498 results about "Test case" patented technology

This invention discloses a preprocessing method for highly polluted pediatric EEG data, belonging to the field of EEG signal processing technology. The invention proposes a robust motion artifact detection method based on a multi-channel voting mechanism. This method overcomes the sensitivity of single-channel detection to transient noise through multi-channel joint decision-making, automatically identifying time periods requiring restoration. A comprehensive preprocessing workflow integrating PCHIP interpolation restoration, adaptive Bayesian wavelet denoising, bandpass filtering, and independent component analysis is designed. This workflow is validated using real pediatric continuous task EEG data. This invention demonstrates excellent performance in preserving frequency band information and improving the weighted signal-to-noise ratio, achieving an average accuracy of 96.4% (205 test cases) and a maximum of 100% based on permutation entropy feature classification. This invention effectively solves the preprocessing challenge of pediatric EEG data in high-noise environments, significantly improving the accuracy and reliability of subsequent classification tasks.

The application discloses an excitation automatic generation method and system and a computer readable medium, and relates to the technical field of electronic design. The method comprises the following steps: based on a pre-acquired test case file, a target test case is acquired from a plurality of pre-stored test cases; case key information of the target test case is acquired, and the case key information is used for representing basic signals to be simulated by the target test case; and based on the case key information, an excitation signal is generated. Therefore, in the face of different target test cases, a control excitation signal with a unified style is automatically generated based on the case key information of the target test case, thereby reducing the dependence of cases on manual checking of logic functions and manual writing of excitations for the functions, and improving the design and development efficiency of integrated circuits.

This application provides a method, apparatus, storage medium, and device for network protocol fuzzing. The method introduces retrieval-enhanced generation technology into protocol fuzzing. By retrieving external knowledge, it provides context for a large language model, ensuring the accuracy of protocol specifications and thus improving the accuracy of generated test cases in protocol testing. Simultaneously, it utilizes the large language model to analyze the out-degree value of the state of the seed to be mutated, and then intelligently allocates test resources based on the out-degree value, thereby enhancing the efficiency of state space exploration. Thus, by combining the large language model with external knowledge retrieval capabilities, test cases that conform to protocol specifications and cover more protocol paths are generated, effectively improving the effectiveness and coverage of network protocol security testing.

The application discloses an industrial control system protocol fuzzing test method based on state conversion, and particularly, the communication flow of an upper computer and a PLC is analyzed, a protocol finite state machine of a communication interaction process is constructed, and the PLC is subjected to the fuzzing test by using test cases violating the finite state machine in a test process, so that the purpose of triggering unknown vulnerabilities of the PLC is finally achieved. The application uses the protocol finite state machine to guide the state conversion path of the fuzzing test process. The method for obtaining the test cases violating the original protocol finite state machine and then performing the fuzzing test on the equipment can efficiently find vulnerabilities. The confirmation method for the state conversion leading to the vulnerabilities can obtain the shortest state conversion path leading to the vulnerabilities.

This invention discloses an online editing and parallel execution method and system for vehicle network test cases, relating to the field of vehicle network testing technology. It establishes an online editing environment via a web interface, enabling automatic generation of protocol code and providing testers with a convenient and efficient development experience. Regarding test case execution, it accurately analyzes the dependencies of test cases, uses a topology sorting algorithm to construct a reasonable execution plan, and adaptively switches between sequential and parallel execution modes. Combined with containerization isolation technology, it allocates an independent execution container for each test case, ensuring the isolation and stability of the testing environment. Simultaneously, it initializes a unified test execution context for each test case and establishes a communication connection with the vehicle network bus simulation engine through a standardized interface, achieving standardization and normalization of operations such as message sending and receiving, fault injection, and assertion verification. In variable management, it adopts a copy-on-write mechanism to achieve isolated sharing of project variables, avoiding data crosstalk.

The application discloses a multicast or broadcast access register verification method and system, and belongs to the chip verification technical field, and comprises the following steps: obtaining a register model corresponding to a device under test; reloading a driver configuration global parameter of a bus agent in a multicast or broadcast test case; obtaining all register nodes in the register model according to the test case, screening all the register nodes according to a register node list to obtain a corresponding register node sequence; obtaining all registers corresponding to each register node in the register node sequence, and screening all the registers of each register node in the register node sequence according to a preset register attribute and a register name of the register list; performing write access on each register to obtain a first register, and performing read access on the first register, thereby improving the verification efficiency.

