7056 results about "Test efficiency" patented technology

The invention relates to a fuzzy testing method, device and equipment based on a large language model, and the method comprises the steps: analyzing and analyzing RFC standard documents of various network protocols through the large language model, and extracting protocol rules and constraint conditions; according to the protocol rule and the constraint condition, a large language model driving method is adopted to generate a test case conforming to protocol characteristics; and performing a differential test through the test case, and verifying the consistency between the actual software of the network protocol and the RFC standard document. According to the invention, the accuracy and security of implementation of the complex network protocol can be improved, and the test efficiency and coverage rate are optimized.

The invention discloses an integrated circuit chip test system based on an AI algorithm, and relates to the technical field of integrated circuit chip testing, the integrated circuit chip test system comprises a chip test platform, the chip test platform is in communication connection with the following modules: a data acquisition module, which is used for collecting historical test data from existing integrated circuit chip test equipment, and sending the collected historical test data to the chip test platform; carrying out preprocessing and integration on the chip test data set to obtain a chip test data set; and the model training optimization module is used for analyzing the chip test data set, learning the relationship between the chip performance and the test vector, and training a test vector AI optimization model. According to the method, by analyzing historical test data and automatically generating the optimized test vector, a redundant item-by-item test process in a traditional test is avoided, key test nodes are accurately positioned through the test vector AI optimization model, and unnecessary test steps are reduced, so that the test time is remarkably shortened, and the test efficiency is improved.

The invention discloses a test case determination method and device, a computer readable storage medium and a processor. The method comprises the following steps: identifying a source code of software by utilizing a pre-trained large model to obtain a plurality of functional modules in the software and a dependency relationship among the plurality of functional modules; in response to updating of the source code of the software, determining a code updating part in the source code; determining a test case matched with the code updating part from a test case library of the software based on the code updating part and a dependency relationship among the plurality of functional modules, the test case being used for testing the code updating part; based on a test result of the test case, adjusting a selection strategy of the test case; and re-determining the test case for testing the code updating part based on the adjusted selection strategy of the test case. The technical problem that a traditional regression test strategy is low in test efficiency is solved.

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 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 provides an automatic feedback method based on a protocol fuzz test and related equipment. The method comprises the following steps: acquiring a dynamic configuration file of the protocol fuzz test; performing real-time monitoring on the protocol fuzz test according to the protocol characteristic parameters of the dynamic configuration file, and determining a real-time data stream of the protocol fuzz test; performing multi-level feature analysis on the real-time data stream to judge an abnormal event existing in the protocol fuzz test; generating a feedback instruction corresponding to the abnormal event by performing multi-dimensional correlation analysis based on a knowledge graph on the abnormal event; and sending an exception notification mail to the user terminal according to the feedback instruction. Through an automatic mail notification mechanism, it is ensured that a tester can receive a notification immediately when a test task fails, the workload of manual monitoring is reduced, and the test efficiency is improved.

The invention discloses an automatic driving vehicle key signal testing method and system based on real data driving. According to the method, data are collected in a real road scene, test cases are automatically generated, a standard test case library is constructed, hierarchical or parallel testing is carried out in virtual simulation, hardware-in-the-loop and real vehicle environments, and result feedback and closed-loop iteration are achieved through automatic analysis. The system comprises a data collection module, a test case generation module, a standard test case library module, a test execution module and a result feedback module. According to the invention, the problems of insufficient scene coverage and low authenticity and efficiency of the existing test method are solved, the comprehensiveness, authenticity and test efficiency of the test scene are improved, and the safety and reliability of the key signal system of the automatic driving vehicle are guaranteed.

