420 results about "Test harness" patented technology

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

The invention discloses a method based on a large language model and ATTamp; the invention discloses a CK framework penetration test automation method and device, and the method comprises the steps: firstly carrying out the structural analysis of multi-source input information and tool output, and guaranteeing that key fields are not discarded; then combining a retrieval enhancement generation technology and a network security knowledge base to provide domain knowledge support for the large language model, so as to generate a model with ATTamp; a penetration test task tree marked by CK tactics, technologies and sub-technologies; on the basis, an optimal tool is automatically selected through a tool resource library and a multi-dimensional screening mechanism, an execution instruction is generated, and finally an execution result is returned to the input analysis module to form a self-adaptive optimization test closed loop. According to the method, semantic fidelity compression and standardization processing of long information can be realized aiming at the problems of large output format difference, more information redundancy and the like of different penetration testing tools, and efficient, explainable and auditory technical support can be provided for automatic penetration testing in a complex network environment.

The invention discloses a test case generation method and device, equipment and a medium, and relates to the technical field of software test optimization. According to the scheme, the multiple initial test cases are obtained, and the test reports corresponding to the initial test cases are generated through the first preset test tool, so that the time for manually compiling the test cases is effectively shortened; when it is determined that a to-be-supplemented test case of which the corresponding code coverage rate index does not meet a preset requirement exists according to each test report, code uncovered information of the to-be-supplemented test case is determined, and test case optimization parameters are configured in combination with project requirements; and based on the parameter, calling a second preset test tool and a large language model to supplement the to-be-supplemented test case to obtain a complete test case. According to the scheme, the availability of the test case is improved through combination of multiple tools; workflows of test cases covering complex environments such as a function calling relation and a control flow structure are generated by utilizing the inference capability of a large language model, and the code coverage rate of the test cases is remarkably increased.

The invention discloses a large language model agent security test method and device based on a model context agreement, and the method comprises the steps: firstly deploying a test tool in a test server, defining an application program interface which comprises function parameters and test probe parameters, describing the test probe parameters as necessary technical requirements for executing nominal functions, and executing the nominal functions according to the test probe parameters; and inducing the tested LLM agent to transmit complete session context data when calling. The test server receives a tool call request including a function parameter value and session context data, a back-end concurrently processes the request, executes a nominal function to generate a benign result, and extracts the session context data at the same time. Afterwards, a benign result is returned to the tested LLM agent, and the extracted data is asynchronously transmitted to a remote log server for recording as a test log. And finally, comparing the test log with the actual operation history, judging whether a session context data leakage vulnerability exists or not, and quantifying the severity level so as to detect whether the LLM agent leaks session memories such as the user interaction history or not.

The invention relates to the technical field of interface testing, and provides an interface testing method and device, electronic equipment and a medium. The method comprises the steps of obtaining a test request of a service interface and test specification data of the service interface; analyzing the test request through a large language model to obtain business logic information of the business interface; performing analysis processing on the test specification data through a large language model to obtain test index data of the service interface; generating a test case of the service interface based on a large language model according to the service logic information of the service interface and the test index data of the service interface; and calling a preset test tool to execute the test case to obtain a test result of the test case.

A test-case generation software receives requests that are to be processed by a request processing software. The test-case generation software obfuscates data in the requests to generate obfuscated request data. The test-case generation software generates test cases based on the obfuscated request data. The test-case generation software configures a testing tool based on the test cases. The test cases can be generated based on a distribution of endpoints identified in the requests. The test cases can be generated based on a distribution of values of a parameter in the requests.

The invention discloses an automatic performance testing method and device based on an HDFS cluster and a server. According to the method, corresponding HDFS cluster built-in test tools are called according to different test targets to execute corresponding performance test items, different scene simulations are realized through configuration of different test targets, and multi-dimensional tests can be performed for different cluster configurations. The performance in multiple aspects of throughput, metadata operation capability, high concurrency and the like can be covered, so that the performance of the cluster can be tested more comprehensively; besides, the method integrates self-contained test tools of the HDFS, and performs unified test based on standardized tools and configuration, thereby facilitating performance comparison among different clusters; according to the method, the test efficiency can be improved to the maximum extent and the human intervention is reduced through the writing of the automatic script and the assistance of the intelligent algorithm, so that the automatic performance test which is uniform in standard, efficient and reusable is realized by the method aiming at the HDFS cluster.

