10 results about "Test case generator" patented technology

The invention discloses an RFID (Radio Frequency Identification) tag chip verification system and device based on SystemVerilog, and a storage medium. The system comprises a use case database, a generator module, a driver module, an input monitoring module, a reference model module and a result comparison module. Wherein a plurality of test cases are stored in the case database; the generator module is used for generating an excitation sequence according to the test case; the driver module is used for converting the excitation sequence into a verification operation instruction and sending the verification operation instruction to the chip to be tested and the reference model module; the input monitoring module is used for capturing the actual output response of the chip to be detected; the reference model module is used for simulating an ideal output response of the chip to be tested according to the verification operation instruction; and the result comparison module is used for comparing the actual output response with the ideal output response to obtain a verification result of the chip to be tested. The verification system provided by the invention not only ensures the function correctness of the RFID tag chip, but also ensures the reliability of the RFID tag chip in practical application, and can greatly improve the verification efficiency and quality.

The present application relates to a generator, a method and an automatic test system for generating test cases for operators in deep learning, wherein the system of the present application is integrated in an integrated circuit device, which includes a general-purpose interconnection interface and other processing devices. The system interacts with the other processing devices to jointly complete the user-specified computing operation. The integrated circuit device can also include a storage device connected to the system and the other processing devices respectively for data storage of the system and the other processing devices.

The invention discloses a structured test case generation method and system based on RAG and MCP, and relates to the technical field of tool calling. The method comprises the following steps of: constructing an RAG knowledge base, partitioning, vectorizing and storing test related documents, and storing a test parameter set at the same time; a user system-level test task is decomposed into atomic task packages by means of a test task analyzer. And calling an RAG retrieval interface, converting the atomic task package text into a vector query condition, matching related fragments in a vector database, and reserving an original text. And the large language model calls an interface of a test case generator through an MCP protocol according to the matching fragment, the original text and the generation requirement, extracts parameters from a test parameter set, generates a structured test case, and stores the structured test case into a test case storage module for an automatic test framework to call and execute. The problems that existing test case design mainly depends on artificial experience, and a large amount of time and labor cost are consumed are solved.

An embodiment of the present application provides a cross-platform compatibility automation testing method, the method comprising: scanning a target platform architecture specification file to extract instruction set features, collecting chip platform information to build a test environment database, building a test case feature model based on the instruction set features and the test environment database, designing a test case generator based on the test case feature model, and generating a test task scheduling plan based on a test execution framework; inputting abnormal behavior features and performance baseline thresholds into a test result analyzer, building a scoring dimension including functional completeness, performance compliance rate and stability indicators, mapping abnormal behavior features and performance baseline thresholds to the scoring dimension to generate a test result scoring matrix, calculating a weighted average of the test result scoring matrix and the optimized weight coefficient as the compatibility level, generating a test report based on the compatibility level and performing regression verification; the present application can improve the comprehensiveness and accuracy of the test and achieve more efficient compatibility evaluation.

The embodiment of the invention relates to a test case generation method, a test method, a test case generator, electronic equipment and a medium. The test case generation method comprises the steps that a unified structure model of a tested design is obtained, and the unified structure model comprises at least one to-be-configured parameter; acquiring parameter configuration information of the at least one to-be-configured parameter; and on the basis of the parameter configuration information and the unified structure model, generating the test case so as to test the tested design by using the test case. According to the method, the test case generation efficiency can be improved, and the completeness and efficiency of chip verification are improved.

The application discloses a RAG and MCP-based structured test case generation method and system, and relates to the technical field of tool calling.The method comprises the following steps: constructing a RAG knowledge base, carrying out blocking, vectorization and storage on test-related documents, and storing a test parameter set.Making use of a test task parser, a user system-level test task is decomposed into an atomic task package.A RAG retrieval interface is called, the atomic task package text is converted into a vector query condition, relevant fragments are matched in the vector database, and the original text is reserved.A large language model extracts parameters from the test parameter set and generates structured test cases according to the matched fragments, the original text and generation requirements, calls an interface of a test case generator through an MCP protocol, and stores the structured test cases in a test case storage module for calling and execution by an automatic test framework.The method solves the problem that existing test case design mainly relies on manual experience and consumes a large amount of time and labor cost.

The invention discloses a DL / T 634.5104 communication-based automatic test method for a power system guarantee and test integrated power distribution terminal, and belongs to the field of power system power distribution automation equipment test. According to the method, a test system composed of an upper computer, a switch, a relay protection tester and a tested terminal is built, data interaction of all devices is achieved based on a DL / T 634.5104 protocol, and two automatic test processes of measurement and control and protection are covered. According to the measurement and control process, a test case generator is instantiated, different industrial standards are adapted, test values corresponding to terminal rated parameters are automatically converted, and measurement error judgment is completed; a protection process depends on an Excel point table to realize constant value mapping, a pressing plate can be remotely put and withdrawn, a constant value can be modified, and the reliability of a protection action can be verified. The system supports a multi-terminal parallel test, can automatically generate an integrated comprehensive report and carry out test data trend analysis and abnormity early warning, solves the problem that a traditional test template is difficult to adapt and protects the pain point of function test manual operation, and improves the test efficiency and accuracy.

A method consisting of obtaining a definition of interestingness 233 and a plurality of test cases suitable for fuzz testing an autonomous system 234 and providing them to a large language model (LLM) 231 which then outputs 238 a score or ranking of the test cases based on the definition of interestingness. The method may further comprise providing the LLM with: information on the state of the system separately from the test scenario, the output format of the LLM, and a methodology for ranking or assigning scores. The LLM may output an explanation of its rankings / scores which may be done by chain-of-thought prompting. The methodology may involve carrying out fuzz testing using selected test cases 239. The test cases may be obtained by a test case generator 220 which may consist of modifying some seed case 222 to obtain a mutated seed case 223. A test case analyser 230 for doing the same is also disclosed. [Figure 2]

The invention provides a test case generation method and device based on reinforcement learning, equipment and a medium, and relates to the technical field of test development. According to the method, the problem description text and the standard answer code are obtained, and the executable test case generator is generated by utilizing the large language model, so that the automation of test case generation is realized, and the tedious work of manually compiling the test case is reduced. A generator is driven to generate candidate test input through a preset test case demand, consistency verification is carried out in a sandbox environment by utilizing a plurality of standard answer codes, the generation efficiency and quality of the test case are further improved by marking effective test input and constructing the test case, and through consistency verification and a dynamic optimization mechanism, the generation efficiency and quality of the test case are improved. The quality and the coverage rate of the test case are remarkably improved, so that the generation efficiency of the test case is greatly improved while high-quality output is ensured in financial insurance application development and medical diagnosis application development scenes.

The invention discloses a Python language defect prediction method combined with function-level dynamic operation characteristics, which comprises the following steps of: acquiring a Python language code item by utilizing an open source website, and constructing a Python language defect data set through item community information multi-layer screening; using a function-level dynamic instrumentation technology and a test case generator to count function-level dynamic operation characteristics; calculating a function-level feature weight by adopting an improved SXGB method based on a game theory; introducing the code version time difference information into a bidirectional long short-term memory network to construct an asymmetric sampling time sequence data adaptive model; performing defect prediction on the high-version Python project based on the constructed model; the method makes substantial progress in the aspects of dynamic feature interpretability, version evolution adaptability, complex asynchronous behavior capture and the like.