293 results about "Test strategy" patented technology

The invention discloses a test case determination method and device, a computer readable storage medium and a processor. The method comprises the following steps: identifying a source code of software by utilizing a pre-trained large model to obtain a plurality of functional modules in the software and a dependency relationship among the plurality of functional modules; in response to updating of the source code of the software, determining a code updating part in the source code; determining a test case matched with the code updating part from a test case library of the software based on the code updating part and a dependency relationship among the plurality of functional modules, the test case being used for testing the code updating part; based on a test result of the test case, adjusting a selection strategy of the test case; and re-determining the test case for testing the code updating part based on the adjusted selection strategy of the test case. The technical problem that a traditional regression test strategy is low in test efficiency is solved.

The invention discloses a software test result analysis system which comprises a multi-source test data acquisition module, an intelligent anomaly detection engine, a cross-project association analysis module, a visual decision support terminal and a self-adaptive feedback optimization module. The multi-source test data acquisition module integrates heterogeneous test tool data and performs standardization processing; the intelligent anomaly detection engine realizes dynamic anomaly detection by using an LSTM model and a reinforcement learning algorithm; the cross-project association analysis module completes cross-project data association by means of code tracking, a knowledge graph and the like; the visual decision support terminal visually displays an analysis result in the form of a three-dimensional thermodynamic diagram and the like; and the adaptive feedback optimization module forms closed-loop control and dynamically adjusts a test strategy. The system effectively solves the problems that according to a traditional method, multi-source data cannot be fused, anomaly detection is not sensitive, and visual analysis is lacked, efficient analysis of software test results and optimization of the test process are achieved through cooperative work of all the modules, and the test efficiency and the software quality are remarkably improved.

The invention relates to an efficient test optimization method, system and device for chip test equipment, and the method comprises the steps: obtaining the equipment state data and test management information of the chip test equipment, carrying out the test unit division of the equipment state data based on the test management information, and obtaining the regional test information; acquiring real-time operation data of the chip test equipment, and performing matching analysis on the real-time operation data and the regional test information to obtain a real-time test task group; acquiring chip performance data acquired by the chip test equipment, performing load prediction on the regional test information to obtain a test load trend, and performing resource planning analysis with a real-time test task group to obtain an initial test scheme; performing exception identification on the chip performance data to obtain chip exception information; and performing global optimization on the initial test scheme according to the priority test sequence to obtain a global test strategy. According to the invention, fine management of different test tasks can be realized.

The invention discloses a server component durability test system, method and device, a medium and a product, and relates to the technical field of computer hardware testing and reliability engineering.The server component durability test system comprises an intelligent control center used for sending an environment parameter control instruction to a test environment construction module, a load time sequence graph is sent to a load simulation module, so that the test environment construction module generates a composite test environment based on the environment parameter control instruction, and the load simulation module applies a network flow load and a calculation task load based on the load time sequence graph; and the data monitoring and analysis module generates a degradation evaluation result of the target server component through the collected data, so that the intelligent control center adjusts a test strategy based on the degradation evaluation result. Visibly, by adopting the technical scheme, the cooperative scheduling precision of the network flow load and the calculation task load can be improved, the test strategy can be dynamically adjusted, and the accuracy of the durability test of the server component is effectively improved.

The invention discloses an intelligent terminal function test method and system, and belongs to the technical field of intelligent terminal function test. The method comprises the steps that a dynamic demand tracking mechanism is constructed, UI elements are analyzed, and a topological graph marking resource occupation types and hierarchical dependence is generated; establishing a demand-use case-defect incidence matrix to realize automatic update of the use case state when the demand is changed; executing a test based on the topological graph and the matrix, traversing a path according to a preset strategy, collecting data and comparing an expected result; and optimizing iteration according to a test result, adjusting a node weight and a matrix mapping relation, and generating a new test path and a use case suggestion. The system comprises a dynamic demand tracking module, an incidence matrix management module, a test execution module, an optimization iteration module and a data storage module. According to the method, the test range is accurately adapted to the demand change, the test coverage and the defect tracing efficiency are improved, a test strategy closed-loop optimization mechanism is formed, and the test requirements of a complex system and an agile development mode are met.

