742 results about "Test execution" patented technology

The invention relates to the technical field of communication control, and discloses an interconnection test method and system for a wireless communication module, and the method comprises the steps: collecting real-time communication data through a multi-source communication interface, extracting topological features through a graph theory model to generate a matrix, and obtaining a signal optimization parameter through a self-adaptive filtering model; and constructing a multi-target test path planning model and outputting optimal path data, and establishing a layered test execution model to complete the test. The system comprises a communication topology analysis module, a path dynamic planning module and a hierarchical test execution module. The method overcomes the defects of a traditional testing method, can comprehensively collect data, accurately analyze topology, effectively process signals, scientifically plan a testing path and perform layered collaborative testing, has remarkable effects in improving testing accuracy, efficiency and comprehensiveness, can adapt to the development requirements of a wireless communication technology, and ensures stable and reliable work of a wireless communication module.

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 discloses an automatic driving vehicle key signal testing method and system based on real data driving. According to the method, data are collected in a real road scene, test cases are automatically generated, a standard test case library is constructed, hierarchical or parallel testing is carried out in virtual simulation, hardware-in-the-loop and real vehicle environments, and result feedback and closed-loop iteration are achieved through automatic analysis. The system comprises a data collection module, a test case generation module, a standard test case library module, a test execution module and a result feedback module. According to the invention, the problems of insufficient scene coverage and low authenticity and efficiency of the existing test method are solved, the comprehensiveness, authenticity and test efficiency of the test scene are improved, and the safety and reliability of the key signal system of the automatic driving vehicle are guaranteed.

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 present disclosure relates to a system (102) and method (500) for analyzing network performance parameters. A user interface module (212) enables reception of comprehensive network speed test requests that specify multiple network performance parameters for analysis. A test execution module (214) triggers coordinated operation of multiple testing units (302a, 302b, 302c) to perform simultaneous network speed tests across different platforms. A data collection module (216) systematically aggregates the generated performance information from all testing units. One or more processors (202) transform the collected information through advanced processing algorithms to generate standardized performance data for each network parameter. An analyzing module (218) performs multi-dimensional analysis of the processed data based on specific attributes to provide comprehensive network performance insights. The integrated approach enables automated cross-platform testing, unified data collection, and sophisticated analysis of network performance characteristics, offering significant advantages over conventional single-platform testing methods.

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 belongs to the technical field of cloud computing and software testing, and particularly discloses an automatic fault injection and recovery testing method based on cloud native, which comprises the following steps: acquiring test basic data of a to-be-tested cloud native system; constructing a fault test execution model according to the test basic data; according to the fault test execution model, executing an automatic fault injection operation; generating an abnormal alarm log according to the system running state after the fault injection operation, and synchronously recording a fault injection operation log; according to the abnormal alarm log, executing automatic fault recovery operation; and generating a fault test report according to the fault injection operation log, the system monitoring data and the recovery operation process log. The invention aims to solve the problems of low automation degree, narrow scene coverage, weak monitoring evaluation and passive recovery in cloud native system fault test in the prior art, and provides a comprehensive, automatic, monitorable and evaluable fault injection and recovery test scheme.

A natural language-based no-code test automation system is provided. The test automation system includes natural language-based test cases and an app description file including a natural language description of a particular test application run on test devices. An intelligent test execution engine includes an orchestrator configured to convert the natural language-based test cases into actions to be performed for testing the test application on the test devices using the app description file and a large language model subsystem implementing large language models. The orchestrator maps each of the actions to a corresponding test application interface call in the test automation system using one or more of the large language models, and automatically tests the test application by iteratively executing each of the actions via the corresponding test application interface call.

The invention provides an automatic leak detection method and system for a dynamic bending durability test of a metal corrugated pipe, and relates to the technical field of metal corrugated pipe performance tests.The method comprises the steps that a to-be-tested metal corrugated pipe is installed on a test station, and test working condition parameters are set through a PLC; the test working condition parameters comprise a bending motion mode, a load spectrum, an internal pressure type, a pressure value, a temperature condition and a test frequency; according to the bending motion mode and the load spectrum, a multi-degree-of-freedom bending motion mechanism is driven to apply a dynamic bending load to the metal corrugated pipe; and when the dynamic bending load is applied, internal pressure is applied to the interior of the metal corrugated pipe according to the internal pressure type and the pressure value, and a temperature environment is synchronously applied, so that a multi-factor coupling load is formed. According to the invention, on the basis of working condition setting, through multi-source data acquisition, correction and fusion determination, an automatic closed loop of test execution, abnormity alarm, helium detection quantification and report generation is realized.

