178 results about "Test code" patented technology

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 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 embodiment of the invention relates to a test code generation method, device and equipment and a readable storage medium, test codes are iteratively generated through an LLM model, coverage rate improvement is automatically verified, a compilation failure rollback mechanism and environment adaptation are combined, automatic closed-loop control of test code generation and coverage rate improvement is achieved, and the test code generation efficiency is improved. And the manual writing and debugging cost is effectively reduced. And the generated test code is subjected to multiple rounds of compilation verification, so that the grammar correctness and the execution feasibility are ensured. The generation direction is continuously optimized through a dynamic feedback mechanism, and the coverage range of unit testing on target codes is systematically improved. And finally, automatically terminating the process when a preset quality index is reached, and outputting an effective test code set which is fully verified.

The invention relates to the technical field of automatic testing, discloses a fine-grained data change log management method and system for an automatic testing platform, and aims to realize high-precision, low-overhead and high-reliability log acquisition of business object field and set element change in a testing process on the premise of not modifying a testing code. The system comprises a declarative acquisition module for marking a to-be-monitored test object through declarative configuration and dynamically injecting log acquisition logic during test operation; the log processing engine is used for respectively acquiring state snapshots of the target business object before and after the test is executed, and identifying change information; the template factory component is used for packaging the identified change information, the context metadata and the timestamp according to a predefined structured data template to generate a standardized log record; and the log persistence module is used for writing log records into a lock-free annular buffer region realized based on atomic operation, and the log records are triggered by a batch coordinator of an independent thread to be asynchronously written into a main storage system in batches.

The invention relates to an OCamml unit test system, which adopts a layered architecture design and comprises a test driving layer, a test case regulation layer and a test suite function layer. The test driving layer automatically manages compiling, execution and result archiving of OCAML test codes through Makefile scripts; the test case regulation layer defines and organizes test cases based on a standardized template, and each test case annotates and declarates information such as a unique identifier and an airworthiness demand number through structured metadata; the test suite function layer comprises an assertion module, a report generation module, a data conversion module and a test auxiliary module. Through the layered architecture design, standardized management and automatic execution of the test process are realized, the standardization and traceability of the test activity are ensured, a complete demand-test-verification traceability evidence chain is provided for airworthiness certification, and the strict requirement of the high-security field for unit test is met.

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 invention relates to an application test method and device, electronic equipment and a storage medium, and relates to the technical field of computers, and the method comprises the steps: obtaining an application service relation graph and test range indication information under the condition that an application test instruction is received; determining a plurality of to-be-tested services and service link diagrams based on the application service relation diagram; performing link weight analysis on each to-be-tested sub-link based on the edge weight information or the node weight information in each to-be-tested sub-link to obtain sub-link weight information; based on the sub-link weight information and the service link diagram, performing a flow distribution test on the plurality of to-be-tested sub-links to obtain a link calling test result; obtaining service test codes corresponding to a plurality of to-be-tested services; based on the service test code, performing a service execution test on each service to be tested in the plurality of services to be tested to obtain a service execution test result; and generating an application test result based on the link call test result and the service execution test result.

The invention provides a software testing method and system. According to the software testing method, by means of the analysis processing capacity of an AI model with the code writing capacity on midscene.js natural language test case, the service requirement of a salesman is rapidly converted into an executable test code, and the executable test code is operated in a pre-established test environment to obtain a corresponding test result. Through the technical scheme provided by the invention, business personnel can easily compile the test code without mastering a professional programming technology, the barrier between the business personnel and technical personnel is broken, and the business personnel can deeply participate in the software test process. As the business test demand case is proposed by the business personnel according to the actual business demand, the consistency of the test scene and the real business process is ensured. The analysis and processing capabilities of the AI model enable the generation of the test code to be more efficient, thereby reducing the time for writing the test code, reducing the code error rate and improving the software test efficiency.

The invention provides a test code update determination method and device, a storage medium and electronic equipment. The method comprises the steps of obtaining a pre-change production code and a post-change production code of a current change code of a smart contract; according to the pre-change production code and the post-change production code, a target feature vector is determined, the target feature vector comprises a code change type feature and a code change measurement feature, and the code change type feature comprises a grammar change feature and a logic change feature of the production code; the code change measurement feature comprises a code file size change feature of the production code of the smart contract; and inputting the target feature vector into the target machine learning model to obtain a model output result which represents whether the test code corresponding to the production code before change is updated or not. According to the method, the update necessity judgment of the smart contract test code is realized through the machine learning model, and the consistency of the smart contract production code and the test code is maintained in time.

