4008 results about "Test efficiency" patented technology

The invention discloses a variation test method and device based on an intelligent automation script. The method comprises the following steps: extracting a statement execution sequence and a branch dependency relationship in an original source code by using a context-aware syntax tree, and generating a control flow diagram and a data flow diagram; performing code semantic analysis on the multi-dimensional code features by using a large language model, identifying potential defect types and variation rules, predicting the test efficiency of variants in combination with a deep Q learning model, and generating to-be-processed variants; performing grammar check and equivalence analysis on the to-be-processed variants to obtain effective variants, and testing the effective variants; variation test indexes are calculated, code weak points are positioned, and test blind areas are identified according to survival variants, so that a visual analysis report is generated; and iteratively generating a new test case according to the current survival variant and the visual analysis report, and testing the current survival variant by using the new test case. According to the invention, the variation test efficiency can be improved.

The invention belongs to the field of automatic driving test, and provides an end-to-end automatic driving system closed-loop confrontation test method based on a world model, and the method comprises the steps: building an end-to-end automatic driving system test platform based on the world model, providing end-to-end automatic driving system perception input information, and carrying out the modeling of a camera sensor, the accurate alignment among the multi-modal scene information is realized; constructing a traffic flow module, and providing map and scene global state information; a traffic vehicle multi-agent collaborative confrontation strategy balancing strategy convergence and strategy diversity is designed, a dense reward function is constructed and matched with an agent heterogeneous strategy adaptive adjustment method, a global exploration target is planned as a whole, and the test efficiency is improved; all the modules are integrated, an end-to-end automatic driving system to be tested is integrated, and efficient closed-loop testing is achieved. According to the method, efficient testing of the performance of the end-to-end automatic driving system can be achieved, the robustness and safety of the end-to-end automatic driving system can be evaluated, and functional defects of the system can be rapidly excavated.

The invention discloses an electronic product performance intelligent test system. The electronic product performance intelligent test system comprises an enhanced digital twinning and multi-physics field modeling system, a multi-modal perception fusion and intelligent test planning engine, a deep fault diagnosis and predictive health management feedback optimization module and a comprehensive optimization objective function framework. An intelligent and integrated test and evaluation system capable of comprehensively improving the test efficiency, the test coverage, the fault early warning capability and the product reliability can be realized.

The invention relates to a world model construction method, in particular to a high-fidelity lightweight world model construction method for an end-to-end automatic driving test, which is used for constructing a high-fidelity world model and performing knowledge distillation on the world model to solve the problems of huge parameters, low reasoning efficiency and the like of the world model. Model parameters are reduced on the basis of reserving the world model generation capability, and the reasoning efficiency is improved; a CUDA operator is developed in a user-defined mode for the bottleneck part of world model calculation, video memory allocation is optimized, and the reasoning efficiency of a high-fidelity world model is improved based on a single-device multi-thread scheduling and multi-device cooperative calculation method. According to the method, the high-fidelity lightweight world model for the end-to-end automatic driving test can be constructed, the problems that an existing world model is low in multi-modal information alignment precision, poor in cross-view and cross-frame consistency, low in reasoning efficiency and the like are effectively solved, the confidence coefficient of the end-to-end automatic driving system test process is improved, and the test efficiency of the end-to-end automatic driving system is improved. And the testing efficiency of the end-to-end automatic driving system is greatly improved.

The invention discloses a software test automation report generation optimization method which comprises the following steps: automatically registering and authenticating a multi-source test data access endpoint, uniformly collecting and normalizing test data with a multi-dimensional attribute tag, and forming a high-quality grouped data set through structured modeling and automatic clustering; further extracting event and result feature nodes, and establishing an interpretable tree rule dependency relationship; according to the method, the minimum redundancy and reusable customized rule path is generated by applying a dependency tree traversal and optimization algorithm and automatic reasoning, and the continuous adaptive evolution of the rule base among multiple projects is realized by combining conflict detection and visual interaction, so that the efficiency and expandability of data processing in a complex test scene are improved, and the test efficiency is improved. And the flexibility and automation level of report customization rule configuration are enhanced.

The invention relates to the field of computer systems, in particular to an operation stability testing method and system oriented to a heterogeneous computing system, and the method comprises the steps: constructing a system overall operation logic model comprising a resource topological structure, a task scheduling rule and a communication link matrix; identifying a key communication path according to the communication link matrix, analyzing a resource competition hotspot in combination with a task scheduling rule, and establishing an interference model library; calling a specific model instance in the interference model library according to a test target, configuring injection parameters, and dynamically applying interference in a system operation process; key performance indexes in the system operation process are collected in real time; based on the real-time monitoring data, a multi-index weighted scoring algorithm is adopted to calculate an overall stability coefficient, a robustness grade and a self-healing capability index of the system, and a stability evaluation result is generated; and generating a visual report according to the topological structure of the operation logic model, and supporting comparison and analysis of historical versions. Unified centralized management is realized, and test efficiency and evaluation accuracy are improved.