The invention discloses a research and development test bidirectional synchronization method based on artificial intelligence, and particularly relates to the technical field of artificial intelligence and software testing. Deep semantic modeling of research and development task behaviors is realized by constructing a multi-modal causal intention map, a test coverage blind area is inferred and recognized based on a graph neural network, a completion task is reversely generated, a complete state set is formed in combination with an original task set, and a condition control vector is adopted to drive generation of a structured test case. Collecting behavior and operation logs after the test is executed, detecting a mismatch area through modal alignment, generating a repair suggestion by utilizing a deviation correction model, and automatically writing back a task system; meanwhile, a state graph dynamic updating mechanism and a reverse task scheduling engine are introduced, and linkage feedback of test results on research and development tasks is achieved; the method can improve test coverage precision and research and development cooperation efficiency, and is suitable for agile development and continuous integration scenes.

The invention discloses an automatic joint debugging acceptance system for a power distribution automation terminal, and relates to the technical field of power system automation. A multi-protocol communication module is in bidirectional communication with a main control module and an intelligent test execution module, so that three-way data interaction among a main station system, the power distribution terminal and a test device is realized; after receiving the instruction of the main control module, the intelligent test execution module outputs an analog quantity / state quantity signal conforming to the terminal interface standard through a self-adaptive quantity adding unit, and applies test excitation to the power distribution terminal through a hot plug type interface array; the data verification engine is directly connected with the multi-protocol communication module, carries out three-level verification on feedback data of the master station, and transmits a verification result back to the master control module to trigger strategy iteration; the cloud co-processing unit obtains verification data through the main control module and executes cross-regional task scheduling and block chain evidence storage operation, the long-standing problems of low efficiency and low precision of power distribution terminal joint debugging acceptance are solved, and key technical support is provided for construction of an intelligent power system.

The invention relates to the technical field of coating testing devices, and particularly discloses an induction cooker glass ceramic functional coating testing device which comprises a base and a detection box located on the base, a detection cavity is formed in the detection box, a testing table is arranged in the detection cavity, and the testing table comprises a testing execution mechanism and a testing placement seat; the test execution mechanism comprises a friction disc, an electromagnetic coil is arranged in the friction disc, and a groove which is spirally distributed is formed in the bottom of the friction disc; the test placement seat comprises a loading table of which the middle of the top is provided with a to-be-tested coating panel in a position corresponding to the friction disc, the periphery of the top of the loading table is provided with a convex check ring, the upper part of the convex check ring is provided with a nozzle corresponding to the to-be-tested coating panel, and the nozzle is communicated with a storage tank arranged at the bottom of the loading table through a pressurizing pipeline; a magnetorheological abrasive is stored in the storage tank; the device has the advantages of high test precision and real test simulation.

The invention provides a performance testing method and device for a large language model and related equipment. The performance testing method comprises the steps that multiple testing platforms for testing, testing scene configuration parameters and a structured testing data set for testing are determined; on the basis of the test scene configuration parameters and the structured test data set, synchronous constraint parameters are generated and distributed to the multiple test platforms, and then a preset load generator is used for controlling the multiple test platforms to concurrently execute reasoning test tasks about the large language model; and when the test is executed, collecting multiple dimension performance indexes of each test platform in real time for data analysis, and generating a reasoning performance comparison evaluation report of the large language model in the multiple test platforms according to a data analysis result. According to the method, the cross-platform performance evaluation period is greatly shortened, and the waste of computing resources is reduced. Manual operation errors are avoided, comparability of multi-platform performance indexes is guaranteed, and more accurate and reliable multi-platform performance test results can be obtained.