Methods, systems, and apparatus, including medium-encoded computer program products for executing a test strategy, include: receiving a request to generate a test script for a new test strategy defined for a software solution, wherein the received request includes a specification of the new test strategy; generating the test script based on executing a large language model that receives as input the specification of the new test strategy, wherein the large language model is trained to automatically generate test scripts based on technical documentation for a testing framework defined for the software solution and integration tests generated for the software solution; and executing the test script for the new test strategy to obtain output data, the output data including performance data for the software solution.

The invention relates to the technical field of DC / DC power supplies, and discloses a DC / DC power supply function parameter testing method and system and computer equipment, and the method comprises the steps: injecting a preset disturbance signal into an input end of a tested DC / DC power supply through a signal conditioning circuit, and obtaining output voltage response data and output current response data; adopting a dynamic multi-parameter test system and collecting target test parameter data; calculating a characteristic parameter set, and executing voltage-temperature control model predictive control analysis to obtain a control parameter sequence; and controlling the power output value of the electric heating wire, the rotating speed value of the heat dissipation fan and the position value of the electric push rod in the test box body to obtain an intelligent adjustment test environment and generate an aging test result and a test strategy adjustment instruction, thereby overcoming the problem of parameter detection blind areas in a traditional test method, and improving the test accuracy even under the condition that the output voltage is accurately matched with the set value. And the power supply performance abnormity can be effectively identified, and the reliability and accuracy of the test are obviously improved.

The invention relates to the technical field of encoder operation and maintenance management, in particular to an absolute value encoder operation error analysis method and system, which are used for more accurately identifying whether a specific source causing an error is an internal equipment problem or an external environment factor through environment external cause influence exclusion analysis; the method is applied to an encoder operation monitoring system, an error analysis instruction is generated when the encoder operation monitoring system monitors that an absolute value encoder has an error, and the method comprises the following steps: in response to the error analysis instruction, analyzing the error analysis instruction to obtain an error analysis result; obtaining an absolute value encoder address, an absolute value encoder model and an error analysis time window which need to be subjected to error analysis; configuring an error analysis test strategy based on the absolute value encoder model and the absolute value encoder address; and testing in the error analysis time window based on the error analysis test strategy, and comprehensively evaluating a test result to obtain a first error test result.

The invention, which relates to the technical field of equipment simulation testing, discloses a simulation evaluation method for automatic testing equipment of an in-vehicle infotainment system, and the method comprises the steps: collecting operation test data, carrying out the recognition processing through a deep convolutional neural network model, obtaining test task data, constructing a test action sequence, mapping the test action sequence into a control instruction, and carrying out the simulation evaluation of the in-vehicle infotainment system. The control instruction is optimized and adjusted according to a preset action rule base; driving the in-vehicle automatic test equipment to execute the control instruction to complete the test operation, recording the operation response time and interface state change data in the test process, calculating a movement track deviation value, calculating a test accuracy score, and when the test accuracy score is smaller than a preset threshold value, starting the in-vehicle automatic test equipment; and if not, supplementing the optimization parameters to the preset action rule base and triggering a new test. According to the invention, accurate control of the test equipment is realized by adopting the TCP / IP communication protocol, and the test strategy is continuously optimized by dynamically updating the preset action rule base, so that the automatic test efficiency of the vehicle machine is improved.

The invention discloses a server test system and method, electronic equipment and a storage medium, and relates to the technical field of data processing. Multi-level information of power-on self-test codes, test data and optical signals is collected for a server; meanwhile, the starting-up process of the server is divided into different starting-up stages according to the code stream, namely the starting-up self-test code, and the server is tested through different test strategies in the different starting-up stages; according to the method, multi-level state sensing and optical intelligent detection are carried out in combination with multi-level information, the coverage degree of server testing is improved, and meanwhile, the server testing efficiency is improved through testing of multiple starting-up stages of a full-automatic process and automatic analysis of testing data. Therefore, the technical problem of how to improve the test efficiency and the coverage degree of the server test can be solved, and the technical effect of improving the test efficiency and the coverage degree of the server test is achieved.

