518 results about "Test script" patented technology

The invention relates to the technical field of software testing, and discloses an automatic test script generation method and system, a storage medium and electronic device.The method comprises the steps that test case information and tested environment information are received, and structured case representation is generated; enhancing the structured use case representation based on a preset knowledge base; generating a plurality of positioning candidates for the target control in the testing step, and establishing a priority relationship among the positioning candidates; generating an executable automatic test script; running the script, and when execution failure is detected, automatically adjusting a positioning strategy, a waiting strategy or a business process based on a failure type, and executing again; and feeding back the successfully executed script information to the knowledge base, and updating the content and priority of the knowledge base. Through organic combination of knowledge base enhancement, multi-candidate positioning and a self-healing mechanism, the technical problems that an existing automatic test script is high in maintenance cost, poor in stability and lack of domain knowledge are solved.

The invention discloses an automatic UI self-healing test method and system based on multi-agent AI, and belongs to the technical field of automatic UI tests.The automatic UI self-healing test method comprises the steps that an original test script is semantized through a test reasoning interpretation class, and an expected intention is output; when the test fails, synchronously collecting multi-source data and extracting multi-modal features, constructing a fault propagation graph according to an expected intention and the multi-modal features, and performing fault propagation analysis by using a graph attention network to obtain a fault diagnosis result; according to a fault diagnosis result, a deep Q network, a greedy strategy and a Byzantine fault-tolerant algorithm are adopted to negotiate and decide a repair strategy through a distributed agent cooperation mechanism, and feedback is obtained; optimizing and dynamically adjusting the repair strategy and the test reasoning interpretation class through a meta-learning algorithm based on feedback; a test intention is deeply understood by constructing a test reasoning interpretation class, and fault diagnosis and automatic repair are cooperatively completed by adopting a distributed intelligent agent, so that the semantic understanding capability, the diagnosis accuracy and the repair success rate are improved.

The invention discloses a test method, device and equipment and a computer readable storage medium, which are applied to the technical field of computers, and comprise the following steps: obtaining multi-source data of a distributed storage cluster, the multi-source data comprising hardware state data, service associated operation data and business dependence data; constructing a relation dependency graph among the hardware nodes, the service nodes and the service nodes based on the multi-source data; adjusting the chaos test script according to the real-time state of the distributed storage cluster and the dynamic adjustment strategy to obtain a target chaos test script; and executing the target chaos test script, determining a fault range and a recovery mechanism based on the relation dependency graph, and outputting a test report. According to the method, comprehensive and accurate presentation of the dependency relationship of each node is realized, and the chaos test script can adapt to the dynamic change of the cluster, so that the test scene is more practical, the invalid test is avoided, the effectiveness, reliability and efficiency of the cluster chaos test are remarkably improved, and the high availability and service continuity of the cluster are powerfully guaranteed.

The invention provides a front-end regression test method, a program product, electronic equipment and a storage medium. The method comprises the following steps: acquiring user behavior data of a user in a to-be-tested application program; based on the element positioning information, performing semantic annotation on the user behavior data through a predefined rule and / or a semantic understanding model to obtain semantic information; based on the network request data, grouping the labeled user behavior data, and screening out a test case corresponding to a single page path for a user behavior data group; restoring the test environment to an initial state; determining a target element corresponding to the interactive operation data in the test case by adopting an element positioning algorithm; and in the initial state, executing a corresponding interaction operation based on the target element, and completing test playback. Therefore, the test script has higher adaptability to local change of the front-end page, the large-scale failure risk of the test case caused by the change of the page structure is reduced, and the stability and reliability of the test are enhanced.

The embodiment of the invention discloses an automatic test script repairing method and related equipment, which are used for solving the problem of failure of an automatic test script locator caused by frequent change of a user interface and improving the stability and maintainability of a test script. The method comprises the steps that the execution process of a test script is monitored, and if a locator of a target element related to current target operation in the test script fails, failed page feature information of a current page is collected; generating at least one candidate locator through a pre-trained locator generation model based on the failed page feature information; and verifying the candidate positioners generated by the pre-trained positioner generation model, and taking the candidate positioners passing the verification as the repaired positioners and updating the repaired positioners to the test script.

