409 results about "Test execution" patented technology

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

The invention relates to the technical field of network security, and discloses a multi-agent cooperative RESTful API vulnerability test method. Constructing a parameter structured representation by analyzing an API interface specification, generating a test value conforming to service semantics by using a large language model, and establishing a semantic request baseline representing normal service logic; constructing a multi-agent collaborative architecture including vulnerability reasoning, case generation, test execution, test analysis and test management; all the agents are coordinated to carry out iterative vulnerability testing through a signal mechanism and a state transition table, and API service analysis, test strategy customization, use case directional variation and execution, result study and judgment and strategy optimization are achieved; and finally generating a structured vulnerability report. According to the method, the problems of semantic blind areas, shallow analysis layers, insufficient adaptive capacity and the like are solved, security risks such as business logic vulnerabilities and sensitive data leakage in the RESTful API can be deeply detected, and the accuracy and coverage rate of vulnerability detection are remarkably improved.

The invention discloses a 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 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.

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

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

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

The invention provides a carrier rocket ground test system and method supporting visual process configuration. The system mainly comprises: (1) a visual process configuration module, which configures a test process file through a graphical interface; (2) a process analysis and scheduling module for analyzing a process file and converting the process file into a task sequence; the test execution engine module (3) is used for driving bottom hardware and executing a test instruction sequence; (4) the test resource library module is used for storing and managing various information of test elements and various information of test equipment; the execution monitoring and data management module (5) is used for displaying a test execution state in real time and recording whole-process data; according to the method, the test logic and the execution program are separated, and a user can quickly construct, modify and reuse an automatic test process in a graphical mode, so that the test flexibility is greatly improved, and the test adaptability and efficiency are remarkably improved.

The invention discloses a multi-protocol compatible intelligent test method and system for a power distribution automation terminal, and relates to the technical field of power distribution terminal test. The method comprises the following steps: acquiring basic information and historical test data of a tested terminal; automatically identifying and matching a communication protocol through a multi-protocol adaptive identification model, and generating a protocol conformance test template; according to the template, executing signal injection and collecting real-time response data, and calculating a terminal response matching degree and a protocol analysis accuracy parameter; and inputting the parameters into the test result evaluation model, and outputting a test result. Comprising an information acquisition module, a protocol identification and template construction module, a test execution and data acquisition module and a test evaluation module. According to the invention, automatic identification, standardized testing and intelligent evaluation of the multi-protocol terminal are realized, the testing efficiency, consistency and accuracy are improved, and the method is suitable for testing and diagnosis of distribution automation terminals of different models.

The invention relates to a test system based on a multi-modal knowledge base, belongs to the technical field of software testing, and solves the problems of insufficient reuse of historical project data and expert knowledge, lack of professional domain knowledge, illusion, low test case adoption rate and low practicability. The system comprises a knowledge base construction module used for constructing a hierarchical multi-mode professional field knowledge base; the preprocessing module is used for forming a standardized project development document and a software source code file of a to-be-tested project; the test case generation module is used for generating a test case and a software test description thereof based on the multi-modal professional domain knowledge base, the project development document of the project to be tested and the software source code file; and the test execution module prepares execution conditions according to the test case and the software test description thereof, and then executes the software test steps in sequence according to the input and operation description steps described by the test process to obtain an execution result of the test case. And knowledge-based and deep structured multiplexing of test assets is realized, and the test quality and efficiency are improved.

A method for testing an electrical device installed in an energy system includes: receiving an identifier and a test identification (testID) associated with the electrical device; validating the identifier and the testID; in response to determining that the electrical device is registered and communicating: setting and storing a polling rate and a posting rate of the electrical device, setting a first plurality of pre-conditions associated with a first test, and in response to determining that the first plurality of pre-conditions is met, performing the first test by: executing a first set of test commands associated with the first test, receiving responses to the first set of test commands of the electrical device, determining first test results based on the responses to the first set of test commands, storing the first test results, and determining whether the electrical device has passed the first test.