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 discloses a wind power plant intelligent simulation acquisition test method and system, and relates to the technical field of wind power plant intelligent acquisition and state prediction control, and the method comprises the steps: obtaining the operation state parameters of a wind turbine generator, and constructing a twinborn prediction model based on a time sequence. And comparing a model prediction value with a measured value to calculate an operation state error, and estimating prediction uncertainty. And dynamically adjusting the sampling frequency of the sampling channel according to the prediction uncertainty and controlling test execution. According to the method disclosed by the invention, a smart wind power plant simulation acquisition test system from data driving to state modeling to risk perception to dynamic regulation and control to multi-node collaborative integration is realized. According to the technical scheme, independent technical contributions are provided, link-by-link logic closed loops are constructed, a breakthrough is made from a traditional static acquisition mode, a digital wind field acquisition test system with predictability, self-adaptability and linkage response capability is formed, and the monitoring efficiency, the risk control granularity and the system resource utilization rate are improved.

The invention relates to the technical field of artificial intelligence and automatic testing, and particularly discloses an AI-based automatic testing method and device. The method comprises the following steps: capturing and recording complete execution historical information in a process of executing a test task by an AI agent, and serializing and storing the complete execution historical information as reusable cache data; before the test is executed, the validity of the cache is judged through a multi-dimensional verification mechanism including data integrity, timeliness, functionality and the like; when the cache verification is passed, a result is quickly obtained based on the cache data playback test process; when cache verification is not passed or execution fails, triggering an AI agent to perform new reasoning and steps to generate and update cache data; and meanwhile, a caching strategy is dynamically adjusted according to test case changes and resource conditions. The device comprises a test executor, an AI agent manager, an intelligent cache manager and a dynamic cache management module, and all the modules work cooperatively to improve the test efficiency, reduce the calling cost of a large language model and enhance the stability of a test result. The method is suitable for Web / APP automatic testing, cross-platform testing, CI / CD process testing and other scenes, the execution efficiency can be remarkably improved, the cost is reduced, and resource utilization is optimized.

The invention provides a network security test coverage evaluation method and system based on deep learning, and relates to the technical field of network security testing, and the method comprises the steps: extracting a multi-dimensional feature vector through constructing a feature fusion network, calculating the similarity based on a test execution path diagram, carrying out the clustering, and removing redundant branches, traversing the optimized path set to obtain a key node sequence, evaluating the contribution degree, and establishing a mapping relation between the contribution degree and the test effect to determine the test coverage rate.

The invention discloses a POL power supply automatic test method based on modular design, and belongs to the technical field of power supply test. The method comprises the following steps: firstly, under the control of an upper computer, automatically reading POL power supply basic parameters including key characteristic parameters such as input / output voltage, rated current and frequency from a preset Excel table, and establishing a judgment reference for testing; then, instrument initialization is completed, communication connection with test equipment such as an oscilloscope, an electronic load and a direct-current power supply is established, and configuration of initialization function parameters is completed; then, executing a measurement task of each core parameter of the POL power supply to be tested, and in the test process, executing a parallel measurement management mechanism, namely configuring each instrument parameter and channel state in real time according to a specific test item, and triggering a retry or interrupt logic under the conditions of communication abnormality, data timeout and the like until the test recovers a running state; and finally, after the test is completed, performing Excel storage and interaction on the standardized test data and the waveform screenshot, and finally safely exiting. According to the POL power supply automatic test method based on the modular design, the whole test process is divided into a plurality of serial or parallel function processing units such as parameter reading, instrument initialization, test execution and test management, data storage and interaction and the like, and high efficiency and usability of a test system are achieved.

The invention discloses a production line test construction system based on an MES system, and relates to the technical field of intelligent manufacturing and production line testing, and the production line test construction system comprises a test configuration module, a test execution module, a data integration module, a visual interface module and an authority management module. The test configuration module is used for automatically obtaining a test process template from the MES system according to the product model information and completing process customization in a graphical mode; the test execution module identifies a to-be-tested product and calls a process file, and controls the test equipment to execute a test and perform data acquisition and judgment; the data integration module binds the test result with the unique identifier of the product, and uploads the test result to the MES system to realize full-process tracing; the visual interface module is used for displaying a process state and a test result; the authority management module is used for performing hierarchical control and version conflict detection on the operation authority; according to the system, the construction efficiency and execution reliability of the test process are improved, and closed-loop and intelligent management of data in the test process is realized.

