344 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 relates to the technical field of software testing, in particular to a self-adaptive software testing environment configuration method and system.The method comprises the steps that before software testing is started, a sensing layer analyzes testing requirements through a prediction model, and a preliminary environment configuration scheme is generated by analyzing codes, configuration, requirement documents and historical data; the containerization and virtualization management module creates a virtual machine and deploys applications according to the scheme, the SDN control module sets network topology and strategies, and the automatic configuration module executes environment establishment; in the testing process, a dynamic monitoring module monitors resource use in real time and feeds back the resource use to a decision-making layer based on a data interaction protocol, a test demand perception prediction model in the decision-making layer generates a resource adjustment strategy and a network optimization strategy based on monitoring data, and a test strategy and a case execution sequence are dynamically adjusted. And the optimization feedback module evaluates the environment configuration effectiveness and transmits the environment configuration effectiveness to the decision-making layer for adjustment. According to the invention, the beneficial technical effect of a more efficient, accurate and reliable software testing process is realized.

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.

The invention relates to the technical field of SOC modular unit testing, and discloses an AI SOC modular unit testing method and device of a set top box, and the method can automatically construct a testing platform simulating a real use environment, generate testing cases covering various scenes, achieve parallel testing and real-time interference compensation, and improve the testing efficiency. And multi-dimensional analysis and cross-batch alignment can be carried out on test data. Meanwhile, the method also has an adaptive optimization capability, and can dynamically adjust a test strategy according to a test result, so as to continuously improve the test efficiency and accuracy.

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 provides a reliability test evaluation method and system for an integrated circuit chip, and relates to the technical field of integrated circuit chip test.The method comprises the steps that a test target and a test index are defined; constructing a multi-level test environment; performing a dynamic stress test in the constructed multi-level test environment; based on the historical test data and the monitoring data, establishing a prediction model by using a machine learning algorithm to predict performance changes and potential faults of the integrated circuit chip under different conditions; performing intelligent diagnosis on faults occurring in the test process by using the established prediction model, and positioning a fault source; and continuously monitoring the test process through the online remote monitoring platform, and dynamically adjusting the test parameters and the test strategy according to the monitoring data and the prediction result of the prediction model. The reliability of the integrated circuit chip is comprehensively and accurately evaluated, and the test efficiency and the fault prevention capability are improved through a multi-level test environment, machine learning prediction and intelligent diagnosis.

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 discloses an automatic test platform based on a financial risk system and a construction method thereof, and relates to the technical field of financial risk management, and the construction method comprises the following steps: compiling a series of automatic test scripts covering core business logic, performance bottleneck points and a security mechanism for the financial risk management system; and when the test script is executed, the running state of the system is monitored in real time, and various data indexes related to the transaction load are obtained. According to the method, the transaction peak value is intelligently predicted by using the machine learning model, the high-concurrency risk is identified in advance, and the test strategy is dynamically adjusted when the load is sharply increased. By means of a traffic mirroring technology, real transaction traffic is copied to a test environment in real time, data volume is dynamically regulated and controlled, business pressure is accurately simulated, a financial risk management system is helped to timely discover and solve the problems of performance bottleneck, resource contention and the like, expandability and safety of the system are improved, and economic losses and compliance risks caused by high concurrency are reduced.

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 technical field of software testing, and provides a GUI testing method and device of an application program, electronic equipment and a storage medium. In the process of running the to-be-tested application program, multiple pieces of GUI state information are collected; for each piece of GUI state information, obtaining each piece of matched target test knowledge from a test knowledge base according to the GUI state information, and generating a corresponding test prompt word in combination with the GUI state information; and generating a test strategy based on the GUI state information and the corresponding test cue word by using the multi-modal large model, and carrying out GUI test on the to-be-tested application program according to the test strategy by using the test tool so as to carry out GUI traversal test on the to-be-tested application program. Related test knowledge is obtained through the test knowledge base and cue words are generated to guide the multi-modal large model to output the test strategy so as to explore more interaction paths to carry out GUI test, so that the test operation is simplified, and the test efficiency and coverage rate are improved.