The invention relates to the technical field of adaptive testing, and particularly provides a WebUI adaptive testing system and method based on multi-agent collaboration and multi-modal perception, and the system comprises a multi-modal perception subsystem, an agent collaboration testing subsystem and an assertion and verification subsystem. The method comprises the following steps: adjusting an element positioning strategy for a multi-dimensional interface feature set through a continuous interaction feedback mechanism, and outputting an element descriptor set; deploying a multi-agent collaborative decision-making unit comprising an interface understanding agent, a test logic agent and a data agent; outputting to form a semantic test script through a collaborative fusion mechanism; comprising the following steps: carrying out pixel-level difference calculation, and identifying a visual inconsistent region through multi-scale image comparison; and performing service-level logic difference, analyzing the consistency of the interface element state and the service rule, and outputting a hierarchical verification report. According to the invention, high coverage rate, low maintenance cost and reliable defect positioning capability of the test can be maintained in an environment with frequent evolution of pages.

The invention discloses an automatic interlocking test method and system based on a RobotFrameWork framework, and belongs to the technical field of interlocking tests.The automatic interlocking test method comprises the steps that on the basis of a preset rule and a general test case, function logic decoupling is conducted on a test script in combination with the RobotFrameWork framework, and function keywords are obtained; obtaining a configuration file according to the interlocking function and the test data type, and performing feature extraction on the to-be-tested data and the interlocking table based on the configuration file to obtain associated test data; and according to the test requirements and the associated test data, performing testing in combination with the function keywords. The method comprises the following steps: performing function decoupling on a test script through a keyword driving characteristic of a RobotFrameWork framework to obtain a function keyword which only encapsulates single function logic, and extracting associated test data related to a test from to-be-tested data and an interlocking table through an interlocking function defined by a configuration file and a mapping rule of a data type. The technical problems that test efficiency is difficult to improve and script maintenance is difficult in the prior art are solved.

The invention discloses a dynamic simulation test verification method and system for a pumped storage unit monitoring system, and the method comprises the steps: building a high-dimensional system state matrix of a pumped storage unit based on the physical parameters and structural features of a hydraulic, mechanical and electrical system of the unit, carrying out the dimension reduction of the high-dimensional system state matrix, and obtaining a dynamic simulation test result of the pumped storage unit; a dynamic simulation model of unit multi-physics field coupling is obtained; constructing a multi-dimensional parameter space based on the parameter sensitivity coefficient and the working condition boundary condition of the dynamic simulation model, and calculating optimal test point distribution through a high-dimensional point flow diameter algorithm to obtain a test scene library; based on the dynamic simulation model and the test scene library, obtaining a real-time monitoring signal sequence conforming to a monitoring system communication protocol; and based on the real-time monitoring signal sequence, signal acquisition, logic judgment and alarm control functions of the monitoring system are tested through an automatic test script, and a performance evaluation result of the monitoring system is obtained. The test comprehensiveness and effectiveness of the pumped storage unit monitoring system are improved.

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 embodiment of the invention relates to the technical field of information, and discloses an interface verification and test method and device based on a large model, a medium and a product, and the method comprises the steps: obtaining a to-be-tested interface document, analyzing the interface document through a first large model, constructing a test request parameter based on a request parameter definition, acquiring a real-time response message by calling a real interface; performing semantic comparison on a response example in the document structure information and the real-time response message by using the second large model to obtain a corrected interface document; comparing the parameter constraint condition in the corrected interface document with the verification logic in the business logic code snippet by using a third model to generate a logic verification passing result; and on the basis of the corrected interface document and a logic verification passing result, a Mock rule and an automatic test case script are generated by utilizing the fourth model, so that the maintenance cost and the false alarm rate of the automatic test script are reduced, and the automatic test efficiency is improved.

The embodiment of the invention discloses a test script generation method, system and device, a medium and a product, and relates to the technical field of tests.The method comprises the steps that target structured DBC data is obtained; processing the target structured DBC data by utilizing a target test script generation model to obtain at least one CAPL test script fragment; the target test script generation model is obtained by training according to historical structured DBC data and corresponding historical CAPL test script fragments; the CAPL test script fragment comprises at least one of variable declaration, function definition and event processing; and according to the at least one CAPL test script fragment, determining a target CAPL test script so as to quickly realize verification of the CAN bus communication condition.