The invention provides a DFT test task management method and device, electronic equipment and a storage medium, and belongs to the technical field of chip design verifier.The DFT test task management method comprises the steps that a data model is constructed on the basis of a design module list and a test step list, the data model is used for indicating testability design DFT test steps of all design modules, and the test steps of all the design modules are stored in the test step list; the data model comprises a plurality of DFT test tasks, attributes of each DFT test task comprise a selection state, and the selection state comprises a selected state and a non-selected state; based on the interactive input, determining at least one DFT test task of which the selection state is selected as an executable DFT regression object; and according to the DFT regression object, driving a DFT test task to be executed. According to the method, the DFT test tasks are normalized through the data model, only the DFT test tasks need to be selected for making the test plan, efficient management of the DFT test tasks is achieved, and the regression test efficiency is improved.

The invention relates to the technical field of wind power, in particular to a dynamic response test method for a wind power variable pitch system. Comprising the steps of building a high-fidelity digital twinborn model, performing virtual testing and case optimization, performing physical self-adaptive testing execution, performing real-time analysis and decision-making driven by machine learning, dynamically adjusting testing stress, performing data feedback and model calibration and generating a comprehensive health report. Compared with the prior art which mainly depends on a fixed physical test process and artificial experience judgment and has the defects of low test efficiency, large resource consumption and difficulty in comprehensively covering extreme working conditions, the method innovatively introduces a high-fidelity digital twinning technology and a virtual test optimization process; according to the method, massive tests are executed in the virtual environment in a risk-free manner, and the enhanced test cases are intelligently generated, so that test forward movement and accurate optimization are realized, the pertinence and efficiency of physical tests are remarkably improved, and the test cost and period are greatly reduced.

The invention discloses an aerospace equipment data-real fusion performance test method and device based on reinforcement learning, and the device comprises a digital twin model building module which is used for building an aerospace equipment high-fidelity mechanism model fusing multi-physical field features, a lightweight digital twinborn body adaptive to reinforcement learning training is generated through a model order reduction technology; the digital twinborn model correction module is used for carrying out consistency calibration of multi-dimensional features and key physical parameter correction on the reduced-order model based on object reference data; the performance test module based on reinforcement learning actively explores a coupling scene of an extreme working condition and multiple faults in an interaction environment by constructing an attacker agent, and autonomously explores a performance boundary and a limit envelope of equipment; and the number-real fusion verification module is used for carrying out a hardware-in-the-loop point compensation test by taking the performance limit obtained by the digital test as guidance so as to assist in decision making and optimization of a test scheme. According to the method, the coverage, the safety and the test efficiency of the limit performance test of the aerospace equipment are improved.

The invention discloses a method and device for automatically generating a Java method unit test case based on AI, and the method comprises the steps: building a structured annotation specification, carrying out the automatic traversal and intelligent analysis of a Java project, extracting a method signature, a parameter type and a parameter constraint condition, constructing a test data generation model, and carrying out the automatic generation of the test case. The model is transmitted to an AI service to analyze business logic and boundary conditions, test case codes are generated, test cases are optimized and integrated to a project test directory, finally, code areas with insufficient coverage are identified through coverage rate analysis, a test completion strategy is generated, and iterative perfection of the test cases is completed. The technical problems that in the prior art, project-level automatic test case generation cannot be achieved, the generated test case cannot fully cover business logic and boundary conditions, and context relation understanding is lacked are solved, full-automatic project-level test generation is achieved, and the test efficiency and quality are improved.

The invention belongs to the technical field of software development and testing, and discloses an artificial intelligence-based software development automatic test case generation system, which is characterized in that an immune heuristic case self-repairing module is adopted, defects are regarded as antigens, antibody cases capable of being self-updated are generated by using a clone selection algorithm, and a gene rearrangement mechanism is automatically triggered when an interface is changed, so that the test efficiency is improved. The details of the use case are adjusted while the core detection logic is reserved; compared with a traditional method, the mechanism can realize use case dynamic adaptation without manual intervention, the maintenance workload is remarkably reduced, and the method is particularly suitable for a complex software system with frequent iteration; the space-time coupling test scene generation engine fuses dynamic scenes such as interaction and state transition of a module and short-time operation after precise coverage login by using a space-time convolutional network; the cross-dimension holographic use case synthesis module integrates multi-source data such as codes, hardware and user behaviors through tensor decomposition to generate a composite use case; functions and performance of software in a complex scene can be comprehensively verified, and test blind areas are remarkably reduced.