The invention relates to the technical field of network security, and discloses a multi-agent cooperative RESTful API vulnerability test method. Constructing a parameter structured representation by analyzing an API interface specification, generating a test value conforming to service semantics by using a large language model, and establishing a semantic request baseline representing normal service logic; constructing a multi-agent collaborative architecture including vulnerability reasoning, case generation, test execution, test analysis and test management; all the agents are coordinated to carry out iterative vulnerability testing through a signal mechanism and a state transition table, and API service analysis, test strategy customization, use case directional variation and execution, result study and judgment and strategy optimization are achieved; and finally generating a structured vulnerability report. According to the method, the problems of semantic blind areas, shallow analysis layers, insufficient adaptive capacity and the like are solved, security risks such as business logic vulnerabilities and sensitive data leakage in the RESTful API can be deeply detected, and the accuracy and coverage rate of vulnerability detection are remarkably improved.

The invention relates to the technical field of optical communication, and discloses an optical module adaptive test and rapid convergence method based on reinforcement learning, which can dynamically generate and execute an optimal test sequence for optical modules of different types or states through an off-line trained RL intelligent agent module, avoids redundant steps in a fixed process, and improves the test efficiency. On the premise of ensuring the test coverage, the test time is obviously shortened, and meanwhile, the detection probability of potential defects is improved; through the closed-loop test of the integrated RL intelligent agent module, the test action can be adjusted in real time according to the state of a single optical module, so that the test process can quickly adapt to the individual difference and process fluctuation of the device, the online quick convergence of the test strategy is realized, and the accuracy and stability of the test are guaranteed; and through online iterative optimization of the RL agent module, new data and new changes in the production process can be continuously learned, so that a test strategy is continuously evolved, and the optimal performance is kept for a long time.

The invention discloses an AI-based software compatibility test system and method, and belongs to the field of software testing, and the method specifically comprises the steps: collecting historical test data, market demands and product update information, predicting compatibility test demands by using a machine learning algorithm, automatically distributing and scheduling test tasks, monitoring a test environment in real time, and automatically configuring the test environment; different use scenes are simulated, when an automatic test script is executed, the progress is monitored in real time, abnormity is processed, and the system generates a detailed test report by learning a test rule, positioning a compatibility problem, adjusting a test strategy and optimizing product configuration, so that the test efficiency and accuracy are improved, and intelligent management of the test process is realized.

The invention relates to the technical field of vehicle software testing, and discloses a vehicle unit test code generation method and device, equipment, a medium and a product. The method comprises the steps of obtaining a tested code; the tested code and the intention prompt word are input into a large language model to be analyzed, a test intention is generated through the large language model, and the test intention is used for indicating the process needed for testing the tested code; inputting the test intention, the tested code and the template cue word into a large language model for analysis so as to generate a test strategy through the large language model, and recommending a code template and a parameter value required by the test from a template library; and integrating the recommended code templates according to the test strategy, and filling the parameter values into the code templates to obtain test codes. The AI illusion is reduced, and the accuracy of generating the test code is improved.

The invention relates to the field of network equipment test, discloses a test method and a test management system for intelligent PON gateway test, and solves the problems of insufficient test coverage, difficulty in equipment compatibility verification, low test efficiency, inaccurate test result analysis and the like in the existing intelligent PON gateway test process. High-quality and high-efficiency testing of the intelligent PON gateway is realized by establishing a testing historical database, dynamically generating a testing strategy, intelligently scheduling testing resources, accurately calculating a testing balance index and pointedly solving the problem of testing imbalance.

The invention relates to the technical field of railway traffic control and software quality detection, in particular to a railway signal safety system function performance testing method which comprises the following steps: S1, knowledge extraction: extracting multivariate entities and semantic relationships thereof from text data related to railway signal safety to form a triple set; s2, constructing and optimizing a graph, constructing a heterogeneous knowledge graph, and optimizing the heterogeneous knowledge graph through a graph neural network and an embedded learning method; s3, constructing an intelligent dialogue mechanism; s4, strategy generation and grade evaluation; s5, task scheduling and execution; s6, test data analysis; and S7, result generation and write-back. According to the method, knowledge graph construction, natural language understanding, man-machine collaborative interaction, automatic test strategy generation and graph self-evolution updating technologies are comprehensively applied, and the verification efficiency and result credibility of the special software for the railway signal safety system in the aspects of function integrity and performance stability are effectively improved.

