistency check; and comprehensive priority scores of the test cases are calculated through weighted summation, a sorting sequence from high to low is generated, and meanwhile, dynamic adjustment during demand change is supported. According to the method, the fuzzy demand quantification accuracy can be improved by 60%, the expert dispute rate is reduced to 8% or below, the regression test error detection efficiency is improved by 40%, and the method adapts to the multi-scene test demand of the acquisition terminal.

The embodiment of the invention relates to the technical field of software testing, and discloses a regression testing method, device and equipment based on database comparison and a storage medium, the method comprises the following steps: executing a target test scene based on system software before change, and synchronously obtaining database change information generated by executing the target test scene; the database change information at least comprises database operation statements triggering data change and corresponding data change information; based on the changed system software, executing the same target test scene, and obtaining database change information in the same mode; sequentially comparing the database operation statements and the data change information in the two times of execution, and outputting a difference report according to a comparison result; the difference report is used for reflecting database operation logic and data consistency difference information before and after system software change. By means of the scheme, the problems that at present, test coverage is not comprehensive, data consistency is difficult to guarantee, and effectiveness of test results is limited can be solved.

The invention relates to a regression test method and system for position information release and electronic equipment, and the method comprises the steps: obtaining a plurality of groups of test case data suitable for a target position based on a preset test case data set, the test case data comprising legal user identity data, test data and expected data; performing simulation release of target position information based on the test data of each test case; release response data of multiple dimensions are obtained, and verification is carried out based on the expected data of each test case in each dimension and the release response data; and recording data generated during simulation release of the target position information, release response data of multiple dimensions and verification data, and generating a regression test report for release of the target position information based on the recorded data. According to the invention, the test efficiency is improved, the manual labor amount is reduced, the test accuracy is high, the coverage is wide, and the expandability is high.

The application relates to the technical field of electric inspection, and particularly discloses a real vehicle function safety test system based on fault injection, which comprises a real-time control module, a bus simulation device, a customized fault injection module, a three-way switching device, a vehicle model adaptive connector and an evaluation module. The application realizes the same programmable platform for communication message injection and electrical fault injection, supports joint scenes, does not need to change lines or disassemble and assemble ECUs, one-key restores the original vehicle state and supports fault code clearing, significantly reduces test preparation and recovery time, can guarantee real-time performance, supports complex injection strategies and automatic regression testing, and finally can automatically troubleshoot the bus simulation device according to the operation process.

This invention presents a knowledge evolution poisoning attack method for graph-enhanced retrieval and generation systems, belonging to the field of retrieval enhancement and generation. Through knowledge evolution forgery attacks and multi-target cross-subgraph collaborative attacks, it can generate evolutionary corpora that satisfy temporal constraints and have stronger structural connectivity without compromising the overall consistency of the knowledge graph. This allows for a more thorough exposure of GraphRAG's vulnerabilities in knowledge extraction, community partitioning, subgraph retrieval, and evidence aggregation stages in authorized evaluation environments. Compared to direct splicing injection, the samples generated by this method more closely resemble the "real knowledge update" distribution and can be used for pre-deployment red team evaluation, post-deployment regression testing, and effectiveness verification and parameter selection for defense modules such as consistency detection, retrieval filtering, and fact verification.

The invention provides a high-priority test case screening method and device, a storage medium and computer equipment, and relates to the technical field of computers.The method comprises the steps that a demand document and a test case set are received; preprocessing the demand document, and constructing a cue word based on a preprocessing result; inputting the cue word and the test case set into a large language model to obtain an initial high-priority test case; after text normalization processing is conducted on the initial high-priority test case, a target high-priority test case is obtained through text matching processing, and the target high-priority test case is marked. According to the method, high-priority test cases can be automatically and accurately screened out in a rapid iteration software development environment, the coverage rate and efficiency of regression testing and smoking testing are improved, meanwhile, the correctness of core functions is guaranteed, and the reliability and applicability of case screening results are remarkably enhanced.

The invention discloses a method-level test case sorting method based on change measurement and defect severity prediction, which comprises the following steps of: constructing an abstract syntax tree of each method, and analyzing differences in different software versions; the method comprises the following steps: abstracting a calling relation of a software runtime method into a software network MSN, extracting a network complexity index and a source code level measurement index of each method, constructing a defect severity prediction data set by combining the defect severity in the method, and constructing a defect severity prediction model by using a machine learning classifier to predict the defect severity in the method; and evaluating the test importance of the method based on the change measurement of the method and the predicted value of the defect severity, evaluating the priority of the test cases in combination with the coverage information of the test cases, and executing the test cases according to the priority sequence. According to the method, the change size of the method and the severity of the defect are considered, the method is of great significance in improving the regression test efficiency and improving the software quality, and technical support is provided for developing high-credibility software.