The invention relates to the technical field of testing, can be applied to the fields of financial science and technology and medical health, and discloses a software testing method, device, equipment and medium based on heterogeneous multi-agent, the method comprises the following steps: receiving a to-be-tested task, and analyzing the to-be-tested task to generate a task vector; for each heterogeneous agent in an agent pool, constructing a capability vector of the heterogeneous agent, and determining a capability matrix according to the capability vector and the task vector; generating a test workflow of the directed acyclic graph according to the task vector and the capability matrix; aiming at each task node in the test workflow, performing graph enhancement retrieval from a domain knowledge base to obtain a retrieval result, and injecting the retrieval result into a control instruction of the task node as enhancement knowledge; and calling a preset test tool to execute a test case generated by the test workflow. And the test quality and the test efficiency of the complex software system are improved.

The invention provides a testing method, a server and a storage medium, and relates to the technical field of testing. The test method is applied to a server, a control module and a tested system module are deployed on the server, communication connection is established between the control module and the tested system module, the current operation environment of the server is a pre-silicon environment, and the test method can comprise the following steps: adopting the control module to test a target main program of a test tool through the target main program; test task information is sent to the tested system module, and the main program is used for shielding the peripheral interface and providing simulation test data; the tested system module is adopted to perform test operation based on the test task information to obtain a test result, and the test result is sent to the control module; and receiving a test result by using a control module. The control module deployed on the server based on the pre-silicon environment and the tested system model are tested, so that the dependence on an external control terminal is thoroughly eliminated, the server of the pre-silicon environment is independently operated and tested, and a result is obtained.

The invention discloses a software supply chain vulnerability verification code generation method based on guiding fuzzy testing. The method comprises the steps that s1, a tripartite library dependency graph with a binary program as a starting node is generated; s2, performing static component analysis on the target application software component to form a component dependency graph; analyzing the component dependency graph layer by layer, and constructing an overall function call graph; s3, matching all vulnerability functions existing in the three-party component based on CVE information, calculating vulnerability function layer distance according to an overall function call graph, and performing directed utility calculation on a prepositioned function and a function priority for fuzzy test energy distribution; s4, performing key node identification and vulnerability distance calculation on a tripartite library critical function in the overall function call graph; and s5: transmitting binary static analysis results of s1 to s4 to a fuzzy test tool for directional fuzzy test. The method has the advantages of being simple in principle, easy to implement, higher in testing capacity, better in applicability and the like.

The invention discloses an automatic testing method and device based on a front-end UI and a terminal, and belongs to the technical field of front-end development testing. Comprising the following steps: detecting a first test instruction of each set of front-end UI program, controlling to carry out demand analysis, determining a function module which needs to be subjected to UI automatic test according to a demand analysis result, and determining a test target; performing automatic technology type selection, and selecting a specified test tool and a continuous integration tool; generating a compiled test case according to the determined function module needing to be tested and the test target; running the test case, and generating a test script according to the test case and an automation technology type selection result; when the test script is verified to be correct, integrating the test script into a continuous integration tool, and automatically running a test through the test script when the code of the subsequent version of the front-end UI program is submitted; and generating a test report, positioning problems and giving repair suggestions. According to the invention, the testing efficiency is improved, and the labor cost of testing is reduced.

The invention relates to the technical field of software testing, and discloses a large-model-based REST-Like API dependency analysis and test case generation method, which comprises the following steps of: obtaining API interface description information, performing semantic analysis on the API interface description information by utilizing a large language model, and generating structured semantic representation so as to identify an operation type, dependency resources and operation resources of each API; an API-resource dependency graph is constructed based on the representation, the dependency graph comprises resource nodes and API nodes, and the operation and dependency relationship between the API and resources is represented through two kinds of directed edges of a dependency edge and an operation edge; on the basis of the graph, a test case is automatically generated through resource initialization template pre-generation and recursive dependency analysis, and the core of the test case is an API calling sequence used for testing the target API. According to the method, through semantic understanding of a large model, the problem that a traditional test tool loses efficacy in dependence analysis on a non-standard REST-Like API is solved.