The invention discloses a stability control strategy test system and method applied to a field stability control device, and the system comprises a test host which is configured to be in communication connection with a stability control host of a stability control master station; the at least one test slave computer is connected with the test host computer and is deployed in a distributed manner to simulate a stability control substation; and the software control system is connected with the test host and is used for analyzing the strategy file, extracting strategy logic from the strategy file, decomposing test steps into a multi-state test template, generating strategy test items, executing the strategy test items according to a preset sequence and dynamically modifying a soft pressing plate and a control word of the stability control host through an MMS protocol. Through distributed communication control of the test host and the test slave, comprehensive simulation of an interface of the field stability control device is realized, and comprehensive test of the field stability control device is realized by simulating all communication signals of the stability control device, reading and identifying a stability control strategy and producing batch stability control test strategy test items. And a new technical means is provided for on-site stability control device testing.

The invention belongs to the technical field of automobile testing, and particularly discloses a digital twinning-based automobile instrument testing method, which comprises the following steps of: automatically generating a structured test case through a large language model, constructing a double-digital twinning architecture by relying on a high-fidelity rendering engine and a real-time simulation engine, and realizing synchronization of a virtual model and a physical instrument; multi-modal data are collected through a multi-sensor array, and defect intelligent analysis and grade judgment are completed in combination with a large language model; and test strategy self-optimization is realized through reinforcement learning based on historical test data. According to the invention, a double-engine architecture in which a high-fidelity rendering engine and a real-time simulation engine cooperatively work is adopted, and the requirements of large-scale scene and refined rendering are met at the same time. And seamless switching and data fusion between the double engines are realized through the scene transformation matrix, so that the consistency of a virtual environment and a physical entity is ensured. Meanwhile, a large language model is introduced into a test case generation and result analysis link, and natural language understanding level test script generation and anomaly analysis are achieved.

The invention discloses an automatic testing method and system for credential equipment, and relates to the technical field of credential equipment test.The method comprises the steps that testing requirements input by a user are analyzed through a natural language interface, key parameters are extracted, historical cases are retrieved, and a structured testing requirement table is generated; based on the structured test demand table, constructing a multi-objective optimization model, and outputting a test strategy matrix after iterative updating by using an NSGA-III algorithm improved by chaotic mapping; performing feature extraction and anomaly detection on the test logs, and identifying anomaly features through a dynamic threshold model; constructing a fault propagation graph model based on the abnormal features, positioning a root cause node by applying an improved causal reasoning algorithm, and generating a strategy iteration scheme; the improved NSGA-III algorithm initializes a population and dynamic target space adaptation mechanism through chaotic mapping, so that the Pareto front coverage rate is improved, and meanwhile, in combination with a resource weight allocation formula of an aging-time decay factor, collaborative optimization of the test cost and the extreme scene coverage rate is achieved.

The invention discloses a power industry software supply chain risk management method and system, a medium and a processor. The method comprises the following steps: acquiring code data of a power information system and a supply chain attack feature library; extracting text features of the data, and generating a code feature vector sequence; performing clustering analysis on the code feature vectors to generate a target feature measurement set oriented to different stages; on the basis of constructing a multi-stage dynamic weight correlation model, calculating a weighted correlation coefficient between the target feature measurement and a preset attack stage, and judging the affiliation of the attack stage; analyzing target feature measurement based on a heterogeneous knowledge graph and a graph attention network, and identifying a potential attack technique type; a self-adaptive attack vector is generated through an attack simulation engine driven by reinforcement learning, response data in the attack simulation process are collected, and a test strategy is dynamically optimized. According to the method, correlation coefficients are calculated for different attack stages, feature measurement of each stage is considered, and the accuracy of attack stage attribution judgment is improved.