The invention discloses a full-link traffic recording method, which comprises the following steps of: recording a request of each transaction, request information of the transaction, an external dependence response result, abnormal information and execution time consumption through pipeline middleware of Asp.netCore; the external dependency of each transaction is recorded through a dynamic weaving structure provided by Harmony.lib, recording of the external dependency is achieved, and recording content of the external dependency comprises response parameters of the service, an external dependency response result and execution time consumption. Through configuration of recording and comparison rules, multi-dimensional verification and problem positioning are realized, the problems of high invasiveness, incomplete dependence coverage, poor playback matching and low verification efficiency of a traditional test tool are solved, and the method is adaptive to various requirements of interface regression testing, online problem reproduction and the like in a distributed scene.

A method includes determining that software associated with an image capture device has received a software update. The method includes causing the image capture device to capture first one or more images of a testing environment. The method includes determining an image quality of the first one or more captured images. The method includes comparing the image quality of the first one or more captured images with a threshold image quality. The method includes, responsive to the image quality of the first one or more captured images being below the threshold image quality, causing the software update of the software associated with the image capture device to be automatically reverted.

The invention belongs to the technical field of software testing, and discloses a black box testing method, device and equipment for in-vehicle software and a storage medium. The method comprises the following steps: acquiring a to-be-tested vehicle-mounted machine application; comparing the to-be-tested vehicle machine application with a historical vehicle machine application to generate a change method set; a preset method library is inquired according to method items in the change method set, test cases corresponding to the method items are screened out, and the test cases cover the method items during operation; and completing a regression test according to the test case. By means of the mode, under the condition that an executor does not need to carry out white box code analysis, the corresponding regression case is matched for the code change content, and the purposes of accurately classifying the test range and improving the version test efficiency are achieved.

One embodiment provides a method of using a computing device to provide regression testing for RPA including monitoring, by the computing device, an RPA bot while the RPA bot is executing a routine in a web test environment. Based on the monitoring, the computing device generates a simulated environment including all elements of the web test environment that the RPA bot interacts with. The computing device further continuously runs the routine in the simulated environment. Upon detecting a change in the web test environment, the computing device propagates the change to the simulated environment and verifies whether the change breaks the routine.

The application discloses a regression test case set selection method based on requirement association, comprising: association relationship basic library construction: requirement association matrix is constructed for a plurality of test requirements, and test item-requirement association matrix is constructed, mapping relationship of test case to test item is constructed, priority order of test case is set, and test defect-test case association matrix is constructed; regression test case selection model construction: test defect is associated with test case, test case is associated with test item, test item is associated with test requirement, and test requirements with different relationship strengths are selected for association; regression test case set selection: based on the regression test case selection model, test requirement, test case priority and defect library are combined to obtain the best regression test case set. The application is based on multiple factors for selection of the regression test case set, so that the effectiveness of the selection is higher.

What is provided is a computer-implemented method, system, and computer program product for automatically selecting tests for regression testing of a software system using machine learning. This includes generating a test map that includes at least one of a plurality of tests corresponding to source files. The plurality of tests and at least one source file are associated with a software repository. Furthermore, the method involves determining a defect score for the at least one test based on historical test data; receiving a component criticality score and defect definition corresponding to the source file; generating a key value corresponding to the at least one test based on the defect score, component criticality score, and defect definition; determining a subset of the plurality of tests based on the key value corresponding to the at least one test; and executing the test subset in conjunction with the software repository.

The present disclosure provides an automatic error-reporting tracing method and apparatus, a storage medium and an electronic device. The automatic error-reporting tracing method comprises: determining whether a running test case has triggered error reporting; when the test case has triggered error reporting, performing tracing to acquire execution information corresponding to the error reporting; and on the basis of the execution information, performing matching in an error reporting-regression test suggestion database so as to obtain a regression test suggestion. The embodiments of the present disclosure can trace error reporting in vehicle-mounted operating systems, so as to determine the positions of modules where errors have occurred and analyze the errors, and can provide corresponding regression test suggestions for the causes of error reporting. For common errors, automatic regression test scripts are given such that regression tests can be performed automatically.

The application belongs to the technical field of automatic software testing and program analysis, and relates to a precise testing service system based on software code analysis reasoning, which comprises a data acquisition and initial graph construction module, an initial context-aware probability execution graph being constructed in combination with static potential call edges; a syntax change semantic analysis module, a structured syntax disturbance signature being generated; a probability disturbance instruction generation module, conditional probability disturbance instructions and polymorphic distribution disturbance instructions being generated, and a probability disturbance instruction set being aggregated; a graph real-time reconstruction module, a reconstructed probability execution graph being generated; an influence domain propagation analysis module, affected nodes being determined and an affected function set being generated; and a regression test subset generation module, a minimized regression test subset being generated. The application solves the problem that, when a traditional regression test selection method faces context-related program behaviors, the actual runtime influence probability of changes cannot be quantified, resulting in inaccurate test range selection.