The embodiment of the invention provides a code testing method, computing equipment, a storage medium and a program product. The method comprises the steps of obtaining a target code selected in a code editing interface through a test plug-in integrated in a code development tool, providing test prompt information, generating a test instruction in response to a trigger operation for the test prompt information, and detecting a test environment of the target code in response to the test instruction, and according to the environment detection result, updating a test environment, generating a test code corresponding to the target code by using at least one intelligent generation model, executing the test code in the updated test environment to test the target code, and outputting a test result. According to the technical scheme provided by the embodiment of the invention, the code testing efficiency and accuracy can be improved.

The invention provides a user interface testing method which can be applied to the technical field of artificial intelligence, and relates to application of a large model in the fields of information security and financial science and technology. The user interface testing method comprises the steps that on the basis of a pre-constructed user interface component model library, intention inference is conducted on initial abstract syntax tree nodes of codes to be tested, target abstract syntax tree nodes are obtained, the target abstract syntax tree nodes comprise variable fields, user interface component type fields and service intention fields, and the variable fields are selected from the variable fields, the user interface component type fields and the service intention fields; the business intention field represents the business meaning of the user interface level; based on the target abstract syntax tree node and the to-be-tested code, testing the target user interface, and outputting a test result; and under the condition that the test fails, constructing an execution snapshot graph based on the target abstract syntax tree node and the test data in the test result to obtain a repair scheme. The invention further provides a user interface testing device and equipment, a storage medium and a program product.

A method and system of testing a fine-tuned LLM for domain specific code generation is disclosed. Further, a processor receives a test dataset corresponding to a domain from a code repository. Further, the processor determines an LLM generated problem statement corresponding to the test code using the fine-tuned LLM. The fine-tuned LLM is fine-tuned based on a training dataset. Further, the fine-tuned LLM is prompted based on the LLM generated problem statement to determine an LLM generated code for a corresponding test function. The accuracy level of the fine-tuned LLM is determined based on a percentage match between the LLM generated code with the test code for each of the set of test functions.

A system accesses a code module that includes one or more units of code and instructs a machine learning model to generate a test suite based on a specification for the code module. The test suite includes tests for testing the code module to verify that one or more units of code successfully execute in accordance with the specification. The specification includes preconditions that precede successful execution of the one or more units of code and postconditions that exist following successful execution of the one or more units of code. The machine learning model generates the test suite. The system receives the test suite from the machine learning model. The system stores and / or transmits the test suite for use in testing the code module.

This invention provides a continuous integration testing system and method for application software, relating to the field of software testing technology. A control terminal constructs test tasks based on the code to be tested and a pre-configured test process, sends them to a test host, and the test host initiates the code to be tested and executes the test tasks through an integration testing module. The integration testing module integrates distributed testing units, which execute corresponding test tasks and output test results. The distributed testing units include page character testing units, page layout testing units, media performance testing units, navigation function testing units, refresh update testing units, and traffic / power testing units. A test result feedback module receives test results from the distributed testing units and feeds them back to the test host. This invention solves the problem that current testing systems can only test individual projects one by one, which is inconvenient for continuous integration testing and results in low testing efficiency, thus improving software testing efficiency.

The embodiment of the invention discloses a function tampering detection method and device, a storage medium and a terminal. When it is monitored that the target function is currently in the callable scene, at least one to-be-tested code mark generated for the target function through a random prediction algorithm is obtained; adding each to-be-tested code mark to the target function, so that the method calling information contains each to-be-tested code mark when the target function is normally called; and performing simulation test calling on the target function, and judging whether the target function is tampered or not according to whether the method calling information of a simulation test calling result contains each code mark to be tested or not. The to-be-tested code mark generated by the random prediction algorithm has dynamic randomness, and the risk that a fixed mark is tampered or shielded in a targeted mode is effectively avoided. When simulation test calling is carried out on the target function, judgment is carried out according to the existence of the marks, and whether technical tampering is carried out on the content and calling logic of the target function or not can be directly locked.