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 relates to the technical field of material corrosion tests, in particular to a thermal shock test system for a turbine blade coating. The turbine blade coating thermal shock test system comprises an environment simulation subsystem and a test execution subsystem, the environment simulation subsystem is used for generating a gas flow, a gas outlet of the environment simulation subsystem is communicated with a gas inlet of the test execution subsystem, and the test execution subsystem comprises a test part and a test piece bearing mechanism. The test piece bearing mechanism comprises a test piece fixing assembly and an angle adjusting assembly, the test piece fixing assembly comprises a test bed and a test piece clamp, the bottom end of the test piece clamp is fixedly connected with the driving end of the angle adjusting assembly, and the test piece clamp is used for fixing a turbine blade test piece; the angle adjusting assembly is used for driving the test piece clamp to drive the turbine blade test piece to deflect to a preset angle. According to the turbine blade coating thermal shock test system provided by the invention, deflection of the turbine blade test piece in high-temperature combustion gas flow can be realized, and the working state of the rotatable guide vane is truly simulated.

The invention relates to the technical field of vehicle testing, and particularly provides a test case sorting method and device, a medium, equipment and a product, and the method can comprise the steps: inputting a feature vector corresponding to each test case in a plurality of test cases of a vehicle software system into a pre-trained large language model, obtaining a semantic feature vector of each test case; scoring the semantic feature vector of each test case by using a priority ranking model to obtain a score of each test case; and sorting the plurality of test cases based on each test case score to generate a test execution sequence. According to the embodiment of the invention, the high-value test case can be accurately identified, and the test precision is improved.

The invention relates to the technical field of software engineering and automatic testing, and discloses a self-adaptive multi-dimensional risk testing strategy design method and system and a storage medium. The method comprises the following steps: triggering a risk assessment service through a CI / CD assembly line, preprocessing original data obtained by a plurality of heterogeneous data sources, and generating a risk feature vector; outputting a multi-dimensional risk index by using the risk assessment model, fusing the multi-dimensional risk index and the dynamic weight thereof based on an adaptive weighted fusion model, and calculating a comprehensive risk score; dynamically updating a risk score threshold value used for dividing the risk level, automatically generating a test strategy matched with the current risk level according to a preset mapping rule of the risk level and the test strategy, and calling the test suite to automatically execute the test strategy; and collecting a test execution result and online operation data as training data, and regularly optimizing parameters of the risk assessment model. The test strategy can be dynamically adjusted according to the real-time risk situation.

The invention relates to the technical field of software quality assurance, and discloses an internet-based software engineering automation test system, which comprises a test environment perception module, a test intelligent arrangement module and a test execution and optimization module, a server resource state, a network delay parameter and a code structure feature are collected in real time through an environment dynamic sensing module, a multi-dimensional environment adaptation degree evaluation model is constructed, and when it is detected that the environment adaptation degree is lower than a threshold value, container resource expansion and network strategy adjustment are automatically triggered; establishing a mapping relation between multi-level defect features and code modules through a defect root positioning system, searching an optimal diagnosis scheme in a strategy space by applying an improved particle swarm algorithm, and accurately positioning a fault point to a source code line number; finally, closed-loop control of test environment self-adaption, test path self-correction and defect positioning self-optimization is realized, and the accuracy of a test result and the fault repair efficiency are improved.

The invention discloses a dynamic self-verification method based on service flow-test flow homologous heterogeneous execution. The method comprises the following steps: uniformly describing service logic and a corresponding interface test contract through a strong type of domain specific language (DSL); the method comprises the following steps: simultaneously compiling homologous DSL descriptions into stateful business workflows executed by a process engine and stateless and combinable atomic test contract sets called by a test executor by utilizing a double-path compiling engine; during operation, loose coupling synchronous triggering and execution of a service flow and a test flow are realized based on a high-throughput event bus, and real-time and high-fidelity contract verification, performance monitoring and chaos probe testing are performed on cross-system interface calling in a production environment. According to the invention, the traditional post-event and off-line integration test is converted into the in-event, on-line and continuous system endogenous capability, and the industrial problems that the complex enterprise system group integration test is difficult and the operation and maintenance monitoring is passive are effectively solved.