The application provides a monitoring method, device and equipment for a ufs test case and a storage medium, which are applied to a ufs verification platform, the ufs verification platform is connected to a to-be-tested device installed with ufs, the method comprises the following steps: the ufs verification platform generates at least one target instruction based on the ufs test case, sends all the target instructions to the to-be-tested device in sequence, and the to-be-tested device performs target testing based on the target instruction; the ufs verification platform writes all the target instructions and related information into a record file, wherein the related information comprises a logical unit number, a logical block address and a block number of the target instruction; the ufs verification platform generates an end signal and sends the end signal to the to-be-tested device and the record file respectively, the to-be-tested device terminates the target testing, the ufs test case is terminated, and the record file terminates writing. According to the technical scheme of the embodiment of the application, all the target instructions and related information can be recorded, so that the troubleshooting speed and efficiency of the ufs test result are improved.

This application provides a method and apparatus for generating random instruction test cases, relating to the field of automated testing technology. First, target instructions or instruction sequences are encapsulated into C inline functions using inline assembly or macro definition, forming a unified function library. Next, a function parameter constraint system is constructed, defining parameter types, address ranges, instruction combination methods, and value range constraints for each encapsulated C inline function. Then, a multi-level nested structure is built based on the C inline functions to organize the instructions, where each level node is associated with a corresponding C inline function name and constraints. Finally, based on a YAML configuration file, the target C inline functions are determined from the multi-level nested structure and combined to generate random instruction test cases. The YAML configuration file includes at least the number of iterations, a random seed, a random strength factor, and test content configuration. The solution provided in this application has the advantages of improved verification efficiency and applicability to different scenarios.

The application discloses a reliability evaluation and optimization method and system for large model function code, a medium and a program product, and belongs to the technical field of artificial intelligence. A demand prompt word, a test case and expected output are acquired to form a standardized test data set; an execution consistency score, a semantic consistency index and a static structure consistency index of the code to be evaluated are calculated and fused into an intention consistency comprehensive score; a safety score is obtained by performing static safety analysis on the code to be evaluated; the intention consistency comprehensive score and the safety score are fused into a final comprehensive score, and the reliability is judged; if the reliability is not good, a defect label is generated according to the scores of the indexes and weighted fusion is performed to obtain optimization guidance information, and the code is corrected or regenerated according to the information. The application comprehensively evaluates the code quality from four dimensions of execution, semantics, structure and safety, highlights the short board effect by adopting a fusion strategy, realizes closed-loop automatic optimization, and significantly improves the reliability and safety of the function code.

The application discloses a kind of interface test case generation method, device, equipment and medium.The method comprises the following steps: obtaining the standardized demand template of prewritten relative to the interface to be tested;According to the set analysis rule, the standardized demand template is analyzed, and the flow chart corresponding to the interface to be tested is generated;According to flow chart, in combination with the interface element coordinate library of pre-determined interface to be tested, the interface test case of interface to be tested is generated.Through the method, standardized demand template is provided for tester, and the flow chart of the requirement corresponding to the interface to be tested is generated according to standardized demand template, the interface element in the interface to be tested is automatically converted into corresponding coordinate, according to flow chart and interface element coordinate library, interface test case is automatically generated, the process of manual click interface to be tested for recording is saved, the generation efficiency of interface test case is improved, and the problem that interface test case conflict is caused by the difference produced by artificial recording is avoided.

The application belongs to the field of trusted software security testing, and discloses a putty trusted software testing method and system based on Python. The application replaces traditional manual operation with an automatic control mode taking Python as the core, so that the full test process of the SIS (Supervisory Information System) safety and trusted infrastructure can be quickly carried out after the version is released. The application automatically processes test case analysis, command execution, output collection, matching judgment, screenshot recording and report generation, thereby avoiding the cumbersome process of manually executing test instructions, manually comparing outputs, manually taking screenshots and manually arranging test documents.

Embodiments of the present disclosure disclose a processing resource allocation method, device, medium and equipment. In the test process, the test cases with the same identifier set are divided into the same set according to the identifier set of the test cases, and the target processing resource is allocated to each test case set according to the total processing resource demand of each test case set and the corresponding pre-allocated processing resource, so that the test cases included in each test case set are tested by the target processing resource, thereby avoiding the problem that the test process cannot be normally performed due to unreasonable allocation of processing resources, even error, and improving the overall utilization of processing resources.