The invention relates to the field of equipment testing, and discloses an EMC testing method and system for an electronic product, and the method comprises the steps: obtaining product information, obtaining an EMC testing strategy of the product in a cloud data server, and enabling the EMC testing strategy to comprise an EMI testing strategy and an EMS testing strategy; the method comprises the following steps of: obtaining products to be tested from produced products according to a set proportion, dividing the products to be tested into an EMI test group and an electromagnetic sensitivity test group, carrying out electromagnetic emission test on the electromagnetic emission test group, carrying out electromagnetic sensitivity test on the electromagnetic sensitivity test group, and according to an electromagnetic sensitivity qualification rate and an electromagnetic emission test qualification rate, carrying out electromagnetic sensitivity test on the products to be tested. And obtaining the qualified rate of the to-be-tested product according to the product classification and the qualified rate, obtaining the EMC data of the to-be-tested product, and completing the EMC test of the electronic product. The EMC performance qualification rate of the product is obtained by comprehensively evaluating the results of the electromagnetic emission test and the electromagnetic sensitivity test, and powerful support is provided for quality control of the product.

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 provides a chip analysis method and device and a readable storage medium, and the method can divide a plurality of to-be-tested chips into a plurality of to-be-tested groups, test the to-be-tested chips in each to-be-tested group in sequence and determine a first statistical parameter, and also can test the to-be-tested chips in the to-be-tested groups after the to-be-tested chips in the to-be-tested groups are all tested. And generating a second statistical parameter based on the test result, thereby generating a corresponding optimization suggestion report and stopping the test when the first statistical parameter or the second statistical parameter meets a corresponding preset condition. The scheme provided by the invention can adapt to test requirements of chips of different numbers and types, ensures that chip analysis has better regularity and reliability through grouping test, can timely find test problems and improve the overall quality of the chips, generates a corresponding optimization suggestion report, provides a specific improvement direction, and improves the test efficiency. And an engineer is helped to quickly position a problem and formulate a solution, so that a subsequent test strategy is flexibly adjusted.

The invention discloses an automatic test case generation and execution method, which comprises the following steps: obtaining input content uploaded by a user, and analyzing the input content uploaded by the user to obtain structured key data; generating a preliminary test case according to the structured key data and a general rule of a knowledge base, optimizing the preliminary test case according to historical data and a code coverage rate, and generating a test case; compiling a test script according to the test case, and executing the test script; analyzing and processing the test execution result, and generating an execution structure and a test case analysis report; and performing optimization processing on the test execution result and the historical data, and dynamically adjusting a test strategy according to an optimization processing result. The invention further discloses a system for realizing the automatic test case generation and execution method. The test efficiency is improved, the test coverage rate is increased, the execution performance is improved, and automatic continuous testing is supported.

The embodiment of the invention provides a software system interface testing method and system, electronic equipment and a storage medium, and belongs to the field of software testing. The method comprises the steps that a software system interface document and a demand document are obtained, the interface document and the demand document are analyzed through a pre-constructed large model, document key information is extracted, and the document key information comprises but is not limited to interface definition, parameter information and business logic; based on the document key information, applying a preset test strategy to generate a test case, and generating a test script and test data meeting interface parameter requirements according to the test case; and integrating the test script into the CI / CD process, executing the test script, obtaining a test result, and generating a test report according to the test result. By means of the technical scheme, the large model technology can be effectively utilized to achieve software interface automatic testing, the testing efficiency and quality are improved, and the testing cost and human errors are reduced.

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 belongs to the field of universal software fuzz testing, and discloses a dynamic clustering fuzz testing method and system based on efficient byte exploration. According to the method, fuzzy test seed bytes are subjected to clustering analysis by using a density-based spatial clustering algorithm, the positions of key bytes are identified, and the effective variation times of the key bytes are recorded. Then, corresponding weights are distributed to the bytes according to the clustering result and the number of effective variation times of the clustering result, an energy distribution strategy is dynamically adjusted in combination with the path coverage rate and path novelty information, and the exploration efficiency of a new path is improved. And performing mutation on the high-weight bytes to generate effective seeds of a new path, locking key byte positions of the effective seeds, performing normalization processing on other positions, and continuing mutation operation. The test strategy is continuously optimized through repeated execution of the steps, and the fuzzy test efficiency and the vulnerability discovery capability are effectively improved.

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.