A quality control system may include a controller configured to be communicatively coupled with a monitoring assembly including one or more detectors. The controller may implement two or more AI quality control (AIQC) modules associated with two or more process steps for fabricating a composite material, where each of the two or more AIQC modules is associated with a different one of the two or more process steps. A particular AIQC module may receive monitoring data associated with the particular process step for a workpiece, generate quality control data using a particular AI model, and update the particular AI model based on testing data associated with the workpiece from one or more testing tools after at least the particular process step.

The invention discloses a test method, a test device, a test tool, a storage medium and computer equipment. The method comprises the following steps: in response to an instruction of executing a test task of a target application in a target scene, determining a test path of at least one to-be-tested functional component associated with the test task; identifying the type of a network communication mechanism between the to-be-tested functional components; mapping a network communication protocol of the to-be-tested functional component to a code conversion template corresponding to the network communication mechanism category to form a test script code of the to-be-tested functional component; and sequentially running the test script code of the at least one to-be-tested functional component based on the test path to execute the test task. According to the method provided by the invention, the time and workload of developing and maintaining a test tool or an engine are reduced, simulation in a real scene can be realized, state monitoring of the target application in the target scene is facilitated, and the quality of the application is evaluated more comprehensively.

Disclosed herein are systems and methods to obtain representative formation pore pressure and formation mobility from pressure measurements with a formation testing tool. In some embodiments, the method includes performing a first pre-test in which a pressure sensor measures a drawdown pressure and a buildup pressure, calculating a statistical value for the measured buildup pressure, determining if the statistical value is above or below a threshold, shutting down a mud pulser if the statistical value is above or below the threshold, and performing a second pre-test in which the pressure sensor measures a second drawdown pressure and a second buildup pressure. In embodiments, the second pre-test includes a formation fluid drawdown flow rate that is different than a formation fluid drawdown flow rate in the first pre-test.

The invention provides a method and a device for testing compatibility of a server operating system, which can improve the speed and the quality of compatibility testing. The server operating system compatibility test method comprises the following steps: acquiring a task script and test parameter configuration; wherein the task script comprises a process of testing the compatibility of the operating system, and the process of testing the compatibility of the operating system comprises at least one of downloading a test script, configuring an offline source, installing a test tool, initially preparing an environment and executing an actual test; generating an assembly line task based on the task script; starting an assembly line task based on a test instruction and the test parameter configuration; wherein the assembly line task runs on a server for deploying an assembly line, and the server for deploying the assembly line and the server to be tested are in the same network environment; and based on the started assembly line task, performing assembly line testing on the to-be-tested server.

The invention discloses a chip prototype verification method and device, a medium and a product, relates to the technical field of chip design, is applied to a hardware debugger of a simulation test tool, and comprises the following steps: analyzing a capability maturity model script; the analyzed script and the execution mode switching condition are sent to a central processing unit of the field programmable gate array, so that the central processing unit determines a current execution mode according to the analyzed script and the execution mode switching condition; test case codes of different execution modes in the capability maturity model script are stored in different data areas of a preset memory pool respectively, so that a central processing unit obtains the corresponding test case codes based on the current execution mode, verification data are generated according to the test case codes and peripheral equipment of a pre-configured chip, and the verification data are stored in the preset memory pool; returning the verification data to a hardware debugger of the simulation test tool; and generating a prototype verification report based on the verification data and the expected data to complete chip prototype verification. And chip prototype verification can be realized by dynamically switching verification modes.

This invention provides a method for modeling the starting performance of a marine gas turbine. First, a gas turbine aero-thermodynamic performance calculation model is established using C++, and a heat transfer model, temperature sensor model, and control law model for the gas turbine's high-temperature components are established using the M language. Then, based on test data from the gas turbine startup process, the method analyzes how the pressure ratio and efficiency of typical gas turbine components change with the physical speed of the gas generator during startup. The corresponding low-speed characteristics of the gas turbine's rotating components are generated and corrected, enabling high-precision, real-time simulation of the gas turbine's starting performance. This method considers the heat exchange between the high-temperature fuel gas and the ambient atmosphere and the gas turbine itself, improving the accuracy of the gas turbine startup performance simulation. The method can provide a simulation testing tool for the design and optimization of gas turbine startup control laws.