The application provides a communication feature model driven relay protection device automatic test method and system, comprising the following steps: 1. Through active detection and response analysis, the communication protocol type, message format and function code mapping relationship of the relay protection device are identified, and a device communication feature model is constructed; 2. Based on the device communication feature model, test cases covering function verification, abnormal processing and boundary conditions are dynamically generated, and automatic mapping of the test cases and the device and execution sequence optimization are completed. The technical scheme can solve the problems of relay protection device test dependence on manual configuration, low efficiency and poor adaptability.

The application belongs to the field of trusted system testing, and discloses a kind of SIS trusted system booting trusted function test method and system, the application is by automatically constructing test environment and centralized configuration test case on automation test host, so that test process does not need manual setting device parameter one by one, avoid the problem of omission and inconsistency caused by manual configuration, improve the efficiency and accuracy of test preparation stage.In the application, the steps of automatically executing restart, modifying the verification object, restoring the file, etc. are performed by remotely connecting the device under test, which makes the process that originally requires manual repeated operation mechanized and repeatable, thereby reducing the risk of misoperation caused by manual intervention.In terms of trust measurement data collection, the trusted chain and measurement information are automatically sent to the test host after each start of the device under test, and the test host can obtain the complete measurement chain in a timely and systematic manner, avoiding the omission problem that may occur when manually comparing logs and PCR values.

This application provides a testing method and apparatus for an autonomous driving cloud simulation platform. The method includes: acquiring multi-source data from the autonomous driving cloud simulation platform; classifying and structurally extracting the multi-source data to obtain corresponding knowledge fragments and storing them in a knowledge source database; vectorizing the knowledge fragments according to their types using different language models to obtain document vector sets, code vector sets, and scene parameter vector sets; receiving test requirements described in natural language and quantizing them; performing vector retrieval in the document vector set and scene parameter vector set using a retrieval enhancement generation algorithm; inputting the retrieval results into an artificial intelligence model to understand the test scenario requirements; obtaining test case logic output by the model; retrieving test code templates from the code vector set based on the test case logic; and injecting input parameters into the test code templates to obtain test code for testing. This application can improve the efficiency and accuracy of testing autonomous driving cloud simulation platforms.

The application discloses a test case generation method, which can be applied to the field of cloud computing. After a first test case is acquired, feature information of the first test case is generated according to the first test case. Then, a second test case with consistent feature information is searched from a feature database according to the feature information of the first test case. Since the second test case has been configured with corresponding first test resources, and the feature information of the first test case is consistent with the feature information of the second test case, the first test case can directly reuse the first test resources, thereby saving the time for configuring test resources for the first test case and effectively improving the efficiency of generating test cases.

To provide systems, methods, and devices for testing vehicle software. [Solution] According to an exemplary embodiment, the system may include a memory storage that stores computer executable instructions, and at least one processor that is communicatively connected to the memory storage, wherein the at least one processor may be configured to execute instructions to generate a graphical user interface, receive a search input from a user in a search area of ​​the graphical user interface, display one or more test steps associated with the search input in a test step area of ​​the graphical user interface, receive a selection input from the user to select one of the one or more test steps displayed in the test step area, and input a code associated with the selected one of the one or more test steps into a first part of the graphical user interface.

This invention provides a testing method, device, and storage medium for stateful network protocols. First, it accurately identifies new state transition events based on the response feedback of the server under test. Then, it extracts corresponding client request message pairs from protocol interaction messages, and further segments them according to field location rules to obtain semantically independent field units. It then identifies differences between field units with the same name to generate candidate field groups, and filters out the candidate field set that truly triggers the state transition through testing. Finally, it performs structure-aware targeted mutations on the test seed based on the candidate field set to generate test cases. By accurately locating the core fields that trigger state transitions, it solves the technical problem of insufficient granularity in trigger condition analysis, making subsequent mutations in the testing process more targeted and effectively improving the accuracy and efficiency of state exploration in fuzzy testing of stateful protocols.