The invention relates to the technical field of data storage, and discloses a solid state disk total write-in data volume testing method, which comprises the following steps of: initializing a testing environment and self-adaptive parameter configuration of a solid state disk; creating a plurality of parallel data acquisition threads, acquiring test data through the data acquisition threads, and storing the acquired test data into a database; establishing a preset health degree evaluation model, analyzing the collected test data in real time according to a preset health degree index system, dynamically adjusting a test load based on a dynamic acceleration stress model and according to the real-time state of the solid state disk, executing a corresponding test operation according to an adjustment result, and recording a test result; and analyzing the test result, and automatically generating a test report according to the analysis result. According to the method, the dynamic acceleration stress model is introduced, so that the test load is dynamically adjusted according to the real-time state of the SSD, and the test efficiency and accuracy are improved.

The invention belongs to the technical field of fatigue testing, and discloses a testing machine phase difference optimization method and system and a rubber product fatigue testing machine. The method comprises the steps of presetting a loading path signal, collecting sensor data, and performing feature extraction on the sensor data to obtain phase difference features; taking the parameters of the test piece and the phase difference characteristics as input of a dual-channel lightweight model, and obtaining a phase difference predicted value of each channel; based on a multi-target dynamic parameter optimization algorithm, control parameters of the test machine are optimized and adjusted in combination with the phase difference predicted value and the inter-channel coupling characteristics; the strain distribution of the test piece is monitored in real time, and when the strain unevenness is larger than a preset strain threshold value, channel load redistribution is triggered, and the phase difference is optimized again; according to the invention, test piece characteristics and loading path changes can be sensed in real time, the phase difference prediction error is reduced, the test efficiency is improved, the energy consumption is reduced, and the authenticity of multi-axis load simulation, the phase control precision and the comprehensive performance of the system are remarkably improved.

The invention relates to an alarm rule automatic generation and closed loop optimization method and system, and relates to the field of computer system monitoring and testing. The method comprises the following steps: acquiring and cleaning a cluster to generate a standardized enhanced alarm event table based on multi-source heterogeneous data fusion; performing feature extraction on the enhanced alarm event table, constructing a feature vector, performing feature importance analysis on the feature vector by using a tree model, and outputting the feature importance analysis; according to statistical distribution of features in the structured feature vector, automatically generating a rule for identifying an alarm scene in combination with business knowledge; converting the alarm scene rule into a structured format, performing logic conversion through a test case generation engine, and outputting an automatic test case; and executing the automated test case and verifying the accuracy of the automated test case so as to dynamically optimize and adjust the alarm scene rule. According to the method, automatic rule generation and closed-loop optimization of a complex alarm scene can be realized, the alarm test efficiency and the scene recognition accuracy are remarkably improved, and the manual intervention requirement is reduced.

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

The invention relates to the technical field of optical communication, and discloses an optical module adaptive test and rapid convergence method based on reinforcement learning, which can dynamically generate and execute an optimal test sequence for optical modules of different types or states through an off-line trained RL intelligent agent module, avoids redundant steps in a fixed process, and improves the test efficiency. On the premise of ensuring the test coverage, the test time is obviously shortened, and meanwhile, the detection probability of potential defects is improved; through the closed-loop test of the integrated RL intelligent agent module, the test action can be adjusted in real time according to the state of a single optical module, so that the test process can quickly adapt to the individual difference and process fluctuation of the device, the online quick convergence of the test strategy is realized, and the accuracy and stability of the test are guaranteed; and through online iterative optimization of the RL agent module, new data and new changes in the production process can be continuously learned, so that a test strategy is continuously evolved, and the optimal performance is kept for a long time.

The invention discloses a function switching device for transformer testing and a testing system thereof, relates to the technical field of transformer testing, is used for solving the problem of low testing efficiency, and is used for setting a switching time reference by acquiring transformer capacity information and detecting the number of closed relays of testing nodes and loop resistance. Analyzing a resistance fluctuation index and loop harmonic characteristics by combining historical loop resistance data, correcting a switching time reference, detecting three-phase winding current, generating a current balance index, evaluating a fault risk level, screening and marking to-be-tested nodes according to the fault risk level, and after the current test node is tested, determining the current test node according to the fault risk level. And performing test processing on the marked to-be-tested nodes based on the corrected switching time reference, thereby realizing intelligent selection of a transformer test sequence, improving test efficiency and ensuring electrical state stability and test precision of each test node.