The embodiment of the invention provides a test method and device based on component change, equipment, a medium and a program product, relates to the field of artificial intelligence, and can be applied to the field of software testing and the field of financial science and technology. The method comprises the following steps: in response to monitored source code change information of a to-be-tested system, determining a change component according to the source code change information; according to the change component and a pre-constructed component dependency graph, determining a function influenced by the change component, and obtaining a target test script associated with the function influenced by the change component; wherein the component dependency graph is a graph which is constructed according to a source code, a log file and a configuration file of a to-be-tested system and is used for representing a dependency relationship among a component, a function and a test script; executing the target test script according to a preset execution rule; wherein the execution rule comprises priority execution rules of a plurality of target test scripts. According to the method, the software testing efficiency and precision are effectively improved.

The invention discloses a mainboard function automatic detection method and device, and relates to the technical field of computer hardware detection. The method comprises: receiving a user instruction through a graphical interface to generate a test queue; distributing an independent thread for each test item to execute hardware detection, and dynamically mapping the position of a physical port; analyzing a test state in real time and updating interface feedback; comparing the actual hardware parameters with preset parameters; and hot update of the test script is supported. The device comprises a graphical interface module, a multi-thread execution engine, a scripted hardware detection module and the like. The mainboard function detection device can perform efficient, automatic and visual detection on the mainboard function, and is suitable for quality control of mainboard production, maintenance and research and development links.

Methods and systems for artificial intelligence (AI) assisted automation of testing of a software functionality related to a user intent on a software platform is provided. In one embodiment, the method includes receiving user action data indicating the user intent related to a software platform and generating a human-readable test scenario. The test scenario, which includes a sequence of human-readable testing steps and an expected outcome, is generated using a scenario machine learning (ML) model. The method includes generating an interpretable test script based on the test scenario using a script ML model. The test script is interpreted to implement testing steps on the software platform, generating a test outcome. A human-readable test report is also generated to evaluate the test scenario on the software platform, based on the test outcome and the expected outcome.

The invention discloses an acceleration tube full-process automatic reliability test system and device, and relates to the technical field of high-power microwave device testing, and the system specifically comprises the following modules: a control test module, a hardware control module, an acquisition processing module, a business logic module, a data persistence module, and a user performance module. Writing and executing an automatic reliability test script of the acceleration tube; receiving and executing a hardware control instruction, and uploading an original analog / digital signal of the equipment; the communication module communicates with equipment in the hardware control module, converts an original analog / digital signal into a digital signal which can be processed by a C # program, and carries out filtering, unit conversion and validity verification on the digital signal; an over-limit alarm function is provided, and the structured test data is sent to the data persistence layer; storing all test related data through a relational database; test parameter configuration, real-time monitoring, alarm states, data records and dose rate curves are provided based on a graphical user interface.

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

The invention discloses an automatic test method and device for control software, a medium and a product, and the method comprises the steps: obtaining an automatic test script which comprises a full-process test case executed when the control software is used for verifying a simulation verification board; and obtaining a current execution statement in the automatic test script, and identifying a to-be-operated target operation element and a target operation needing to be executed for the target operation element. And obtaining target text content matched with the target operation element, and positioning an element screen coordinate of the target operation element according to the target text content. And after executing the target operation in the target graphical user interface according to the element screen coordinates, returning to execute the operations of sequentially obtaining the current execution statements in the automatic test script, obtaining the updated target graphical user interface when it is determined that iteration is ended, and verifying the execution correctness of the automatic test script. According to the technical scheme, the accuracy and execution efficiency of automatic testing through the control software are improved.

The invention discloses an AI-driven full-scene intelligent test platform which comprises the following steps: performing static scanning on a target code under the triggering of a code submission event through a code static scanning module to generate a scanning result, and then inputting the scanning result into a pre-trained first AI model to obtain code quality evaluation data. And generating a white box test case through a white box case generation module. In addition, a black box test case is generated through a black box case generation module. An automatic script generation module inputs the black box test case into a pre-trained fourth AI model to generate an automatic test script; and finally, running the white box test case and the automatic test script to obtain an original test report. And inputting the original test report into a pre-trained fifth AI model through a result analysis module, and generating defect distribution data and test suggestion data. The full-scene test coverage of the software life cycle is realized, the test of each link of the software is comprehensively and systematically covered, and the test efficiency is improved.

