196 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 discloses a communication protocol automatic analysis and test data generation method and system, and the method comprises the steps: analyzing an unstructured protocol document, recognizing a fixed field and a variable field in the document, and outputting structured data; automatically generating test data based on the structured data, dynamically calculating a checksum according to a specified check algorithm type in the structured data, and filling the checksum into the original message to form a complete test message; and generating a standardized test data set according to the complete test message. According to the method, manual intervention is not needed from document analysis to test data generation, the analysis efficiency is improved, and most protocol scenes are covered through the boundary value, the abnormal value and the orthogonal combination strategy. The method supports various document formats, data types and verification algorithms, adapts to protocol standards of different industries, facilitates problem positioning and regression testing through standardized output documents, and reduces the maintenance cost.

The invention relates to the technical field of chips, in particular to a chip regression test method based on to-be-tested design configurations, electronic equipment and a medium, and the method comprises the steps: automatically generating a test case corresponding to each to-be-tested design configuration through setting chip regression test starting parameters and pre-constructed test case reconstruction information; recording test case states of a regression test preparation process and an operation process which need to record historical information in a database, and optimizing each to-be-tested design configuration to allocate a corresponding resource configuration based on a user identifier, historical regression test information corresponding to a to-be-tested design identifier and a current machine load; and the chip regression test efficiency and accuracy are 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 discloses a full-link traffic playback test method and system for a financial system, and the method comprises the steps: forwarding network traffic from a production server to a pre-release environment server, and carrying out the preprocessing, and then generating real-time traffic; performing full-link playback on the real-time traffic in the pre-release environment server, generating a playback result, and feeding back the playback result to the test platform to generate monitoring data; and converting the real-time traffic into historical traffic, performing full-link playback, and generating monitoring data. And according to the response state and the monitoring data of the pre-release server, analyzing the defect of version change to generate a daily test report. According to the invention, full-link closed-loop testing is realized, and a full-service system is covered. All-time testing is supported, request sending is flexibly configured, and continuous flow playback during the market opening period is ensured. Through testing flow classification, the flow is forwarded and stored in real time, the environmental difference is solved through preprocessing, and the defect discovery rate is improved. The problems of insufficient full-link regression test means, incomplete scene coverage and low test efficiency in the prior art are solved.

The invention provides a UVM-based instruction set acceleration component verification platform construction method, which comprises the following steps: firstly, generating a required instruction signal according to an input signal of an acceleration component by a verification platform, then generating a floating-point number meeting calculation requirements according to requirements, and meanwhile, ensuring the configurability of various parameters which are random and excited in an effective range of operational data; a C-based soft library is called as a reference model for comparison with a hardware output result, so that the verification accuracy is ensured; then collecting and merging coverage rate files obtained by excitation operation through scripts to realize convergence of the coverage rate and ensure the completeness of verification; and finally, when hardware design finds an error and is modified, a verification platform can be called to carry out a regression test, so that the method has relatively high reusability, and the verification efficiency 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 provides an RPA script minimum increment repairing method based on evolutionary swarm intelligence and reinforcement learning, and relates to the technical field of RPA process automation, and the method comprises the steps: obtaining an event, and generating a rule JSON set; analyzing and mapping condition keys of the rule JSON set, and extracting a decision chain; performing rule coverage vector locking encoding on the decision chain, setting a mutation probability according to a structure influence factor to generate candidate individuals, crossing the individuals with similar structures, and sequentially completing grammar, variable and interface permission verification to obtain an initial patch candidate group with complete coverage; converting the initial patch script into a chain graph, inputting the chain graph into a local-global double-flow enhanced network for script optimization, outputting optimized patch candidates with composite scores, sorting according to the composite scores and the number of node changes, selecting a dominant pedigree to execute controlled micro mutation and block crossing, and obtaining a final patch script meeting a convergence condition; and carrying out full regression test on the final patch script, and after the test is passed, carrying out deployment and archiving a running log.

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.

The invention relates to the technical field of chips, in particular to a code coverage rate processing method, electronic equipment and a medium, and the method comprises the steps: S1, designing a test case in a running regression test based on a to-be-tested chip, and obtaining text information corresponding to each code coverage object; s2, analyzing the attribute information, obtaining chip level information and code coverage rate types corresponding to each code coverage object, analyzing the operation information, and obtaining a regression test sequence number, regression test time and an operation result corresponding to each code coverage object; s3, generating metadata corresponding to each code coverage object, and storing the metadata in a preset script file; s4, analyzing metadata in a preset script file to generate a first database, a second database and a third database; and S5, displaying the form of the code coverage rate. The processing efficiency of the code coverage rate is improved, and resource consumption in the processing process of the code coverage rate is reduced.

Methods, system, and non-transitory processor-readable storage medium for a test selection system are provided herein. An example method includes selecting, by a test selection system, a regression test case from a plurality of regression test cases in a software testing lifecycle system. The test selection system determines a product release weight associated with the regression test case, where the product release weight incorporates new features associated with a product release. The test selection system obtains a regression test case value for the regression test case by applying the product release weight. The test selection system selects the regression test case for use in regression testing for the product release, based on the regression test case value and executes the regression test case on a system.

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.

The present invention discloses an automated classification method for regression test error simulation waveforms based on a Mamba neural network architecture, belonging to the field of integrated circuits. The method comprises parsing a simulation waveform file obtained from a regression test, converting a key signal waveform into a discrete sequence of integer waveforms; normalizing the numerical range of the waveform sequence to the 0-1 interval, intercepting a fixed length and inputting it into a Mamba neural network model, with the network outputting two parameters: block size and block starting position; dividing the waveform using the two characteristic parameters output by the network, calculating the thickness, degree of fluctuation, and mean characteristics of each waveform block, and calculating the overall characteristics; performing a fast Fourier transform on the waveform using integer multiples of the waveform block size as a window, and calculating frequency domain features; and merging the extracted features into a multidimensional feature vector and inputting it into a support vector machine to output a final classification result. The present invention can effectively improve the accuracy of diagnosing the cause of regression test failure, replace the manual triage process, and improve verification efficiency.

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 embodiment of the invention provides a regression test case generation method and device, computer equipment and a storage medium, and belongs to the technical field of artificial intelligence. The method comprises the following steps: acquiring target test demand information; performing function classification on the target test demand information to obtain a target demand function category; screening the historical test demand information according to the target demand function category to obtain selected test demand information; generating test parameters according to the selected test demand information to obtain target test parameters; performing screening processing on preset historical regression test cases according to the selected test demand information to obtain selected regression test cases; and generating a test case based on preset case generation indication information, the target test parameters and the selected regression test case to obtain a target regression test case. The method can be applied to business systems needing a large amount of data, such as financial science and technology and health medical treatment, manpower can be saved, and the use case generation efficiency is improved.

This invention provides a testing method, apparatus, and computer-readable medium for a decision engine. The method includes: first, determining a test case set corresponding to a target decision engine; second, performing regression testing on the target decision engine based on the test case set, generating a first regression test result; the target decision engine is used to indicate the logic of implementing a specific business through a combination of one or more decision nodes; then, determining whether the first regression test result meets preset conditions; finally, if so, adjusting the actual decision engine or the test case set based on the first regression test result, generating an adjustment result. Therefore, all decision nodes of the decision engine can be covered based on the test case set, thereby achieving testing of all decision nodes in the decision engine and reducing the failure rate of the decision engine in a production environment.