563 results about "Test code" patented technology

The invention discloses an unmanned aerial vehicle flight control system vulnerability detection method based on data flow analysis and LLM, and belongs to the technical field of intelligent software testing. Comprising the following steps: extracting a code function module associated with user operation in an unmanned aerial vehicle flight control system through a data flow analysis method, and establishing an operation-code mapping relation library; generating a structured natural language semantic description for each function module code by adopting a large language model LLM, and forming a multi-dimensional semantic feature vector; based on correlation analysis of multi-module semantic features, a combined test scene is constructed, and a natural language test case is generated; the natural language test case is converted into an executable test code through reverse semantic mapping, and coding reconstruction of test logic is completed; and executing a test code and capturing a runtime log in an unmanned aerial vehicle simulation environment, and performing vulnerability feature extraction and root cause positioning by using a large language model. According to the method, the efficiency is improved, and meanwhile, the deep coverage test of a complex interaction scene is supported.

The present application provides a code testing method, applied to a code testing system. When a test code is generated, context information of a code under test is extracted, and the test code is generated on the basis of the context information of the code under test. The context information often has a service meaning and can embody a test scenario, so that the prior knowledge of the service and the test scenario is achieved in the generation process of test codes, thereby generating test codes having higher quality.

The invention provides a method and device for generating a test case based on a large model and electronic equipment, and relates to the technical field of artificial intelligence such as natural language processing, large language models and deep learning. According to the specific implementation scheme, when a test case is executed to test a tested code, assertion error reporting information is obtained; generating a first prompt word based on at least one of the test case, the tested code and the assertion error report information; inputting the first cue word into the large model to obtain a first output result of the large model; the first output result comprises repair scheme information, and the large model is used for outputting the repair scheme information matched with the first cue word based on the first cue word; and performing multiple rounds of interactive dialogues with the large model based on the first output result to generate a test case of the tested code. By implementing the embodiment of the invention, the accuracy and the code coverage rate of the test case can be improved, the problem can be quickly positioned, the repair suggestion can be automatically generated, the manual intervention is reduced, and the test efficiency is improved.

The present application discloses a test code repairing method applied to a code development platform. The method comprises: obtaining a test code corresponding to a source code, and then executing the test code to obtain execution information of the test code, wherein the execution information comprises abnormal stack tracking information output during execution of the test code; on the basis of the execution information, performing fault localization on the test code to obtain location information of a faulty code; on the basis of the location information of the faulty code, extracting context information, wherein the context information comprises at least one of a faulty test case, a fault description, or the faulty content; and inputting a prompt constructed on the basis of the context information into a language model and performing inference, so as to obtain a first repaired code. The method is used to perform fault localization in light of the execution information, extract the context information on the basis of the location information of the faulty code, and, on the basis of the context information, generate accurate and complex repaired code via an advanced language model, thereby adapting to various complex fault scenarios and improving repair efficiency and accuracy.

Provided in the present application is a code generation method. The method is executed by a code generation system, wherein the code generation system is used for automatically generating a test code. The method comprises: receiving a test step description inputted by a user; retrieving a text code pair vector library and a test method vector library on the basis of the test step description, so as to obtain a test code fragment and a test method use case which correspond to a similar test step description, wherein the text code pair vector library comprises description text and a vector formed by a corresponding test code, and the test method vector library comprises a vector formed by the test method use case; then, on the basis of the test code fragment and a test method which correspond to the similar test step description, performing reasoning by means of a large language model (LLM), so as to generate a test code corresponding to the test step description; and presenting to the user the test code corresponding to the test step description. The method combines retrieval with LLM reasoning, such that a complex test code can be automatically generated, thereby improving the efficiency of automated development in complex test scenarios.