The invention provides an automatic software testing method and system based on artificial intelligence. The method comprises the following steps: analyzing a software demand document by using an NLP technology, converting the software demand document into structured data, extracting a key function point, and identifying a software function point; generating a test case covering all function points through a deep learning model in combination with historical test data training; automatically executing a test operation, analyzing a test result, analyzing a test log by using a machine learning algorithm, identifying and classifying potential defects by using a data mining and pattern recognition technology, and generating a repair suggestion report; and analyzing feedback data in the test process, dynamically adjusting a strategy according to a test result by using a reinforcement learning algorithm, and optimizing a test case and the strategy. According to the invention, intelligent analysis of test data, automatic generation of test cases and automatic execution of a test process are realized; flexible configuration and expansion can be carried out according to the actual condition of software; the test efficiency and quality are improved, and the test cost and manpower consumption are reduced.

The invention discloses a test case generation method and device, equipment and a medium, and relates to the technical field of software testing, and the test case generation method comprises the following steps: storing request data subjected to structured processing into a seed case library; the request data are various types of request data in the operation process of the service system; determining a cue word according to the target information based on the large model, and generating an initial test case through the cue word and a generation rule; the target information comprises characteristics of request data in the seed case library, an interface document of the tested software and a business logic specification; executing the initial test case according to the test request of the tested software, performing statistical analysis on the code coverage rate of the tested software in the execution process, and screening the initial test case according to an analysis result to obtain a screened test case; and after the execution is finished, filtering the screened test cases according to the first execution result of each test case to obtain a target test case. Therefore, the testing efficiency and quality can be improved, and automatic testing is achieved.

The invention provides a multipath solid-state power controller detection device and method, and belongs to the technical field of integrated testing and fault diagnosis, and the device comprises an MCU control circuit module which is used for achieving the full-process automatic control and data analysis of the testing device; the load control module is used for controlling a load environment provided in a test process; the data acquisition circuit module is used for acquiring an SSPC channel, a switching value, a small voltage signal and a current signal; the power circuit module is used for providing power; the communication interface circuit module is used for communicating with the outside; and the display screen and key circuit module is used for man-machine interaction in the detection process. According to the detection device, SSPC all-condition performance verification is realized through multi-channel synchronous excitation, distributed data acquisition and dynamic loading; the core pain points of low test efficiency and difficult fault positioning of the multi-channel SSPC board card are solved.

The invention relates to the technical field of wiring terminals, in particular to an intelligent testing method and system for the contact resistance of a wiring terminal, and the method comprises the following steps: adjusting the resistance testing frequency according to the environment temperature to adapt to different conditions, combining current and voltage data, analyzing the historical change trend of the resistance, predicting the potential change range, and obtaining the contact resistance of the wiring terminal through the current and voltage data. Evaluating the mutual influence with the resistor, judging the abnormal reason of the resistor, adjusting a test scheme according to fault diagnosis, predicting potential faults, and making a test plan. According to the invention, through environment induction and data analysis, the resistance test frequency is adjusted in real time to adapt to environment change, so that the resistance measurement in the test process is more sensitive and accurate, the response speed and data quality of the test process are improved, historical and current resistance data are automatically analyzed, potential faults can be effectively predicted and identified, and the test efficiency is improved. Problems caused by operation errors are reduced, and a prospective fault prediction function enables the adjustment of the test period to be more scientific.

The embodiment of the invention provides a security authentication method, device and system for a test platform, and a storage medium, and relates to the technical field of network security. The method comprises the following steps: performing fingerprint acquisition on virtual and real equipment to generate a unique identifier, dynamically slicing based on a software defined network to form an isolated test environment, and injecting a zero-trust access strategy associated with the fingerprint; and based on the zero-trust access policy and the device fingerprint, allocating a minimum permission through an attribute-based access control model, continuously evaluating device behaviors to calculate a dynamic trust score, and adaptively updating the permission according to the trust score. By constructing a full-process security certification system and through multi-dimensional mechanism cooperation, dynamic risk perception and timely strategy adjustment, fine-grained control of virtual and real equipment access in an industrial control scene is realized, the dynamic adaptability and risk resistance of a test platform in a complex network environment are improved, and the test efficiency is improved. Equipment access safety, authority distribution minimization and behavior monitoring continuity are ensured, and the safety risk of the industrial control system is reduced.