Embodiments of the present disclosure provide a test case generation method and device, equipment, a storage medium and a program product, relating to test technology, comprising obtaining data transmission relationships between interfaces, wherein the data transmission relationships comprise a plurality of initial mapping relationships; determining a probability of each initial mapping relationship according to each initial mapping relationship in the data transmission relationships, the probability being used to represent a probability that a parameter is derived from one interface when the parameter is used as an input parameter of another interface; determining real mapping relationships between the interfaces according to the probability of each initial mapping relationship, and generating a scenario case according to the real mapping relationships. In the scheme provided in this embodiment, a real mapping relationship with a higher probability in a parameter transmission process can be determined, so that a mapping relationship for representing parameter transfer that is more consistent with an actual scenario can be obtained, and then a scenario case that is consistent with an actual application scenario can be generated based on the real mapping relationship.

The application discloses a fuzzy test seed screening method and device. The method is based on multiple sets of fuzzy test seeds. Seed messages corresponding to the fuzzy test seeds are sent to a test object in sequence, and the change degree of each state feature of the test object when processing the seed messages is monitored. The change degree of the state of the test object when processing the messages can determine the complexity of the device under test when processing the messages or commands. The more complex the processing logic is, the more likely bugs exist, and the test should be focused on. Finally, the fuzzy test seeds are sorted according to the state influence degree of the seed messages on the test object, so as to determine the screening priority of each fuzzy test seed, so that the fuzzy test seeds with higher priority are screened preferentially to generate test cases, thereby improving the test efficiency.

The application relates to the technical field of GPU performance analysis, in particular to a performance analysis and optimization system based on a memory access intensive program, which comprises a GPU, a test case corresponding to a program to be analyzed, a processor and a memory storing a computer program; when the computer program is executed by the processor, the following steps are implemented: according to memory access parameters corresponding to the test case and a thread start rate corresponding to the GPU, determining an ideal bandwidth of the GPU when the test case is run; comparing the ideal bandwidth with an actual bandwidth of the GPU when the test case is run; determining whether optimization is needed; after it is determined that optimization is needed, judging whether parameter optimization is needed according to a first limitation condition; and providing an optimization target and a limitation condition of the optimization, thereby providing an optimization direction for performance optimization, so that the accuracy and efficiency of performance analysis and optimization are improved.

This application provides a functional verification method applicable to the fields of artificial intelligence or big data technology. The method includes: acquiring a preset knowledge graph, the knowledge graph including markers indicating differences between functional points in a first system and functional points in a second system, the differences including difference types; acquiring first system test cases corresponding to the differences; based on the difference types, executing a corresponding test case generation strategy on the first system test cases to obtain second system test cases; calculating the functional coverage of the second system with respect to the first system; and, if the functional coverage is greater than a preset coverage threshold, performing regression testing verification based on the second system test cases. This application also provides a functional verification device, equipment, storage medium, and program product.

This application proposes a software automated testing method and system, relating to the field of software testing technology. The method includes: constructing a directed acyclic graph (DAG), identifying call path fragments, and constructing test input data; driving the software system under test to execute a test run and generating new function call information; converting the new function call information into a sequence of new nodes, and performing structural difference analysis with historical test run records to generate a cumulative composite difference value; if the cumulative composite difference value is greater than a preset threshold, storing the test input data in a pre-constructed test case library as a new test case, forming an updated test case library; and executing multiple rounds of test runs on the software system under test based on the updated test case library. This allows potential defect paths that were previously continuously uncovered to be systematically discovered, reproduced, and solidified, fundamentally alleviating the dilemma of insufficient accuracy and resource waste caused by the non-evolving nature of testing behavior.

This application discloses a smart contract testing method, apparatus, electronic device, and computer-readable storage medium, relating to the field of blockchain technology. The method involves: determining a target smart contract to be tested and determining target test cases for testing the target smart contract; obtaining a modifier contract corresponding to the target smart contract; using the modifier contract to call and execute the target smart contract across contracts according to the target test cases to test the target smart contract; and recording the contract execution information of the target smart contract during the testing process using the modifier contract. This application achieves automated recording of smart contract execution information and eliminates manual intervention in the entire recording process, thereby improving the efficiency of contract execution information recording.