The invention provides an automatic network protocol testing method and system based on a large language model. According to the method, through three core technologies of structured protocol specification extraction, hybrid test case generation and retrieval feedback enhanced code generation, full-process automation from a protocol specification document to an executable test code is realized. The method comprises the following steps: firstly, carrying out preprocessing and structured analysis on an RFC document, and extracting protocol field information and state machine description; a complete test case covering normal, abnormal and boundary conditions is automatically generated based on protocol elements; and finally, an initial test code is generated in combination with a test equipment API document retrieval result, and multi-round iterative optimization is performed through running log analysis and an experience knowledge base. Compared with the prior art, according to the scheme, an end-to-end automatic test work chain is achieved, new protocol testing can be adapted without manual protocol modeling, meanwhile, a large language model and expert experience are fused through a feedback mechanism, and the test efficiency and the code quality are remarkably improved.

The invention discloses a full-process automatic unit testing method, device and equipment for an AI chip operator, a medium and a product. The method comprises the following steps: generating an engineering directory and a test framework design document through an architect agent according to operator interface information and a DSL operator design document knowledge base; the method comprises the following steps of: generating a test code for unit test by a software engineer agent according to a test framework design document and a domain knowledge base, and storing the test code in an engineering directory; multiple rounds of interaction are carried out through a software engineer agent and a test engineer agent, a test code is gradually corrected into a target test code which can be successfully compiled, a generated test case can be successfully executed and the generated test case meets the code coverage rate requirement, and a target operator code passing a unit test is obtained; and submitting the target operator code and the target test code which pass the normativity check to a code warehouse through a code auditing engineer agent so as to automatically realize the whole-process unit test of the AI chip operator.

The invention discloses an agent-based test case generation method and device, equipment and a medium, and relates to the technical field of software testing, the method comprises the following steps: in response to a test case generation instruction for a target function, displaying a test case framework of the target function; in response to an interaction instruction for a preset position in the test case framework, obtaining a target test code of the target function; wherein the interaction instruction is used for triggering interaction between a first agent and a second agent, and the first agent is configured to be used for analyzing a logic structure of a function code of a target function to obtain a structure code of a test point of the target function; the second intelligent agent is configured to be used for generating a target test code based on the structure code of the test point; and displaying the target test code at a preset position to obtain a target test case of the target function. The problem that the generation accuracy of the test case is low can be solved.

The invention provides a test program generation method and device, computer equipment and a readable storage medium, and belongs to the technical field of software development. The test program generation method comprises the steps of obtaining a test requirement document of a target chip; analyzing the test demand document to obtain keyword information corresponding to the test demand document; based on a preset test development model and the keyword information, obtaining test demand development model information; according to the test requirement, developing model information, calling at least one artificial intelligence interface in a preset large language model, and generating a plurality of test codes; and according to the plurality of test codes, generating a target test program corresponding to the target chip. According to the method, the effects of shortening the development period of the test program and improving the development efficiency of the test program can be achieved.

The invention aims to provide a method and a system for realizing a built-in self-test code of a PCIE (Peripheral Component Interface Express) physical layer. The method comprises the following steps of: integrating PCIE BIST GEN module packaging data in a controller layer and sending the data to a physical coding sub-layer; the physical coding sub-layer codes the packaged data and sends the coded data to the physical medium adaptation layer; and the physical medium adaptation layer converts the coded data into serial data and transmits the serial data back to the controller layer. According to the invention, the BIST test assembly meeting the PIPE protocol requirement is embedded in the PCS layer, and compared with a traditional BIST test scheme, through early-stage simulation and post-silicon test data result analysis, not only can the electrical performance test requirement of an original analog circuit be met, but also the test coverage of the PCS layer is increased. And the full-stack coverage test from the physical signal to the protocol logic is realized.

The invention discloses a high-quality micro-benchmark performance test automatic generation method and device based on a large language model, and the method comprises the steps: carrying out the analysis of a target project, and constructing a system dependence graph; analyzing a calling link of the target method by utilizing the system dependency graph, and guiding the large language model to perform performance classification according to source codes in the calling link; the performance classification result is matched with a predefined JMH parameter template; contextual information and a parameter template of a target method are integrated, and a large language model is effectively guided to generate a high-quality micro-benchmark performance test case; and analyzing the successfully generated micro-benchmark performance test code, detecting bad practices in the code by utilizing the bad practice rule base, repairing the bad practice code, and finally generating an efficient and accurate test case. The method is superior to a traditional method in the aspects of test generation accuracy, performance defect detection capability and the like, and the generated test case has remarkable advantages in the aspects of understandability and performance measurement accuracy.

