842 results about "Test execution" patented technology

The invention discloses an intelligent software testing method and system based on automatic script generation, and relates to the technical field of software testing, and the method comprises the following steps: deploying a distributed data acquisition probe, dynamically adjusting sampling frequency, collecting software operation data, and extracting data features based on a deep learning model; based on the data features, establishing a behavior pattern classification system, and mapping behavior patterns to realize hierarchical behavior classification; the method comprises the steps of constructing a test scene, generating test data, executing a test task, monitoring a test execution state in real time, calculating a test efficiency index, evaluating and feeding back a test effect, and dynamically adjusting a feature extraction strategy. According to the method, deep learning and reinforcement learning technologies are utilized, accurate recognition and classification of software behavior modes are achieved, and comprehensiveness and effectiveness of testing are guaranteed through multi-dimensional coverage rate analysis and a closed-loop optimization mechanism; and meanwhile, the automation level and the intelligent degree of software testing are remarkably improved, and a powerful guarantee is provided for improving the software quality.

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 a software testing automation platform and an intelligent optimization method thereof, and particularly relates to the technical field of software testing. The test case management module simplifies definition and automatic classification of test cases through a visual interface and a natural language processing technology; secondly, a test script generation module automatically generates and optimizes a test script by utilizing a preset template library and a self-defined script function in combination with an intelligent optimization tool; the test execution module executes test tasks in parallel in a multi-server or virtual machine environment through a task scheduling algorithm, and extracts environment load and response time characteristics in real time; then, the test result analysis module comprehensively analyzes an execution result by using the data prediction model, and identifies and marks an abnormal test case; and finally, the intelligent optimization module deletes the abnormal cases and dynamically adjusts the priorities of the normal cases to ensure that the high-priority test cases are executed preferentially, so that the automation level of test management is effectively improved, and the test execution efficiency and the result accuracy are optimized.

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 provides a testing method and device, testing equipment, network equipment, a medium and a program product, and is applied to the technical field of testing. The method comprises the following steps: obtaining test requirement information of a to-be-tested scheme, and obtaining test process information obtained by executing the to-be-tested scheme by test execution equipment; analyzing the test process information according to the test requirement information by adopting a multi-modal large model to obtain a test intermediate execution instruction; and sending the test intermediate execution instruction to the test execution equipment for further test execution of the to-be-tested scheme. By adopting the method, the test process analysis in the multi-modal test process is realized by utilizing the analysis and reasoning capability of the multi-modal large model on the multi-modal information, and the test intermediate execution instruction for guiding the test execution is generated according to the test requirement information and is used for executing the subsequent test steps, so that the multi-modal test efficiency is improved under the multi-modal test scene. Automation of the interaction process is tested.

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.

The invention discloses a software testing method and system based on a large model, and relates to the technical field of software testing, and the method comprises the following steps: step 1: describing a code review rule, and expanding specifications required to be checked: firstly, listing the check specifications required to be satisfied by a code, and according to a thinking chain and a zero- / feed-shot example, establishing a list of the check specifications required to be satisfied by the code; the check rules in the list are described as reasoning instructions of the model according to the check key points and the check steps through combination of one or more technologies of context learning; 2, code slicing: performing structure analysis and dependency analysis on the tested software project: firstly, slicing the code according to a function by utilizing a code analysis tool; according to the software testing method and system based on the large model, convenient project management, user-defined configuration and high-automation-degree test execution can be implemented on a software evaluation task, and the evaluation efficiency is effectively improved.

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 discloses a database driven document content pressure testing and monitoring system and method. The system comprises a database query module, a data processing module, an automatic test triggering module, a pressure test execution module, a real-time monitoring module, a data analysis and feedback module and a configuration and management module. According to the method, the JMeter is integrated into the CI / CD tool, the JMeter is configured to interact with the common CI / CD tool so as to support automatic triggering and execution of testing, continuous integration process design is adopted, check points are set in the CI / CD process, after code changes and is pushed to a version control system, a bound JMeter performance testing task is automatically started, a real-time monitoring and feedback mechanism is adopted, and the performance testing efficiency is improved. The test task comprises a component for monitoring performance indexes in real time, so that data can be captured in real time during the test execution period, and feedback can be immediately provided for the development team after the test is completed.