The invention provides a large model assisted Fuzz test Harness generation method and system, and the method comprises the steps: migrating a library of a QNX platform to a Linux environment for operation, and carrying out the glue code packaging of interface difference and system call difference through the generality that the library of the QNX platform and the Linux environment share a POSIX standard, thereby achieving the automatic adaptation of key API and context constraint; then analyzing binary semantics by means of an intelligent Agent constructed by a large model, automatically generating a Harness skeleton, focusing potential dangerous points (such as memory management, character string processing functions and the like), generating an initial seed in combination with a static or dynamic analysis result, and finally executing a Fuzz test in a controllable execution environment. And high coverage and rapid vulnerability positioning of the multi-dimensional attack vector of the target library are realized. The technical problems that Harness writing highly depends on expert experience, a customized generation strategy for target binary semantics is lacked, and comprehensive understanding on the binary semantics and context constraints is lacked are solved.

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 discloses a software outsourcing-oriented heterogeneous code warehouse intelligent coupling degree detection system and method, and relates to the technical field of software engineering.The method comprises the steps that an instruction is detected, and code file information, dependency information and development log information are obtained through a distributed crawler module, an abstract syntax tree analysis tool and a natural language processing module; carrying out modular segmentation on the code file by utilizing semantic coupling analysis, inputting the code file into a large language model equipped with a LoRA adapter, identifying a coupling inverse mode, and carrying out preliminary optimization based on a quantum heuristic coupling optimization algorithm; after optimization, a multi-user concurrent scene is simulated through digital twin simulation, and the coupling degree is dynamically detected; meanwhile, a cross-language interface testing tool is used for testing interface compatibility and call chain coupling; the system comprises an information acquisition module, a semantic coupling analysis module, a quantum optimization module and a coupling degree detection module, provides a deep optimization basis for developers, and improves the coupling degree detection and optimization efficiency of the heterogeneous code warehouse.

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 solid state disk performance testing method and device and a storage medium. The solid state disk performance testing method comprises the steps that multiple to-be-tested solid state disks and multiple testing machines are obtained; determining a test sequence of the to-be-tested solid state disk, a target performance test tool and an execution sequence of the target performance test tool based on the test rule; performing repeated read or write test on the to-be-tested solid state disk based on the test sequence and the execution sequence; reading target performance test tool data recorded by the test machine in the test process, and performing fluctuation anomaly detection based on the target performance test tool data to obtain a detection result; adjusting the target performance test tool and the corresponding execution sequence based on the detection result, and continuing to test after adjustment to obtain a test result; and carrying out data processing based on the test result and the double capacity of the solid state disk so as to carry out multi-capacity-based visual display on the test result. In the mode, the convenience of performance problem reason analysis is improved, and the complexity of a processing flow is reduced.

The invention discloses an automatic testing system and method for a modular interface, and relates to the technical field of interface testing, and the system comprises an interface analysis module which is used for loading a to-be-analyzed interface document and extracting interface basic information from the to-be-analyzed interface document; the test case generation module is used for generating test cases of normal and abnormal scenes based on the interface basic information and a preset case template; the interface information comparison module is used for automatically detecting updating of an interface document, positioning changed content and synchronously updating a test case before the test is executed; the test execution module is used for executing an interface test by calling a test tool or a built-in Selenium interface automation framework; the test data analysis module is used for collecting test data generated in a test process in real time, and calling AI model analysis to quickly position an interface error reason; and the test document output module is used for summarizing the test data and the AI analysis result and generating a test report in multiple dimensions. According to the invention, the test and maintenance work of various interfaces can be rapidly and accurately completed.

The invention provides an automatic testing method and system for embedded equipment and a computer readable storage medium. The automatic testing method for the embedded device comprises the steps that a test case is obtained, wherein the test case comprises at least one natural language command written by a natural language; analyzing the test case to generate a marking command corresponding to the natural language command, wherein the marking command has a text format adaptive to the test management website; based on a natural language command in the test case and a marking command corresponding to the natural language command, an operation instruction is generated through an AI test tool, and the AI test tool is constructed based on a large language model and an embedded device knowledge graph; the embedded device is controlled to execute the operation instruction, the embedded device comprises an execution mechanism, and the operation path of the execution mechanism is determined based on the operation instruction and the sensed real-time environment; and responding to the execution of the operation instruction, and generating a test result according to feedback data of the embedded device.