The invention discloses a one-key performance test method, medium and equipment based on JMeter and template configuration, and the method comprises the steps: obtaining a parameterized performance test template from a template configuration center in response to a test instruction, injecting runtime parameters through a template engine, and generating an executable JMeter test plan; parsing the plan to identify a load pressure demand, thereby dynamically scheduling resources from a distributed load injector cluster and distributing a test plan; uniformly triggering test execution on the cluster, and synchronously acquiring a performance data stream from the JMeter and a resource data stream of the tested system; and finally, timestamp alignment and fusion are carried out on the two types of data streams, intelligent diagnosis is carried out on a formed monitoring data set based on a diagnosis rule base or an intelligent analysis model, and a visual test report containing bottleneck positioning, resource association and link tracking analysis results is generated. According to the invention, full-process automation and intelligentization of performance testing are realized, and the testing efficiency is remarkably improved.

Apparatuses, methods, and systems for determining winning arms of electronic testing. One method includes obtaining historical data related to the testing, creating a histogram based on the historical data, the histogram including bins and weights, creating a distribution by computing concentration parameters of the distribution from the weights of the histogram, executing the testing, receiving new data collected based on the execution of the test, allocating the new data into same bins as the bins of the histogram of the historical data yielding a new data bin count, computing a posterior distribution comprising updating the distribution using the same bins and the new data bin counts and the concentration parameters of the distribution, inferring corresponding central tendencies of samplings of a metric distribution, constructing an overall utility distribution for each arms of the test, and determining a winning arm of the testing.

The invention relates to a Python-based Web system automatic test method, which comprises the following steps of interface test data capture, page element acquisition, test framework establishment and establishment of a visual test platform by combining a UI (User Interface) and an interface case, in the interface test data capture, a charls tool is used for data capture, agent setting and SSL (Secure Socket Layer) certificate installation; after packet capturing is completed, file conversion in a yaml format is carried out; in the step of page element acquisition, related information of elements is acquired by using a method provided by Selenium, and a page is analyzed, processed and packaged. According to the method, the Web automatic test execution efficiency can be improved, the problem that the use threshold is too high is avoided, and the project risk and the labor cost are reduced.

The invention relates to the technical field of coal mine test equipment, in particular to a one-stop automatic test integration platform and a test method for coal mine application software. The one-stop automatic test integration platform comprises an executable test case construction module, an automatic test execution module and a test result management module. According to the automatic test platform and the test method, the functions of test management, system safety penetration, software automatic test, source code static analysis, system performance test, localization adaptation test and the like are integrated; the problem that in the prior art, it is difficult to comprehensively cover all function combinations and abnormal conditions by manually compiling test cases is solved, and the test omission ratio is remarkably reduced; centralized management and correlation analysis of data in each link in the testing process are realized through the data centralized management module, so that the testing efficiency is improved, and the problem positioning is more accurate and rapid; a standardized testing process is integrally formed, and software quality and compliance are guaranteed through all-around testing means.

The invention relates to an automatic interface test management method and device, equipment and a medium, and the method comprises the steps: obtaining an interface document of a to-be-tested interface, carrying out the analysis of the interface document, generating interface case data containing the primary configuration content of an interface case, and transmitting the interface case data to a server; performing execution grouping on the interface cases configured with the input parameter value set, generating a case execution group based on interface grouping information and a preset test execution strategy, setting an execution sequence and an exception handling rule for the case execution group, and generating a corresponding execution link at the same time; calling an execution link based on the trigger request to sequentially use each group of request content execution cases in the input parameter value set to execute the interface cases in the group, and generating corresponding case execution results; high automation and intelligentization are achieved in the whole interface test process, manual intervention is remarkably reduced, the test coverage rate is increased, the problem response speed is increased, and therefore the working efficiency of testers is effectively improved, and the human error risk is reduced.