The invention discloses a knowledge extraction and envelope coverage-oriented software vulnerability test method and related equipment, and the method comprises the steps: obtaining vulnerability key information of target software, and obtaining sensitive function features through defect dependence analysis and construction based on the vulnerability key information; performing semantic analysis on the analysis report and the code abstract associated with the sensitive function characteristics, screening to obtain a target sensitive function, performing path envelope reverse tracking on the target sensitive function, and constructing to obtain a target path envelope; and obtaining coverage information enveloped by the target path, and carrying out fuzzy testing on the basis of the coverage information in combination with the iteratively optimized variation sample. According to the method, through intelligent closed loop of analysis-positioning-testing-feedback-optimization, static analysis provides accurate guidance for dynamic testing, and the static analysis strategy is inversely optimized by the result of the dynamic testing, so that the maximum improvement of the testing efficiency and the vulnerability discovery accuracy is realized in limited testing resources, and the testing efficiency and the vulnerability discovery accuracy are improved. The method can be widely applied to the technical field of software security.

The invention belongs to the field of software testing and defect detection, focuses on reliability verification of a physical simulation engine, is suitable for scenes depending on physical simulation, such as robot simulation, automatic driving testing, unmanned aerial vehicle control, education and scientific research, and particularly relates to a variation-based physical simulation engine defect detection method. Potential defects of core modules of collision detection, mechanical calculation, dynamics and the like are efficiently found through a variation test method. According to the method, a feature library is constructed through static library API analysis and AST / IR code analysis, test code expansion is performed by utilizing a large model, a test driver adaptive to a specific data type is generated, a physical semantic constraint mutation seed is combined, a test is executed through libFuzzer, defect and coverage rate data are analyzed, a use case selection strategy is optimized, and the test efficiency is improved. Defects of core modules such as collision detection and dynamic solution are efficiently detected, and the test pertinence and efficiency are improved.

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 relates to a robot full-automatic test system and method, and belongs to the technical field of robot test.The system comprises a test case management module, a voice instruction generation and sending module, a to-be-tested robot, an image acquisition module, an action monitoring module, a test result judgment module and a data storage module; all the modules cooperate to automatically operate the to-be-tested robot in the whole process, so that the test period of the to-be-tested robot is shortened, the test efficiency is improved, and the input cost is reduced.

The invention relates to the technical field of oil product detection, in particular to a full-automatic condensation point determinator and a determination method.The full-automatic condensation point determinator comprises a base and a test tube, the top of the base is fixedly connected with a mounting base, the surface of the base and the surface of the mounting base are provided with a test bath mechanism and a supporting mechanism, and the test bath mechanism enables a motor to drive a test bath to rotate; the rotation angle of the motor is controlled through a preset program, precise positioning is achieved, the tedious operation of hole-by-hole adjustment of the original structure is avoided, the rotating shaft is locked through mechanical clamping, angle deviation in the testing process is prevented, then manual adjustment is replaced by the motor and the electric push rod, and the test efficiency is improved. The double locking effect is achieved, accidental displacement can be prevented, and precision and efficiency are improved; according to the clamping mechanism, the four arc-shaped clamping plates apply uniform radial pressure through the first springs to clamp the outer wall of the test tube, the inner diameters of the clamping plates are gradually increased from top to bottom, and the clamping mechanism is compatible with test tubes with different outer diameters.

The invention discloses a single-hole cluster test method, device and equipment for cave depot water curtain holes and a storage medium, and relates to the technical field of underground engineering and water sealing.The method comprises the steps that a test instruction input by a user is received; when the test instruction is a single-hole water injection fallback test instruction, sending a single-hole water injection fallback test control signal to a programmable logic controller of the target water curtain hole through an OPC server so as to perform a single-hole water injection fallback test and collect first test data; when the test instruction is a water curtain effectiveness test instruction, water curtain effectiveness test control signals are sent to programmable logic controllers of all the water curtain holes through the OPC server, so that water curtain effectiveness tests are carried out on all the water curtain holes, and second test data are collected; and obtaining a test result according to the first test data and the second test data. According to the application, remote data acquisition and test control of the water curtain hole cluster can be realized without entering the cave depot by field personnel, and meanwhile, the test efficiency and the data accuracy are improved.