A test file generation method, apparatus and device, and a storage medium, the method comprising: analyzing a to-be-tested code file to obtain output information and input information in the to-be-tested code file; the input information is input into a case operation tested module to obtain output information after the case operation tested module outputs operation, and the output information after the operation comprises a code coverage rate; according to the output information after operation and preset output information, a comparison result is obtained, and the preset output information is expected information obtained through calculation according to the logic of the tested code and the input information; and performing output integration according to the comparison result and the code coverage rate, and generating a test file so as to be suitable for various embedded projects, so that the technical problem that the existing test file is tedious to use and not easy to understand is solved, and the effects of simplifying the use complexity and being easy to understand are realized.

The application discloses a code verification method and device, and relates to the technical field of code verification. The method comprises the following steps: acquiring a to-be-tested code; running the to-be-tested code to acquire a video stream corresponding to the to-be-tested code; obtaining an actual trajectory of a target virtual object running by using a trajectory estimation algorithm based on continuous multiple real-time rendering pictures; and performing trajectory error analysis on the actual trajectory and an expected trajectory to obtain a code verification result. In the application, the real-time rendering video stream is generated by running the to-be-tested code, and the trajectory estimation algorithm is used to compare the expected trajectory with the actual trajectory, so that the visual effect verification of the to-be-tested code is realized, the problem that the prior art can only verify the theoretical correctness of the code and cannot guarantee the actual running effect is solved effectively, and therefore the motion trajectory of the virtual object is ensured to meet the design intention.

The present disclosure provides a method and device for generating unit test code, electronic equipment and storage medium, relating to the technical field of computer, especially to the technical field of data processing, artificial intelligence and the like. The specific implementation scheme is as follows: obtaining target function code in inventory code; extracting function information and statement information from the target function code; generating unit test code corresponding to the target function code based on the function information and the statement information; and performing function test on the target function code based on the unit test code.

The invention belongs to the technical field of micro-ring modulator optimization, and particularly relates to a micro-ring modulator feedback control system for realizing optical modulation amplitude and linearity optimization. A low-speed PAM-4 test signal easy to process is generated through a test code generation module and is pre-distorted through a feedback control module to drive a micro-ring modulator, a signal acquisition module acquires a response signal of the modulator in real time, and an eye pattern calculation module extracts current light modulation amplitude and linearity of quantitative performance from the response signal and calculates the light modulation amplitude and linearity of the micro-ring modulator. And the feedback control module synchronously adjusts the working points of the micro-ring modulator based on the indexes to optimize the light modulation amplitude, and adjusts the pre-distortion coefficient to optimize the linearity, thereby solving the problems of performance compromise and power consumption increase caused by the separation of the light modulation amplitude and the linearity optimization in the prior art. Compared with the prior art, collaborative optimization is achieved, and energy efficiency is improved while performance compromise is avoided.

The application provides a software code defect identification method and system based on feature fusion, relates to the technical field of artificial intelligence, and comprises the following steps: acquiring source code data, and extracting a multi-dimensional feature vector from the source code data; fusing MCDC structural features, static structural features and semantic features to generate a fused feature vector; constructing a defect identification model based on GraphCodeBERT, taking the fused feature vector as a training sample to train the defect identification model, and using a loss function fused with an MCDC risk score to optimize the parameters of the defect identification model during the training process; inputting the fused feature vector of the code to be tested into the trained defect identification model to obtain a defect confidence of the code to be tested, and generating a defect identification result based on the defect confidence, so as to solve the technical problems of high-risk defect omission, poor field adaptability and weak multi-project compatibility in the existing code defect identification technology.

Embodiments of the invention provide a memory leak detection method and apparatus, and a computing device. The method comprises the steps of obtaining a to-be-tested code; taking the to-be-tested code as the input of the first neural network model, and generating a parameterized test script of the to-be-tested code by using the first neural network model; operating the parameterized test script; in the process of executing the parameterized test script, monitoring runtime data of the to-be-tested code; under the condition that the memory leaks, determining the position of a code causing the memory to leak in the to-be-tested code according to the runtime data; generating a leakage detection report; the leak detection report includes a code location and a test execution path. By adopting the method, the leak behavior of the to-be-tested code is verified by dynamically executing the parameterized test script, and the memory leak point is specifically positioned, so that the accuracy and comprehensiveness of detection can be effectively improved.