The invention provides an API test case generation method and device based on neural symbol reasoning and a readable storage medium, and the method and device extract a parameter mode through a neural semantic analyzer, verify complex constraints in combination with a symbol rule base, and dynamically adjust the weight of neural generation and symbol verification through a dynamic coordinator, thereby achieving efficient and compliant test case generation. And when the constraints conflict, the reverse reasoning module generates parameters and abnormal data which violate the constraints, and supports nested constraint analysis and dependency analysis of the RESTfull / GraphQL / gRPC protocol through a multi-protocol adapter. Experiments show that the maximum generation speed of the use case can reach 2100 / s, the constraint violation detection rate is 98% +, the CPU occupation is only 38%, and the test efficiency and quality are remarkably improved.

The invention relates to a system and a method for testing the conductivity of an engine wire harness, and relates to the field of intelligent detection, a programmable switch matrix is formed by acquiring a wire harness layout diagram and arranging matrix relays, and after logic self-inspection is executed, an optimal conduction path is searched based on a hierarchical partition model and a DFS algorithm; according to the method, the path image sets of the partitions are overlapped and mapped to identify abnormal wire harness sections, and finally, abnormity is determined through analog signal injection and waveform analysis and physical repair guidance is performed, so that the technical problems of low test efficiency, poor flexibility and difficulty in adapting to complex variable wire harness layout conductivity test are solved, and the purposes of improving the test flexibility and efficiency and reducing the test cost are achieved. And a fault point can be accurately positioned.

The invention relates to the technical field of power electronic equipment testing, and discloses a special intelligent testing device and method for a power UPS, and the device comprises a multi-source power supply system which comprises a three-phase program-controlled variable-frequency power supply, a single-phase program-controlled variable-frequency power supply and a DC program-controlled power supply, the output voltage of the three-phase program-controlled variable-frequency power supply is 0-480V and is adjustable, and the output voltage of the single-phase program-controlled variable-frequency power supply is 0-480V; the output voltage of the single-phase programmable variable-frequency power supply is 0-280V and the frequency of the single-phase programmable variable-frequency power supply is 45-64Hz and adjustable; the output voltage of the direct-current programmable power supply is 50-1000V and adjustable; an electronic load system; a signal acquisition system; an embedded control system; and an upper computer software system. A three-phase program-controlled variable-frequency power supply, a single-phase program-controlled variable-frequency power supply and a direct-current program-controlled power supply are integrated to form a multi-source power supply system, a resistive and rectifying dual-mode electronic load is combined, millisecond-level synchronous switching of a voltage level and a load state is realized through an embedded control system, a closed-loop test capability of multi-dimensional performance of the power UPS is formed, and the test efficiency is improved.

The invention discloses a coordinated regulation and control system and method for dynamically testing pod environmental parameters, and the system comprises a multi-source sensor array which comprises a plurality of sensors used for collecting various environmental parameters in a pod in real time; the central controller is used for fusing sensor data and digital twinborn prediction information in real time through an FPGA + GPU heterogeneous architecture, dynamically generating and optimizing a regulation and control strategy based on a deep reinforcement learning algorithm, and synchronously coordinating an execution mechanism group to realize multi-physics field coupling control; the digital twinning interface is used for synchronizing the physical test environment and the bidirectional data flow of the digital twinning interface in real time, calculating and predicting the environment parameter evolution trend based on multi-physics field coupling, and feeding back closed-loop correction model parameters through reinforcement learning; and the execution mechanism group is used for adjusting the environmental parameters according to the control instruction. The system has the testing environment control functions of multi-parameter coordinated regulation and control, low-delay dynamic response and intelligent optimization capability, and the accuracy and testing efficiency of complex working condition simulation can be improved.