The invention provides an unmanned workshop automatic control method based on B / S architecture, which is used in the field of new energy battery detection, and comprises the following steps: S1, a laboratory information management system LIMS initiates a test task request; by integrating a laboratory information management system LIMS, a warehouse management system WMS, an AGV scheduling system, an equipment control system and a central database, a unified and collaborative intelligent management and control system is constructed, and full-process automatic and intelligent management from test task initiation, arrangement and distribution test, battery cell placement, AGV carrying, test execution to final ex-warehouse verification is realized. The bottleneck of a traditional system is broken through from multiple dimensions, and the new energy battery detection process is comprehensively promoted to be transformed and upgraded to be intelligent and unmanned. The battery cell information is automatically identified through code scanning, the corresponding process parameters and the test storage location are matched in a linkage mode, the detection task is intelligently generated, a traditional mode of manual instruction issuing and manual resource allocation is replaced, the labor cost is reduced, and the task processing accuracy and execution efficiency are improved.

The invention discloses an autonomous evolution type 5G protocol fuzzy test system based on a large language model, and the system comprises a protocol extraction unit which employs the large language model to analyze a 5G protocol specification document, and extracts structured protocol knowledge elements containing a message format, state machine logic and parameter constraints; the vulnerability analysis unit generates a potential vulnerability description list through big language model reasoning based on the knowledge elements; the test strategy generation unit drives a large language model to generate a targeted test case based on protocol knowledge, vulnerability description and historical test knowledge in the dynamic test knowledge base; the test execution unit executes the use case and captures a result; and feeding back an analysis result of the internalization unit, extracting a causal rule, generating new test knowledge and feeding back the new test knowledge to the knowledge base. According to the system disclosed by the invention, test targets and resources can be autonomously scheduled according to continuous updating of the knowledge base, so that the test process has an iterative optimization capability, and full-process automation and intelligentization of 5G protocol fuzzy testing are realized.

The invention discloses a cloud password service-oriented fuzzy test and compliance evaluation platform and method, and relates to the technical field of cloud computing and password security evaluation. The evaluation platform comprises a demand analysis module, a test case generation module, a fuzzy test execution module, a compliance detection module, a result fusion analysis module and a report generation module, and the result fusion analysis module is connected with the fuzzy test execution module and the compliance detection module. And the cloud password service detection module is used for carrying out association analysis on the response data, the abnormal log and the compliance detection result acquired by the fuzzy test, identifying the security vulnerability type and the compliance defect level of the cloud password service, and removing a repeated detection result. Fuzzy testing and compliance detection are organically fused, correlation analysis of the two results is achieved through the result fusion analysis module, the problems that in the prior art, the two tests are separated, and the results are difficult to integrate are solved, and the safety compliance condition of the cloud password service can be comprehensively reflected.

The invention relates to the technical field of automatic testing, discloses a fine-grained data change log management method and system for an automatic testing platform, and aims to realize high-precision, low-overhead and high-reliability log acquisition of business object field and set element change in a testing process on the premise of not modifying a testing code. The system comprises a declarative acquisition module for marking a to-be-monitored test object through declarative configuration and dynamically injecting log acquisition logic during test operation; the log processing engine is used for respectively acquiring state snapshots of the target business object before and after the test is executed, and identifying change information; the template factory component is used for packaging the identified change information, the context metadata and the timestamp according to a predefined structured data template to generate a standardized log record; and the log persistence module is used for writing log records into a lock-free annular buffer region realized based on atomic operation, and the log records are triggered by a batch coordinator of an independent thread to be asynchronously written into a main storage system in batches.

The invention provides a test case generation method and device, equipment, a medium and a program product, and can be applied to the field of artificial intelligence and the field of financial science and technology. The method comprises the steps that the difference between first version core data and second version core data is analyzed, and changed metadata is obtained; on the basis of the change metadata, semantic modeling is conducted on the old-version case data through a test case generation model, and a first test case is generated; wherein the test case generation model is constructed based on a recurrent neural network and an attention mechanism; scheduling and executing the first test case, and collecting multi-modal data in the execution process; processing the test execution data through the exception recognition model to obtain a recognition result; wherein the test execution data comprises multi-modal data, and the anomaly recognition model is constructed based on a sequence processing neural network; and according to the identification result, modifying the first test case based on an exception repair strategy to obtain a second test case.

The invention discloses an electric power information system safety test system and method, and the system comprises a test management scheduling platform, a multi-level test execution engine, a real-time lossless collection and monitoring module, an intelligent analysis and decision engine, a digital twin simulation test platform, and a system self-protection and toughness evaluation module. According to the security test system and method for the electric power information system, all-around and deep security coverage of the electric power information system is realized, the breadth and depth of vulnerability discovery are remarkably improved, meanwhile, a real-time security test with lossless business is realized, high continuity and high availability of electric power production business are guaranteed, and secondly, the security of the electric power information system is improved. The intelligent and automatic testing process is realized, and the testing efficiency and the accurate decision-making capability of safety management are greatly improved.