The invention provides an automatic management interaction method, system and device of a whole vehicle software version and a medium, and relates to the technical field of vehicle software engineering.According to the method, functions of version monitoring, change analysis, test management and version management are provided through an integrated main interface, and a user can check the software version state and tasks to be done in real time; and performing multi-dimensional version comparison and risk assessment to generate a detailed change and risk report. In addition, the method supports configuration of a test strategy, execution of an automatic test and generation of a test report and a defect positioning list, and the test efficiency and accuracy are effectively improved. And in the aspect of version management, the whole process operation from creation to release is realized, the timeline and historical report of the whole life cycle can be displayed, and the transparency and traceability of version control are ensured. On the whole, the method effectively improves the efficiency and reliability of whole vehicle software version management, simplifies the operation process, and enables the version control to be more efficient, more accurate and easier to manage.

The invention relates to the technical field of software testing, and discloses an agent-based multi-dimensional test sample automatic generation method and system.The agent-based multi-dimensional test sample automatic generation method comprises the steps that code changes are captured, interface definitions are extracted, and multi-source data are fused for consistency verification; constructing a multi-dimensional dependency graph and analyzing the change influence to obtain an associated interface list; generating a multi-dimensional test scene; performing parameter traceability and consistency derivation, and initializing test data and environment to obtain a complete test data set; generating a use case code, and performing hierarchical optimization and executable verification; test arrangement optimization and automatic execution are carried out, and faults are monitored and diagnosed in real time; carrying out multi-dimensional analysis and defect identification, dynamically evaluating the value of a test case and optimizing a test strategy to obtain a comprehensive test report; according to the invention, full-process automation of test case generation is realized, the test efficiency and quality are improved, and the test maintenance cost is reduced.

A data processing system implements after determining that a test in a target branch of a code repository starts failing, receiving a pull request (PR) onto the target branch and blocking the PR (invoking a build policy and a test policy); after determining that the failing test in the target branch is disabled, tracking the disabled test in a disabled test file; in response to a request to requeue the test policy, determining whether artifact in the build policy is identical with artifact in the test policy; when not identical, fetching all versions of the file within a time period, generating a union content of all versions of the file, and applying the requeued test policy using the union content, the time period being between a start time of the build policy and a start time of the requeued test policy; and unblocking the PR.

The invention provides a storage equipment testing method and device and electronic equipment, and can be applied to the technical field of computers. The method comprises the steps that an initial test script is executed, target configuration parameters and target test strategies of the storage device are obtained, the initial test script comprises a diagnosis script and a test strategy matching script, the target configuration parameters are obtained by executing the diagnosis script, and the test strategy matching script is used for selecting the target test strategies based on the target configuration parameters; according to the target configuration parameters and the expected use duration of the equipment, a target test period is determined, and the target test period is a test period obtained after an initial test period in the initial test script is compressed; and obtaining a test evaluation report by using test execution information obtained by testing the storage device based on the target test period and the target test strategy.

The invention relates to the field of interface testing, and particularly provides a cross-type interface testing method and system based on a console, a terminal and a medium, and the method comprises the steps: packaging a bottom layer function of an operating system through a dynamic link library; interface configuration information is analyzed from the interface registration request, and a unique ID is allocated to an interface and registered to a console; receiving an interface test request, selecting an execution mode according to a test strategy identifier carried in the test request, if the execution mode is a single-interface test, directly calling a target interface and introducing a test parameter to carry out an interface test, and if the execution mode is scripted, analyzing an interface calling sequence and a logic control rule in a test script to carry out the interface test; calling a corresponding adapter according to the interface type in the testing process; and generating a structured test report for display. According to the method, a lightweight and high-expansion cross-type interface test scheme is realized, and the test coverage rate and efficiency are improved through dynamic interface adaptation, scripted process control and visual result analysis.

The invention discloses an MQTT protocol fuzzy testing method and system based on a large language model guiding sequence generative adversarial network, relates to the field of fuzzy testing, effectively combines the advantages of the large language model and the sequence generative adversarial network, and analyzes basic training data by introducing an intelligent analysis technology of the large language model. And the quality of the training sample of the sequence generative adversarial network is obviously improved. According to the method, the initial seeds can be enriched through the large language model, the discriminator can be assisted to perform multi-dimensional evaluation on the data generated by the generator, and the authenticity and diversity of the test seeds are enhanced. The generation of redundant test cases is greatly reduced, so that the fuzzy test process is more efficient. Meanwhile, a seed elimination technology based on an energy value is designed, it is further ensured that the tested seeds have higher quality, and the efficiency of vulnerability discovery is effectively improved. Meanwhile, according to the maximum coverage length, the test strategy is dynamically adjusted, continuous optimization of the test process is achieved, and a solid guarantee is provided for the test. According to the method, multi-level variation is carried out on the test seeds by utilizing a large language model, vulnerability information existing in the test seeds is quickly positioned, and meanwhile, multi-dimensional and deeper mutation is carried out on the test seeds, so that more existing vulnerability information is explored, namely, the multi-level mutation is carried out on the test seeds; the test seeds which successfully cause the vulnerabilities are verified and optimized by means of the response of the test target, the success and failure positions are summarized, and a more reliable guarantee is provided for subsequent variation.