The invention relates to a control rod drop function availability automatic test method and a DCS system, and the method comprises the steps: receiving a test start instruction, entering a test mode, and in the test mode, obtaining the test sequence of each test rod group, and the measurement rod position and the counting rod position of a control rod; sending a bar moving instruction to the current test bar group; after the control rod action of the current test rod group is completed, the counting rod position is consistent with the target rod position, and the change of the measuring rod position of the control rod is detected; judging whether the change of the measurement rod position of the control rod accords with a preset threshold value; and if yes, judging that the control rod drop function availability test of the current test rod group is qualified. According to the invention, the availability test of the rod falling function of the control rod is changed from the traditional manual operation to the automatic test, so that the loss caused by human errors is effectively avoided; time consumed by the whole test is shortened, manpower is saved, and test execution efficiency is improved; and automatic checking is carried out, and a test result is given, so that human errors caused by long manual checking time are avoided.

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 an embedded software testing method and device, equipment and a medium, and relates to the technical field of computers, the embedded software testing method and device are applied to a Jenkins server, a plurality of testing nodes are mounted on the Jenkins server, each testing node comprises a to-be-tested piece and auxiliary testing equipment, and the method comprises the steps that task parameters of a testing task are extracted, screening out at least one target test node based on the task parameters and hardware environment parameters of the plurality of test nodes; the test task is issued to a target test node, so that the target test node configures a software environment and pulls a test case, and a test script of the test case is loaded to the software environment based on a CANoe target interface so as to perform a test; and uploading a test result to a project management server. According to the invention, full-process automation of test preparation, test execution and test feedback is realized, and the test accuracy, consistency and integrity are 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 discloses a branch coverage rate calculation method and device based on BOOL logic, and relates to the technical field of software testing. The method is suitable for the test case taking the BOOL logic expression as basic test data, the branch path diagram is generated according to the BOOL logic expression, the coverage rate condition of the test case set on the BOOL logic branches is calculated according to the covered path condition in the case execution process, covered and uncovered BOOL branch reports are output according to the test execution condition, and the test efficiency is improved. The test case executed by the black box is transparent, and meanwhile, a test case set can be completed according to uncovered branch guidance in an output report.

The invention discloses a method for automatically testing an interface based on RPA. The method comprises the following steps: making a test plan; building a test framework; compiling a test script; performing integrated testing; executing the test script; analyzing a test result; and maintaining the test script. Based on an RPA tool, through a graphical interface and predefined operation, a tester can create an automatic test script without writing any code, and the tester can define a complex test process only through simple dragging, clicking and configuration; an RPA tool is generally designed to be visual and easy to use, even a tester without any programming experience can quickly master the RPA tool, and the tester can master the basic skill of automatic testing through simple training and practice; the RPA has a unique verification mode for the login system needing to be verified, targeted system verification can be carried out, and the login interface can obtain the token conveniently.

The invention relates to the technical field of software testing, in particular to a software testing method, device and equipment. According to the method, the test priority of each module of a to-be-tested object is identified, a plurality of test cases are matched with each module according to the test priority, different test weights are allocated to each test case, and then the execution paths of the test cases are crossed and mutated according to the test weights and the test priority through a genetic algorithm, so that the test efficiency of the to-be-tested object is improved. And determining an optimal test case execution path, performing test defect feedback in real time according to a test result through a reinforcement learning algorithm in the test process, and adjusting the test priority of each module of the to-be-tested object and the test weight of the test case through a reward function according to a defect feedback result. Therefore, the software test platform can adaptively adjust the test execution path in the test process according to the test result, the test efficiency is greatly improved, and the defect discovery rate is also improved.

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.