The invention discloses a large model training method and device based on a voice task, a medium and equipment. The method belongs to the field of voice models, and comprises the steps of obtaining task description data of a voice task, reference model parameters and an experiment target, retrieving related technical knowledge data in a preset knowledge base by utilizing a retrieval enhancement generation technology, constructing a structured cue word input large model in combination with historical experiment records, and generating a training code and an experiment planning scheme. And then, performing iterative training on the reference model according to the experimental planning scheme to obtain a first voice task model, and performing testing based on a preset test script and a performance index requirement to obtain test result data. And finally, feeding back a test result or error information in a training process to the large model, updating a historical experiment record until an iteration termination condition is met, and finally obtaining an optimized voice task processing model. The problem that various voice task models cannot be accurately and efficiently trained in the prior art is effectively solved.

The invention relates to the technical field of data storage, and discloses a solid state disk compatibility and reliability testing method which comprises the steps of initializing a testing environment, installing an operating system, compiling and executing a testing script and configuring a compiling environment. Basic information of the solid state disk is recognized and classified, an automatic script is written, the classified basic information of the solid state disk is created into file clusters of different sizes according to the automatic script, continuous / random reading and writing are conducted, and file integrity is verified; and performing performance test on the classified basic information of the solid state disk by using a Fio tool and recording performance indexes of the solid state disk, wherein the performance indexes comprise sequential read-write speed, random IOPS and response delay, compiling an automatic script, and simulating a database load to perform small block random read-write operation. According to the invention, a plurality of modules for basic function and compatibility test, performance test, power management and reliability test, safety characteristic test and the like are integrated into a complete and automatic test scheme.

A network function configuration and test generation framework are configured to generate a test script indicative of a configuration and test cases for verifying a virtual function implemented in a virtualized computing environment. A test input is received that encodes information for verifying a network function. The information includes identification of a test tool, a target testbed for testing the network function, and network information including parameters for network conditions to be operational during testing of the network function. A data parser translates and formats the test input. The formatted test input in input to a topology discoverer configured to identify a network topology of the testbed and which network functions deployed on the testbed are emulated and which network functions deployed on the testbed are real. A configuration generator generates a configuration file usable to configure applicable network functions and their functionalities.

The invention provides a user interface testing method and device, electronic equipment, a medium and a program product, and can be applied to the technical field of big data and the technical field of artificial intelligence. The method comprises the following steps: acquiring a target test script, and performing semantic conversion on an operation instruction in the target test script by utilizing a first model to obtain a target test step set containing business semantic description; the target test step set is executed, in the process of executing the target test step set, the first model is used for determining the positioning mode of the target interface element according to the business semantic description, corresponding interaction operation is executed, and actual interface output is obtained; in response to execution failure of the target test step set, generating a diagnosis result by using a first model at least based on the actual interface output and the business semantic description; and inputting the diagnosis result into a second model, generating a modification code snippet by the second model, and applying the modification code snippet to the target test script.

A network function configuration and test generation framework are configured to generate a test script indicative of a configuration and test cases for verifying a virtual function implemented in a virtualized computing environment. A test input is received that encodes information for verifying a network function. The information includes identification of a test tool, a target testbed for testing the network function, and network information including parameters for network conditions to be operational during testing of the network function. A data parser translates and formats the test input. The formatted test input in input to a topology discoverer configured to identify a network topology of the testbed and which network functions deployed on the testbed are emulated and which network functions deployed on the testbed are real. A configuration generator generates a configuration file usable to configure applicable network functions and their functionalities.

The invention provides an AI-driven automatic test system and intelligent optimization method based on VISA and SCPI. The method comprises the steps that a natural language test requirement input by a user is acquired, the requirement is analyzed, and a test script conforming to the SCPI specification is generated; issuing the test script to the test instrument cluster through the virtual instrument software architecture interface, executing the test script, and collecting test data in real time; performing multi-modal fusion analysis on the basis of the collected test data to detect anomalies in the test process, and dynamically adjusting test parameters or test scripts according to an anomaly diagnosis result; performing cooperative task scheduling optimization on a plurality of instruments in the test instrument cluster based on the adjustment result; according to the method, a large language model is combined with an SCPI command knowledge graph to realize automatic conversion from a natural language to a test script, and test parameters and multi-instrument scheduling are dynamically optimized in combination with reinforcement learning, and the test efficiency and precision are remarkably improved through real-time anomaly detection and root cause positioning.