The invention discloses a tool and model testing method based on TTS, and belongs to the technical field of intelligent terminal testing. According to the method, the TTS technology is combined with natural language generation, environment simulation and a self-adaptive algorithm, a test text set containing sentence pattern variants and synonym replacement is generated through a natural language generation model, a parameter-adjustable TTS engine is used for synthesizing voice signals with acoustic and emotional characteristics, the voice signals and an environment impulse response function are subjected to convolution superposition of scene noise and then input into a terminal, and the voice signals are converted into voice signals with the acoustic and emotional characteristics. Mapping to a semantic vector space to calculate similarity, and finally generating an iterative test strategy according to the confusion matrix. According to the scheme, test text automatic generation, complex environment simulation and test strategy adaptive optimization are realized, the test efficiency and coverage are improved, the problem is accurately positioned, the multi-scene adaptability is enhanced, and a full-process intelligent test scheme is formed.

The invention discloses a resource allocation method and device for a server, and relates to the technical field of cloud computing resource scheduling, and the method comprises the steps: building a cloud computing basic environment, and carrying out the enhanced deployment of the cloud computing basic environment, so as to build a cloud computing enhanced environment; and secondly, algorithm verification and full-link verification enhancement operation are performed on the cloud computing enhanced environment to dynamically deploy server resources of the cloud computing environment, so that the technical problems of low software testing efficiency, high time cost and labor cost, large error and low precision due to excessive dependence on manual intervention in related technologies are solved, and the method and the device for testing the server resources of the cloud computing environment are provided for the server resources of the cloud computing environment. The technical effects that the anomaly discovery time and the fault average repair time are greatly shortened by utilizing the AI prediction model, the limitation of a single tool in a high-concurrency complex scene is solved by adopting a labor division collaborative test strategy of step pressure and behavior simulation, and the resource utilization rate and the anomaly detection coverage rate are improved are achieved.

The invention discloses an equipment pressure testing method, equipment, a storage medium and a program product, and relates to the technical field of pressure testing, and the method comprises the steps: constructing pressure testing strategies of a first system and a second system in to-be-tested equipment, and executing corresponding pressure testing operation; collecting first test data of the first system and second test data of the second system, and extracting first feature data of the first test data and second feature data of the second test data; generating a target feature based on the first feature data and the second feature data; and generating a diagnosis result based on the target feature by using a diagnosis model constructed based on an expert system and a machine learning model, and generating a diagnosis report based on the target report template. According to the method, the pressure test data of each operating system can be collected, the features are extracted and fused, the model fusing the expert system and machine learning is used for correlation analysis and automatic diagnosis, automatic and accurate positioning of the performance bottleneck is realized, and the diagnosis comprehensiveness and accuracy are improved.

The invention relates to the technical field of computer storage, and discloses a test strategy for improving the read-write performance stability of an SSD (Solid State Disk), and the strategy comprises the following steps: obtaining the current available capacity of an SLC cache of the SSD; based on the obtained current available capacity, setting a total data volume used by a performance stability test, so that the total data volume is smaller than the current available capacity; and executing the performance stability test on the solid state disk by adopting the set total data volume so as to obtain performance data capable of reflecting the hardware stability of the solid state disk. The real-time available capacity of the SLC cache is obtained through the standard interface before the test, and the test data volume is set by taking the real-time available capacity as the rigid basis. By means of the method, precise stripping and evaluation of the performance stability of the solid state disk hardware are achieved, and the test result can truly reflect performance fluctuation caused by hardware components such as a master control or flash memory particles.