The invention relates to a multi-device integrated aging test method, which solves the problem that an aging room needs to be built independently in the traditional aging test by designing a movable multi-device integrated aging test cabinet, and greatly reduces the test cost. The aging cabinet can be connected with a plurality of camera devices at the same time for testing, thereby meeting the requirements of small-batch testing, and facilitating the later transition transportation. The equipment IP is automatically read and the connection is established by presetting an aging test tool, and the full-process automatic control of equipment self-inspection, parameter configuration, power-on and power-off test, high-temperature aging and the like is realized by combining a PLC control system, so that the aging process is simplified, and the operation difficulty is reduced; each power supply panel in the aging cabinet can be independently controlled at an aging control computer end, and flow control is performed through early-stage programming debugging, so that the test flexibility and accuracy are improved; the functions of automatic IP, firmware version checking and upgrading, hardware self-checking and the like are achieved in cooperation with independent order loading and placing equipment, the manual participation degree is reduced, and the production efficiency is improved. Compared with the prior art, the multi-device integrated aging test method and system provided by the invention have the advantages that the portability, automation and intelligentization of the aging test are realized, and the deployment efficiency and the test efficiency are remarkably improved.

The invention relates to a test case generation method and device, equipment, a readable storage medium and a program product. The method comprises the following steps: acquiring first data source information of target equipment in the intelligent substation and a target test model corresponding to the target equipment, and acquiring second data source information of a test tool corresponding to the target equipment, so as to generate a test case according to the first data source information, the target test model and the second data source information, the test case is used for testing the target equipment. By adopting the method, the reliability of test case generation can be improved.

The invention discloses a multi-modal-based automatic test script generation method and system, and the method comprises the steps: a user describes a test demand through a natural language, uploads an interface screenshot to carry out multi-modal input, and calls a large language model to generate an AIRTEST script; performing mode matching on the generated script by using a regular expression, extracting all picture element names, and performing reordering processing to form an element name list; the original interface screenshot and the element name list are input into the visual large model, and the visual large model is required to return standardized coordinate data; image cutting operation is executed based on the coordinate data, and actual image resources are provided for the test script; and automatically generating a. Air item folder named by a timestamp, creating a Python script file with the same name in a directory, writing a test script code generated previously, storing picture resources obtained by cutting into the item folder, and forming a complete executable test suite meeting the requirements of an AIRTEST framework. According to the invention, the core pain points of high learning cost and difficult maintenance of a traditional automatic test tool can be solved.

The invention discloses a method for automatically testing the real-time performance of a PreemptRT kernel. The method comprises the following steps of: pre-configuring a mirror image package and a test tool set of the PreemptRT kernel for a central control node to complete environment preparation; mirror image package deployment and remote environment configuration of a to-be-tested PreemptRT kernel are carried out on the to-be-tested equipment through the central control node; generating a test matrix of the to-be-tested equipment according to the test strategy, and calling the test tool set to test the to-be-tested equipment according to the test matrix to obtain a test result; and analyzing the test result through the central control node to obtain a key index of the PreemptRT kernel to be tested, and further determining whether the performance of the PreemptRT kernel to be tested is improved or not. According to the invention, the whole process of environment preparation, kernel deployment, test execution, parameter tuning and result analysis can be automatically completed, and rapid and accurate evaluation of the real-time performance change of the PreemptRT kernel is realized.

The invention provides an automatic testing method and system based on retrieval enhancement generation and a large language model, and the method comprises the steps: obtaining a plurality of previous historical test cases, carrying out the vectorization, and constructing a vector database; obtaining a new test case described by a natural language, and perfecting the new test case by adopting related contents in a retrieval enhancement generation technology index vector database; the improved test case is converted into coherent test steps, tested software is started, analysis and decision making are carried out based on a large language model, and an automatic test tool is called to automatically execute all the test steps; after all the test steps are executed, obtaining a test result and analyzing the test result by using a large language model; according to the method, the test is automatically executed and the test result is judged by simulating a real person through a large-model-driven UI automatic test technology, so that the automatic test of the natural language use case is realized, the execution and maintenance cost of the test is reduced, and the test flexibility and the coverage rate are improved.