This application discloses a test data processing method, apparatus, equipment, and storage medium for production problem feedback, relating to the field of software test data processing technology. The method includes: structuring historical production problem data to obtain structured production problem data; constructing a problem database based on the structured production problem data; determining root cause analysis data based on the problem database in response to newly added production problem data; updating test assets in the problem database based on the root cause analysis data when the root cause analysis data passes correctness verification, obtaining updated test assets; and generating test case data based on the updated test assets in response to system function change data. Through the structured governance and knowledge base construction of historical production problem data, the method achieves automatic determination of the root causes of newly added production problems and dynamic mapping and updating of test assets.

The application discloses a kind of orthogonal test methods, equipment and storage medium based on user account, comprising: obtaining real-time account state information and real-time service traffic data;From real-time account state information, target test account is allocated, and the mapping relationship of target test account and test case is established;Real-time service traffic data is analyzed for scene characteristics, and the parameter structure of orthogonal test table is generated parameterized test case combination based on characteristic dimension and value distribution dynamic adjustment;Parameterized test case combination and target test account are injected into test environment to execute traffic playback, and according to the difference feedback of playback response data and expected result, adjust the test parameter value weight and case execution priority in orthogonal test table.The application forms closed loop feedback by account state dynamic identification and orthogonal table adjustment driven by traffic characteristics, realizes the matching of test account and case and test parameter adaptive optimization, to improve test scene coverage and execution efficiency.

This invention discloses an IoT fuzzing method based on LLM-guided and FSM dynamic inference, belonging to the field of IoT network security and software testing technology. Addressing the problems of low coverage and inaccurate state machine inference in current IoT protocol fuzzing, this invention first constructs an initial FSM by combining IoT protocol specifications and captured traffic data. Then, it generates a large number of test cases through mutation of seed test cases for fuzzing testing. Features are extracted from device responses, and state identification is performed by calculating similarity. When a new state appears, the FSM and state fingerprint database are updated. When coverage becomes a bottleneck, LLM-guided path inference is used to generate extended sub-FSMs and test cases, which are then executed. The FSM is then corrected based on the test results. This invention enables high-precision automated construction of IoT protocol state FSMs, improving test coverage and enhancing the efficiency and accuracy of vulnerability discovery.

The present application relates to the field of optical module testing, and particularly relates to an optical module firmware timing test platform, which comprises a host computer, a control board, a test unit, an oscilloscope and a power supply, the test unit comprises a test board, the test board is loaded with a to-be-tested optical module, the control board and the oscilloscope are both connected to the host computer, the to-be-tested optical module on the test board is in communication connection with the control board, the control board is connected to the oscilloscope through an indication signal pin, the emission end of the to-be-tested optical module is connected to the oscilloscope, the host computer is used for issuing a test instruction to the control board, acquiring a firmware timing waveform and performing analysis and calculation, the control board runs an optical module firmware timing test case in response to the instruction, and controls and monitors the test unit and the to-be-tested optical module to realize the test case, the control board also outputs an indication signal to the oscilloscope, the oscilloscope is used for displaying and recording the firmware timing waveform, and sends the waveform to the host computer for measurement and recording. The present application can effectively reduce the loss of manpower and time, improve the test repeatability, and accelerate the test speed.

This application discloses a memory management method and electronic device, relating to the field of computer technology. The method includes configuring the memory of any controller in a target cluster based on its current memory management parameters, running preset test cases on the controller to obtain performance indicators under the current memory configuration, determining the fitness function value of the controller under the current memory configuration, and then determining the controller's historically optimal memory management parameters. If the current iteration count has not reached an iteration count threshold, the memory management parameters are updated based on the target update speed, and iteration continues based on the updated memory management parameters. If the current iteration count reaches the iteration count threshold, the controller is configured with appropriate memory based on its historically optimal memory management parameters. This achieves dynamic memory management of the controller, resulting in improved memory utilization.

This application relates to a method, system, device, and medium for real-time evaluation of business rules based on a large language model. The method includes: invoking a large language model to convert natural language business rules into structured description data containing entity identifiers, attribute identifiers, and rule constraints; mapping entity identifiers and attribute identifiers to the location information of corresponding program elements in a domain model based on a pre-stored mapping library, generating detailed mapping data; generating source code files implementing a preset evaluator interface based on the structured description data and the detailed mapping data; converting the source code files into an executable form and executing them in an isolated execution environment; invoking the evaluator interface, evaluating the execution results using generated test cases, and generating a verification report. This application achieves fully automated conversion of business rules to executable code, reducing maintenance costs and improving the efficiency of rule deployment.