The invention discloses a test method of a server system, a storage medium, electronic equipment and a program product, and relates to the technical field of computers, and the method comprises the following steps: firstly, obtaining an equipment feature vector of a to-be-tested server system; performing fuzzy matching on the equipment feature vector and a feature description vector capable of performing server system testing in a driver library; if the matching is successful, collecting hardware characteristic parameters of the server system to be tested, and dynamically determining a test threshold value of the hardware state of the server system to be tested according to the environment parameters monitored in real time; and then testing the hardware state of the to-be-tested server system based on the hardware characteristic parameters and the dynamically determined test threshold. Compared with the prior art, automatic identification and adaptation of multi-manufacturer hardware equipment are realized, the time of manual intervention and the complexity of drive configuration are remarkably reduced, the test cost is further reduced, the test efficiency is improved, and meanwhile, the test accuracy and flexibility are also improved.

The invention relates to the technical field of automation equipment, and discloses a three-temperature test sorting machine, which is characterized in that a heat preservation cover is arranged on a workbench, and a test space is formed by the heat preservation cover and the workbench, so that the consistency of temperature in the test space can be ensured, a chip is uniformly heated in the test space, and automation of three-temperature test of the chip is realized. The temperature of the chip is adjusted in advance by additionally arranging the pre-heating device, so that the whole chip is heated more uniformly, and meanwhile, the waiting time is fully utilized to adjust the temperature in advance, so that the test time is saved, the accuracy of a chip test result and the stability of a test yield can be ensured, and the test efficiency is improved. Moreover, the test efficiency is improved, and large-scale popularization and application are facilitated.

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 relates to an intelligent cabin software testing method and device, an intelligent cabin and a vehicle. The method comprises the following steps: acquiring a test requirement document of the intelligent cabin software; according to the test demand document, generating a decision tree and a dynamic demand graph corresponding to the test demand document; generating a function knowledge graph corresponding to the intelligent cabin software according to the decision tree and the dynamic demand graph corresponding to the test demand document; according to the function knowledge graph corresponding to the intelligent cabin software, generating a test case of the intelligent cabin software; and according to the test case of the intelligent cabin software, generating and executing a test script of the intelligent cabin software to obtain a test result of the intelligent cabin software. According to the method, the automatic process of compiling the test case and generating the test script can be realized, and the test efficiency of the intelligent cabin software is improved.

The invention provides a vehicle software testing method and device based on a large model, and relates to the technical field of software testing, and the method comprises the steps: obtaining the testing demand information of to-be-tested vehicle software; generating a model prompt according to the test demand information, wherein the model prompt is used for indicating to generate resources required by the vehicle software test; inputting the model prompt into the large model, and obtaining each driving scene and a vehicle software test case output by the large model; performing physical rule verification on each driving scene; determining the driving scene passing the verification as a target driving scene, and inputting the target driving scene into a simulation platform to obtain simulation data of the target driving scene; and inputting the simulation data and the test case into an automatic test platform to enable the automatic test platform to analyze the simulation data, and executing the test case according to the analyzed simulation data to obtain a test result. By applying the method provided by the invention, the test efficiency and the coverage rate can be improved.

The invention belongs to the field of material performance testing of mechanical structure strength, and particularly relates to an ultrasonic fatigue experiment monitoring method based on digital twinning. According to the method, on the basis of an ultrasonic fatigue testing machine platform, an ultrasonic fatigue digital twin model of a tested object is established by collecting frequency, temperature, load and other test data, and real-time online monitoring of ultrasonic fatigue and life prediction are carried out in combination with a fatigue life prediction model. Compared with a traditional test method, the method has the advantages that ultrasonic detection data and a digital twinborn model technology are combined, the fatigue life of the material is predicted and evaluated, the test efficiency is improved, the long-life test cost is reduced, and the accuracy and reliability of test data are improved.