The invention provides a communication protocol consistency test method and system. Key function points are extracted by analyzing a target protocol document; based on the key function points, a predefined first prompt template is applied to generate a test case prompt, a large language model is guided to generate a standardized test case corresponding to each key function point, and the first prompt template comprises k few-sample examples; dynamically retrieving a related code context from a pre-constructed long-term memory library through a retrieval enhancement generation mechanism, generating a code generation prompt by applying a predefined second prompt template based on the standardized test case and the related code context, and generating an executable test code based on the code generation prompt; and performing iterative optimization on the executable test code through the large language model, and generating a new code generation prompt based on a code execution result of the previous iteration and the retrieved related code context in each iteration. The test case can be automatically generated and dynamically adapted, and the test coverage rate, efficiency and flexibility are improved.

The invention provides a code generation method which is executed by a code generation system, the code generation system is used for automatically generating a test code, and the method comprises the following steps: receiving a test step description input by a user, retrieving a text code pair vector library and a test method vector library according to the test step description, the text code pair vector library comprises description texts and vectors formed by corresponding test codes, and the test method vector library comprises vectors formed by the test method calling examples; and according to the test code snippets and the test methods corresponding to the similar test step descriptions, reasoning through a large language model (LLM), generating test codes corresponding to the test step descriptions, and presenting the test codes corresponding to the test step descriptions to a user. According to the method, retrieval and LLM reasoning are combined, the complex test code can be automatically generated, and the automatic development efficiency of the complex test scene is improved.

The present disclosure is directed toward systems, methods, and non-transitory computer-readable media for generating function code and test code to determine that the function code satisfies an intent query. For example, the disclosed systems utilize a large language model to process an intent query and generate function code that defines one or more processes whose execution satisfies the intent query. In addition, the disclosed systems also utilize the large language model to generate test code that defines a function test for determining that the function code satisfies the intent query. Moreover, the disclosed systems can execute the test code to determine that the function code satisfies the intent query.

The invention discloses a server test system and method, electronic equipment and a storage medium, and relates to the technical field of data processing. Multi-level information of power-on self-test codes, test data and optical signals is collected for a server; meanwhile, the starting-up process of the server is divided into different starting-up stages according to the code stream, namely the starting-up self-test code, and the server is tested through different test strategies in the different starting-up stages; according to the method, multi-level state sensing and optical intelligent detection are carried out in combination with multi-level information, the coverage degree of server testing is improved, and meanwhile, the server testing efficiency is improved through testing of multiple starting-up stages of a full-automatic process and automatic analysis of testing data. Therefore, the technical problem of how to improve the test efficiency and the coverage degree of the server test can be solved, and the technical effect of improving the test efficiency and the coverage degree of the server test is achieved.

The invention discloses a code generation method and device based on a large model, equipment, a medium and a product, and the method comprises the steps: carrying out the code generation through a first code large model according to target code demand data, and obtaining an initial code; according to the first code snippet, generating a test code through a second code large model to obtain a unit test code; according to the unit test code and the initial code, code repair based on editing distance regularization is conducted through a third code large model, and a to-be-analyzed code is obtained; performing iterative optimization on the to-be-analyzed code and the unit test code to obtain a target code corresponding to the target code demand data; according to the method, code generation, unit test generation and code repair are carried out in a multi-model cooperation mode, the reliability and accuracy of code generation can be effectively improved, software security vulnerabilities are reduced, and therefore the stability and security of a software system are improved.

A computer-implemented method for the automated generation of test code for testing software. The method includes generating, via a machine learning model, at least one test case and / or a test code at least based on a code of the software and a prompt; and evaluating the at least one test case and / or the test code, wherein an evaluation result is obtained. A computer-implemented method for further training a machine learning model and / or further machine learning model is also described. The machine learning model configured to generate at least one test case and / or a test code for testing software at least based on a code of the software and a prompt, and the further machine learning model is designed to generate a test code for testing the software at least based on at least one test case and a further prompt.