The invention belongs to the technical field of central control screen performance testing, and particularly relates to a new energy automobile central control screen performance testing device which comprises a dynamic extreme environment reproduction cabin, a bionic man-machine interaction behavior simulator, a multi-modal parameter synchronous acquisition array, an intelligent decision-making level analysis and evaluation engine and a holographic visualization decision-making support terminal. Physical environment support is provided through the dynamic extreme environment reproduction cabin, environment parameters of the dynamic extreme environment reproduction cabin are synchronized to the multi-modal parameter synchronous acquisition array in real time through the CAN bus, and operation data generated by the bionic man-machine interaction behavior simulator and performance indexes acquired by the multi-modal parameter synchronous acquisition array are preprocessed by the edge computing node and then are transmitted to the multi-modal parameter synchronous acquisition array. The holographic visual decision support terminal is transmitted to the intelligent decision level analysis and evaluation engine through the gigabit Ethernet, and an evaluation report generated by the intelligent decision level analysis and evaluation engine drives the holographic visual decision support terminal to display a result, so that the construction of a closed-loop test system is realized, the test efficiency and the performance evaluation accuracy are remarkably improved, and the automation level and the intelligent level are high.

The invention provides an automatic simulation test system and method for a semiconductor EAP system, and belongs to the field of semiconductor manufacturing, and the method specifically comprises the steps: defining a test scene through test case coding; constructing a test environment by using the equipment simulation module and the external system simulation module; driving a test process of the tested EAP program through an automatic execution engine and generating real-time output data corresponding to the tested EAP program; and comparing the real-time output data generated by the automatic execution engine with an expected result, and generating a test report. According to the processing scheme, behaviors of equipment and an external system are truly simulated in a software simulation mode, an actual production scene is accurately restored in a test link, dependence on a physical environment is reduced, and test coverage is improved; and moreover, the test scene is solidified through codes and configuration files, so that the versioning management and one-key automatic regression test of the test cases are realized, the test efficiency is remarkably improved, and the quality of secondary development is guaranteed.

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

The invention relates to a lubricating grease porous material permeability test device, and relates to the technical field of material performance analysis, the device comprises a placing table for placing a sample, the placing table is provided with a driving device and a test seat, and the test seat is provided with a test cavity; the driving device is used for driving the testing seat to move in the direction close to the placing table so as to contain the sample into the testing cavity; a sensing device used for sensing lubricating grease below the sample is arranged on the placing table, a sealing device used for sealing the peripheral wall of the sample is arranged in the testing cavity, a conveying device used for conveying the lubricating grease to the position above the testing cavity is arranged on the placing table, and a pressurizing device used for applying pressure to the lubricating grease above the sample is arranged on the placing table. The multiple steps of sample clamping, sealing, grease injection, pressurization and detection are integrated into a coherent automatic process, the test efficiency is remarkably improved, the consistency of test conditions is ensured through mechanical positioning and automatic control, and high repeatability and high reliability of test results are ensured.

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.

According to the cold region slope multi-field coupling effect simulation test device and method, the device is composed of a freeze-thaw environment test box, a slope model, an anchor rod axial loading system, a crack water injection assembly and a multivariate data monitoring system, and the multi-physical field coupling effect of freeze-thaw cycle, crack water permeation and long-term creep can be simulated. By dynamically adjusting the temperature gradient and graded loading parameters, data of a stress field, a temperature field and a displacement field can be collected in real time, the influence of different freeze-thaw conditions and creep drawing loads on a slope damage mechanism can be analyzed, a key test means is provided for revealing the strain rate effect, the aging deformation characteristics and the instability criterion of the slope in the cold region, and the test efficiency is improved. The method has an important guiding value for stability evaluation and disaster prevention and control of the cold region slope engineering.

The invention belongs to the field of automatic testing, and particularly relates to an automatic testing system and method for aviation fly-by-wire flight control equipment, and the system comprises a system self-inspection unit, a system resource unit, a system interface adaption unit, and a system testing control unit. And the system self-checking unit controls the automatic test system to execute a self-checking function through operation software. The test efficiency and the test coverage rate can be remarkably improved, the problem of function test omission can be effectively solved, the fault of the tested airborne avionics equipment is analyzed by adding the YMECA fault analysis module and combining the definition event and the structure function of the fault tree, qualitative analysis is carried out on the fault, a professional basis is provided for fault diagnosis, the maintenance difficulty is reduced, and the test efficiency is improved. The aircraft maintenance guarantee efficiency is improved, and joint test of a plurality of airborne avionics devices and parallel test of a plurality of airborne avionics devices of the same model in a fly-by-wire flight control system of a certain type of fighter can be realized.