The invention discloses an automatic test script generation method and device based on deep learning, equipment and a medium, and relates to the technical field of computers. Comprising the following steps: analyzing an obtained test case to extract key test information; using a preset dynamic Bayesian classification model to perform classification evaluation on the test cases based on the key test information to obtain corresponding risk probabilities, and using a preset weight adjustment function to adjust the priorities of the test cases according to the risk probabilities; generating an automatic test script based on the test case by using a preset deep learning model; extracting failure features from the execution result of the automated test script by using a preset failure mining function, and updating the failure features to a preset knowledge base; and utilizing a preset incremental learning scheduling function to optimize a preset dynamic Bayesian classification model and a preset deep learning model based on the execution result. Therefore, intelligentization, high efficiency and sustainable optimization of automatic test script generation can be realized.

The invention discloses a high-speed parallel EMMC (Embedded Multi Media Card) test method and system. The method comprises the following steps: generating a test script; the test script comprises the steps of generating a protocol setting instruction based on an interface protocol type of the to-be-tested EMMC, generating a test command based on a test item type of the to-be-tested EMMC, and setting a test ending condition; based on the test script, testing a plurality of to-be-tested EMMCs in parallel through a plurality of test daughter boards comprising multiple channels, and collecting test parameters in real time; wherein different test items of each to-be-tested EMMC are tested according to a preset sequence; in the testing process, follow-up testing is adjusted based on testing parameters collected in real time and a preset optimization rule; and for each tested EMMC, when it is judged that a test ending condition is met, ending the test, returning a test result, analyzing the test result and outputting a test report. Through the automatic optimization strategy and the parallel test, the test efficiency can be improved, and the labor dependence and the test cost can be reduced.

The invention discloses a test and evaluation method for a virtualization system in multiple scenes, which comprises the following steps: deploying an executable file compiled by a test script at a virtualization client, and testing the performance of a client operating system to judge the performance loss of the virtualization system to computer resources. The method comprises the following steps: step 1, creating a project, and configuring system parameters; 2, integrating a test program into a project, and generating a mirror image file; step 3, packaging a complete virtualization system mirror image; 4, transmitting the mirror image to a development board through a network protocol; 5, executing a command to start a system, and logging in a system console through a serial port; and 6, calling and executing the function test script, the performance test script and the security test script.

The embodiment of the invention provides an integrated testing method and device and a storage medium. In the embodiment of the invention, the AI large model, the MCP protocol and the multiple test frameworks of the execution layer are fused, so that an integrated test process with the cooperation of multiple test types is realized; the AI large model analyzes the test requirement document, recognizes multiple test requirements, is responsible for generating multiple test cases from the multiple test requirements, further converts the generated multiple test cases into multiple types of test scripts, calls a corresponding test framework to execute the test script corresponding to each test type through the MCP service of the execution layer, and performs the test on the test scripts. An integrated process from test case generation and script conversion to a test process is realized, and collaborative execution of multiple types of test scripts is realized. In addition, the integrated test framework further comprises a scheduling layer which is used for responding to the output of the AI large model, calling the MCP service of the execution layer, unloading the function of scheduling and managing the MCP service of the execution layer from the AI large model, and improving the reasoning efficiency of the AI large model.

The purpose of this disclosure is to utilize generative AI to reduce the effort required to create test scripts. [Solution] A program for operating a computer having a processor and memory, the program causing the processor to execute the following steps: accepting specification of information related to a test from a user; reading WAI-ARIA roles and labels from a page expressed in HTML as summary information about the page on which the function to be tested is executed; creating a first prompt including information related to the test, summary information, and an instruction statement instructing the output of test procedure information; inputting the first prompt into a generation AI and causing the generation AI to output the test procedure information; and creating a test script based on the procedure information.

The invention designs and implements a performance test environment construction method oriented to cross-chain transaction of block chains. The system supports a user to customize test scripts and execution parameters according to test requirements, tasks are executed and workloads are initiated at the same time through multiple actuators, a load scene of a tested cross-chain application system is created, the whole process of cross-chain transaction from an initiator to a receiver is tracked at the same time, key data are collected, and performance test indexes are calculated. And a visual result report is generated. Comprising the following steps: analyzing system requirements, and describing and analyzing functional requirements and non-functional requirements of a system; carrying out summary design on the system, and respectively designing and describing the system from a logic view angle, a process view angle, a development view angle and a physical view angle; detailed design is carried out on each module of the system, and a scheme is designed for the modules from two different perspectives of a class diagram and a time sequence diagram; and carrying out system testing and summarization on the system.