The invention relates to the technical field of software engineering and artificial intelligence crossing, in particular to an API test case rapid generation method and system based on an AI large model.The method comprises the following steps that joint analysis and semantic fusion are conducted on an API document and a demand document through a multi-modal data analysis layer, and a complete test context is constructed; generating a test case based on the pre-trained large model by using a hybrid inference engine; the method has the beneficial effects that the association constraint of the API document and the demand document is automatically extracted through semantic understanding; a parameter combination strategy is optimized through reinforcement learning, and the problem of combination explosion is solved; constructing a self-adaptive test case maintenance mechanism, and responding to API version iteration; an executable test code that can be directly integrated into the CI / CD pipeline is generated.

The invention provides a core particle and a test method thereof, and the core particle comprises a home terminal generator which is used for generating and sending a test code to a sending channel for transmission; wherein one test code is transmitted through one sending channel, and the number of the test codes is the same as that of the sending channels; the home terminal multiplexer is used for receiving the detection code through the receiving channel; wherein one detection code is received through one receiving channel, and the number of the detection codes is consistent with the number of the receiving channels; and the home terminal checker is used for generating a corresponding check code according to the received detection code and checking the corresponding detection code through the check code, if the check is successful, the transmission channel corresponding to the detection code is unobstructed, otherwise, the transmission channel corresponding to the detection code is transmission fault. According to the core particle and the test method thereof provided by the invention, the requirements of a serial transmission test of a single channel and a parallel transmission test of a plurality of transmission channels can be met.

The invention relates to the technical field of code testing, in particular to a test case generation method and device, computer equipment and a storage medium. The method comprises the steps of obtaining at least one piece of historical test data for a to-be-tested code; constructing a target test case template for the to-be-tested code according to a function requirement and a business rule corresponding to the application scene of the to-be-tested code; and according to the target test case template, generating code test cases for a covered code path and an uncovered code path of the to-be-tested code respectively. In the process of generating the code test case, the function requirement and the service rule of the application scene are referred to, so that the code test case can cope with the complex and changeable requirement and service rule in the current application scene, and it is ensured that the test efficiency is improved in the process of testing the to-be-tested code according to the code test case. And the test result for the to-be-tested code is accurately obtained, so that the test result conforms to the current application scene of the to-be-tested code.

The invention provides an automatic test generation platform and method for an operating system kernel derived function. The method comprises the following steps: (1) intelligent symbol extraction and analysis; (2) generating an LLM-driven test code; (3) performing automatic compiling and virtualization testing; and (4) intelligent error diagnosis and repair. According to the method, the test coverage degree is greatly improved, through the multi-level symbol context extraction technology, single function information is extracted, the dependency relationship of related functions in the same element is analyzed, a function call graph and data flow analysis are constructed, rich context information is provided for LLM, and the problem that traditional manual test case writing is incomplete in coverage is solved.

The embodiment of the invention relates to a test case generation method and device, equipment, a storage medium and a program product. The method comprises the steps that a target test case document is analyzed, and interface calling description and an interface calling sequence are determined; based on the interface calling description, determining a target request method and a target request parameter corresponding to the interface calling description from the candidate interface information; performing parameter value extraction on the interface calling description based on each target request parameter, and determining a first request parameter and a first parameter value; based on the target request method and a second request parameter in the target request parameters, querying a parameter dependency relationship graph obtained based on historical test data, and determining a parameter value of a dependency parameter having a parameter transmission relationship with the second request parameter as a second parameter value; and based on the target request method, the first parameter value and the second parameter value, generating an automatic test code according to the interface calling sequence. In this way, the generation efficiency, integrity and performability of the automatic test code are improved.