The invention provides a cluster reliability test method based on fault simulation, which comprises the following steps: acquiring injection parameter information, and performing fault simulation in a cluster based on the injection parameter information and a fault transfer model to obtain a complex fault scene; key performance index records are obtained in real time based on the complex fault scene; executing a reliability detection step based on a preset reliability detection model and the key performance index record, and obtaining a data analysis report; and obtaining a reliability score, an influence analysis result and a risk prediction result based on a data analysis report, a weighted scoring algorithm, an anomaly detection algorithm and linear regression analysis, and completing reliability detection of the cluster. According to the cluster reliability test method and system based on fault simulation provided by the invention, the test efficiency and the reliability detection level are greatly improved, the fault simulation is carried out in the cluster and the reliability detection model is combined, so that the accurate quantification of the reliability detection result is realized, and the reliability detection efficiency and the detection capability are improved.

The invention discloses a solid state disk performance fluctuation test method, device and equipment and a storage medium, and relates to the technical field of performance tests.A corresponding test action sequence is generated according to a performance test instruction, a plurality of test actions are organized into a standard test process capable of being repeatedly executed, and the performance fluctuation test efficiency is improved. The influence of the difference of manual test operation execution on the test result is eliminated, the performance fluctuation test result of the to-be-tested solid state disk is calculated based on the storage performance index of the to-be-tested solid state disk in the test action sequence execution process, and objective evaluation of the performance fluctuation of the solid state disk is realized on the basis of sufficient data support. The automation and standardization of the test are realized from the two aspects of the test process and the result evaluation, and the efficiency and accuracy of the test are improved.

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 core particle testing method and system, computer equipment, a storage medium and a computer program product, and is applied to the technical field of chip testing. The method comprises the following steps: acquiring the number of module chips of a to-be-tested core particle; determining at least one test environment component matched with the number of the module chips; the at least one test environment assembly is in one-to-one correspondence with the module chips of the to-be-tested core particles; and running each test environment component in parallel, and testing the corresponding module chip through each test environment component according to a preset test case to obtain a test result of each module chip. By adopting the method, different chip specifications can be adapted, the development cost is saved, the test environment components run in parallel when the core particles are tested, and the test efficiency of the core particles is improved.

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 technical field of software development, and discloses an automatic UI function test method and system, electronic equipment and a storage medium. The method comprises the steps of receiving a natural language test requirement; intercepting an interface image in real time and transmitting the interface image to a multi-modal analysis module through an API; interface element layout is identified based on computer vision (CV), demand semantics are analyzed in combination with natural language processing (NLP), and a dynamic operation instruction set is generated; driving the automatic tool to execute clicking, sliding and input operations through the API; dynamically adjusting a test path according to execution feedback, and covering a multi-scene case; interface element states, system logs and performance data are monitored in real time, and automatic verification is achieved through multi-dimensional data comparison. According to the method, multi-modal recognition and AI intention understanding technologies are fused, the problems that a traditional UI test script is high in maintenance cost and low in scene coverage rate are solved, non-intrusive self-adaptive full-process testing is achieved, and the testing efficiency is improved by 40% or above.

The invention discloses a remote disturbance test system and method in primary frequency modulation, and relates to the technical field of power system control, and the method comprises the steps: obtaining a primary frequency modulation intelligent control system, and configuring a master-slave redundancy control device; generating and verifying a primary frequency modulation test disturbance signal, and triggering a remote disturbance test according to a verification result; the master and slave control devices respectively respond to the test and collect the power grid state signal flow, and analyze and generate a master and slave frequency modulation load instruction; evaluating and screening the master-slave load instructions by using a hardware high-selection module, and determining a target frequency modulation load instruction; and sending the target instruction to the DCS and the DEH for test recording and performance evaluation, and optimizing a frequency modulation strategy according to a test result. The technical problems of low test efficiency and insufficient accuracy caused by system complexity in an existing primary frequency modulation remote disturbance test system are solved, and the technical effects of simplifying the system structure, improving the test efficiency and remarkably enhancing the test accuracy are achieved.