The invention relates to the technical field of electronic measurement, in particular to a multifunctional comprehensive test method and system for a direct-current power supply, and the method comprises the steps: initializing a test; a static performance test step; a dynamic performance test step: driving a direct-current electronic load module to execute a time sequence instruction sequence in the dynamic load test file, and acquiring an output voltage and an output current waveform through a high-speed data acquisition module in the execution process; a ripple noise test step: switching the high-speed data acquisition module to an alternating current coupling mode and acquiring a high-frequency noise waveform in a constant load current section in the time sequence instruction sequence; a correlation analysis step; and a test termination step: controlling the load to return to zero and closing the tested DC power supply. Through automatic configuration and test execution of the system, the complexity of manual operation is reduced, and the test efficiency is improved. And especially in a high-frequency test scene, the test time is remarkably saved through automatic execution.

The invention belongs to the technical field of natural language processing, and particularly discloses a large language model test case self-adaptive generation method based on domain knowledge enhancement and closed-loop feedback, which constructs a domain knowledge base, and through a dynamic knowledge retrieval enhancement technology, in a test case generation process, a large language model test case is generated. The large language model can obtain and fuse the most relevant domain context in real time, so that a test case highly fitting domain business logic is generated, and a multi-step reasoning prompt framework based on a test thinking chain is designed to guide the large language model to generate the case; and automatically executing the generated test case, and collecting test execution feedback data to construct a preference optimization data set for performing directional fine tuning and reinforcement learning on the large language model, thereby realizing a complete closed loop of generation-execution-feedback-optimization. In this way, the model can continuously learn from test practice, the generation strategy of the model is continuously corrected, and self-evolution of case generation accuracy and effectiveness is achieved.

The invention relates to the technical field of software development, in particular to a code change influence recognition and automatic test execution method and system.The method comprises the steps that multiple types of nodes are extracted from code data, relation edges among the nodes are constructed according to code dependency relations, weights are set, and a semantic map is obtained; when the code is changed, analyzing by using a static analysis strategy, a dynamic analysis strategy and a semantic understanding strategy to obtain a change entry node; calculating the affected probability of each node according to each entry node, the semantic map and a preset propagation threshold; and obtaining and executing a test case related to each influenced node to obtain a test result. It can be understood that according to the technical scheme, three analysis strategies are combined, the direct influence and indirect influence of code change are comprehensively captured, then the test cases can completely cover the influence nodes, and the test efficiency is high.

The invention discloses a distributed testing method and system based on micro-service architecture. The method comprises the steps of generating a test task and a fault injection task according to a test plan; distributing each test case to a plurality of test agents according to the test task, so that the plurality of test agents respectively execute the corresponding test cases, and the plurality of test agents and the plurality of micro-service instances of the tested system run on a plurality of service nodes in a one-to-one manner; injecting a corresponding fault in an execution environment of the tested system according to the fault injection task; and collecting and summarizing log data related to the test, and outputting a test result and the influence of the fault on the test result according to the log data. According to the embodiment of the invention, a complete test process from test plan generation to test result analysis of the tested system is supported, high cooperation of fault injection and test execution is realized through accurate control of fault injection, and meanwhile, the distributed test system constructed based on the micro-service architecture can be adaptively expanded according to the scale of the tested system.

A method of generating a code output in response to a natural language problem description. The method includes: receiving the natural language problem description; generating, by a neural network based language model, a first candidate code snippet based on a first input prompt combining the natural language problem description and a first instruction; executing, at a code execution environment, the first candidate code snippet based on a unit test thereby producing a first feedback reflecting a correctness of the first candidate code snippet; generating, by the neural network based language model, a second candidate code snippet based on a second input prompt combining the natural language problem description, the first candidate code snippet, and the first feedback; and executing, at the code execution environment, the second candidate code snippet based on a runtime test thereby producing a second feedback reflecting a runtime efficiency of the second candidate code snippet.

The invention belongs to the technical field of semiconductor testing, and particularly relates to an HBM-DRAM grouping testing system and method, and the system comprises a main testing controller and a plurality of testing execution units configured in the system. And the main test controller is in communication connection with the plurality of test execution units through a preset test coordination bus. By physically segmenting the test interface into a plurality of independent, low-needle-count probe card modules, challenges of designing and manufacturing a single, huge, ultra-high-needle-count probe card are fundamentally avoided. Therefore, the manufacturing cost, the calibration difficulty and the maintenance cost of each probe card module are greatly reduced, and the overall yield and the service life of the probe card are remarkably improved.