The invention relates to a test case execution method and device, equipment and a medium. The method comprises the steps that multiple test cases are analyzed, a mapping file, a variable name and an expression of each test case are obtained, and the mapping files are used for representing the mapping relation between the variable names and the expressions; according to the mapping file, the variable name and the expression of each test case, generating a test code of each test step in each test case; packaging the test codes of the test steps of the same type, and obtaining a code module corresponding to each test step type; and according to a preset execution sequence, calling the code module corresponding to the test step type to which each test step belongs in sequence to obtain test results of the plurality of test cases. According to the technical scheme, the execution efficiency and accuracy of the test case are improved.

The present disclosure is directed toward systems, methods, and non-transitory computer-readable media for generating function code and test code to determine that the function code satisfies an intent query. For example, the disclosed systems utilize a large language model to process an intent query and generate function code that defines one or more processes whose execution satisfies the intent query. In addition, the disclosed systems also utilize the large language model to generate test code that defines a function test for determining that the function code satisfies the intent query. Moreover, the disclosed systems can execute the test code to determine that the function code satisfies the intent query.

The invention provides a software monitoring method, system and device based on byte code replacement and risk awareness and a medium, and belongs to the technical field of software security. The method comprises the steps that a special annotation mark in a source code is scanned, a test code entry point is recognized, and metadata information is extracted; performing encryption processing on the metadata and generating a registry file with a digital signature; environment safety data are collected through four monitoring dimensions, and a comprehensive risk score is calculated; generating a grading fusing instruction according to the score; and finally executing the fusing operation of byte code replacement or thread sandbox isolation. According to the invention, accurate identification and real-time protection of the leakage risk of the test code are realized; through a multi-dimensional monitoring and hierarchical fusing mechanism, the system security is ensured, and the influence on the service performance is minimized; and byte code replacement and thread isolation technologies are adopted, so that security protection can be realized without restarting the application, and the availability and the operation and maintenance efficiency of the system are improved.

Efficient generation of multi-platform compatible source code and test code with consistency and quality in software development SOLUTION: The schema-driven development system includes a user input unit, a schema generation unit, and a code generation unit, wherein the user input unit acquires data in various formats such as a natural language and a CSV file, the schema generation unit converts the acquired data into a schema, and the code generation unit generates a source code and a test code based on the generated schema.SELECTED DRAWING: Figure 1

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 relates to an interface calling assertion monitoring method and computer equipment. The method comprises the following steps: in response to a triggered interface calling instruction, generating a tracking address identifier of an interface; running a test code of the interface, and obtaining a test log and an interface response value generated in the running process of the test code; injecting the tracking address identifier into the test log and the interface response value, and binding the test log comprising the tracking address identifier with the interface response value comprising the tracking address identifier; according to the universal assertion and the self-defined assertion in the assertion library, assertion analysis is carried out on the test log and the interface response value which are bound with each other, and an assertion result of interface calling is obtained. By adopting the method, the accuracy of interface calling assertion can be improved.

The invention relates to the technical field of vehicle software testing, and discloses a vehicle unit test code generation method and device, equipment, a medium and a product. The method comprises the steps of obtaining a tested code; the tested code and the intention prompt word are input into a large language model to be analyzed, a test intention is generated through the large language model, and the test intention is used for indicating the process needed for testing the tested code; inputting the test intention, the tested code and the template cue word into a large language model for analysis so as to generate a test strategy through the large language model, and recommending a code template and a parameter value required by the test from a template library; and integrating the recommended code templates according to the test strategy, and filling the parameter values into the code templates to obtain test codes. The AI illusion is reduced, and the accuracy of generating the test code is improved.

The invention discloses an automatic test method and device for map operation response, equipment and a medium, and belongs to the technical field of Internet. The method comprises the following steps: acquiring a current tile serial number of a map display area; wherein the tile serial number is an index relationship established in advance based on the tile map position and the serial number; simulating operation data on the map to obtain an actual tile serial number after operation; resolving the operation data, and determining a target tile serial number according to a resolving result; and determining a test result of map operation response according to a comparison result of the actual tile serial number and the target tile serial number. According to the technical scheme, the target tile can be accurately calculated and checked with the actual tile by indexing the map tiles and aiming at any initial position and any map operation in different map resources, so that the accuracy of a test result, the design rationality of a test framework and the maintainability of a test code are improved.