The invention relates to a rock mechanics testing method and system based on artificial intelligence, and the method comprises the steps: carrying out the three-dimensional scanning of a rock sample, and obtaining three-dimensional model data; sending into a convolutional neural network to analyze the surface characteristics of the rock sample, and obtaining the initial state parameters of the rock sample; according to the initial state parameters, a rock mechanics test loading scheme is formulated through an adaptive optimization algorithm, and a test execution instruction is obtained; applying a preset load to the rock sample according to the test execution instruction, and synchronously acquiring mechanical response data and a deformation image sequence; according to the deformation image sequence, constructing a full displacement field and a strain field of the rock sample, and obtaining global deformation characteristics; and based on the global deformation characteristics and the mechanical response data, identifying damage behavior parameters of the rock sample through a time sequence characteristic extraction algorithm, and obtaining a damage type. Intellectualization, data closed loop and self-evolution of the whole rock mechanics test process are achieved, and the test precision and the reliability of rock damage prediction are improved.

The invention provides a code testing method and device, electronic equipment and a storage medium, and the method comprises the steps: responding to a to-be-tested code submission operation, and generating a target test case according to a to-be-tested abstract syntax tree and a to-be-tested demand document of a to-be-tested code; generating a target UI test script corresponding to the target test case according to interactive elements in the to-be-tested code user interface; and executing a test task constructed based on the target test case and the target UI test script to obtain a test result. The labor cost and the time overhead of a test link are remarkably reduced, a rapid feedback closed loop from code submission to test execution is constructed, and the software development efficiency and the quality guarantee capability are integrally improved.

The invention provides a grouting-curing-intercepting cross-cut rapid coal uncovering method, and relates to the technical field of cross-cut coal uncovering. The method comprises the steps that drilling topological mapping is conducted on a target area, a connected gas interception and extraction network is constructed, and gas attenuation characteristics are extracted to determine a grouting permeation resistance coefficient; then, a high-pressure grouting dynamic pressurization gradient sequence is formulated, and an in-situ test execution unit is configured in a negative pressure guide reserved area; establishing a process response state diagram containing bag strength, sieve tube smoothness and crack filling test nodes, generating an optimal grouting path by adopting closed-loop feedback logic, and collecting a multiphase flow grouting response data set; and finally, generating a complete solidification curtain map by using the data set, executing a solidification-gas interception collaborative verification decision, and outputting a safe coal uncovering instruction. By means of digital closed-loop control, accurate solidification of superfine cement on coal seam microcracks and efficient interception and extraction of gas are achieved, and the safety and operation efficiency of cross-cut coal uncovering are remarkably improved.

When values of physical operating parameters can be changed without rebooting the computing platform, latency of in-system test (IST) execution of hardware components of a field (deployed) computing platform can be reduced. Tests (e.g., patterns or vectors) are executed for changed values of physical operating parameters (e.g., supply voltage, clock speed, temperature, noise magnitude / duration, operating current, etc.) to provide the ability to detect faults in hardware components.

The present disclosure relates to the technical field of material corrosion test, and particularly relates to a turbine blade coating thermal shock test system. The turbine blade coating thermal shock test system comprises an environment simulation subsystem and a test execution subsystem, the environment simulation subsystem is used for generating a gas flow, a gas outlet of the environment simulation subsystem is in communication with a gas inlet of the test execution subsystem, the test execution subsystem comprises a test part and a test piece bearing mechanism, the test piece bearing mechanism comprises a test piece fixing assembly and an angle adjusting assembly, the test piece fixing assembly comprises a test bench and a test piece clamp, a bottom end of the test piece clamp is fixedly connected with a driving end of the angle adjusting assembly, the test piece clamp is used for fixing a turbine blade test piece, and the angle adjusting assembly is used for driving the test piece clamp to deflect the turbine blade test piece to a preset angle. The turbine blade coating thermal shock test system provided by the present disclosure can realize deflection of the turbine blade test piece in a high-temperature gas flow, and truly simulates a working state of a rotatable guide vane.