This disclosure provides a code generation method, a code generation device, and related products. The code generation method includes: generating code to be tested using a first model based on prompt information; generating a test strategy corresponding to the code to be tested using a second model based on the prompt information and / or the code to be tested; testing the code to be tested based on the test strategy to obtain test results; wherein the test results are used to perform adversarial updates on the first and second models; and obtaining target code based on the test results and the code to be tested. This method can generate code with strong generalization ability, conforming to code rules, high execution efficiency, and robustness.

The invention provides a vulnerability detection method and device, equipment and a storage medium, and can be applied to the technical field of information security. The vulnerability detection method comprises the steps that to-be-detected codes are input into a large language model, a knowledge database is used for analyzing the to-be-detected codes, safety analysis code lines in the to-be-detected codes are output, and the safety analysis code lines represent key code lines used for vulnerability detection in the to-be-detected codes; according to a security analysis code line in the to-be-tested code, marking the code attribute graph of the to-be-tested code to obtain a marked code attribute graph; performing node vectorization and graph matrix on the marked code attribute graph to obtain a node vector matrix and an adjacent matrix set; and inputting the node vector matrix and the adjacent matrix set into a vulnerability detection model to extract vulnerability features based on the node vector matrix and the adjacent matrix set, and outputting a vulnerability detection result for the to-be-detected code.

Embodiments of the present specification provide a test case generation method, a computing device and a storage medium, wherein the test case generation method comprises: receiving description information of a to-be-tested object; generating an initial test case corresponding to the to-be-tested object, reference to-be-tested code and abnormal to-be-tested code according to the description information, wherein the initial test case is used to test the running state of the to-be-tested object; verifying the initial test case, the reference to-be-tested code and the abnormal to-be-tested code to obtain a target verification result corresponding to the initial test case; and generating a target test case corresponding to the to-be-tested object according to the target verification result and the initial test case.

The invention discloses an automatic toughness verification system and method for a cloud native system. The system is composed of an intelligent scene management module, a compilation period fault injection actuator, a semantic perception integrated interface, a four-dimensional verification and evaluation engine and a panoramic visualization and continuous optimization module. According to the method, a semantic test plan is generated through a structured service fault scene library, fault logic and atomic task identification are bound in a deterministic mode through condition compiling in the construction stage, and a special test program is generated; a preset fault is triggered during business execution, function correctness, recovery compliance, state consistency and performance influence four-dimensional verification is carried out in parallel, an aggregation result is generated to generate a score quantitative evaluation toughness index, and a high-value test scene is intelligently recommended based on a coverage rate to form a closed loop. According to the method, fault injection and business semantics are accurately associated, binary zero test code residues are produced, the verification depth and efficiency are improved by one order of magnitude, and the method is suitable for high-compliance scenes such as finance and AI training.

The invention relates to the technical field of software engineering and software quality assurance, and provides a method and a system for evaluating influence of quantitative code change on a program implementation effect. The method comprises the following steps: acquiring code difference information between a to-be-tested code branch and a baseline branch, analyzing and extracting structured information of a changed code through a large language model, and calculating a basic influence value of the structured information of the changed code; calling a program behavior feature library based on the structured information of the change code, and calculating a dynamic adjustment coefficient; calculating the final influence score of each dimension according to the product of the basic influence value of the structured information of the change code and the dynamic adjustment coefficient; the final influence score of each dimension comprises a core function influence score, a performance efficiency influence score, a data consistency influence score, an interface compatibility influence score and a security influence score; and generating an influence analysis report according to the final influence score of each dimension. According to the method, the basic influence value determined by the change type is multiplied by the dynamic adjustment coefficient determined by the module criticality and the historical risk, so that the code change influence is accurately and dynamically quantified.

This application provides a method and apparatus for generating test code in a target programming language. The method includes: during the verification phase of chip design, converting first test code into second test code based on a preset conversion program; the first test code is obtained by encoding the operation sequence in the verification requirements using a custom programming language, and the preset conversion program includes keyword conversion rules between the custom programming language and the target programming language, the keyword conversion rules including at least one of function mapping rules, register access mapping rules, and variable access mapping rules; determining the syntax tree corresponding to the second test code; at least one node in the syntax tree corresponds to at least one syntax keyword included in the second test code; traversing the syntax tree to obtain third test code in the target programming language; the third test code conforms to the direct programming interface specification. Using the above method can improve the generation efficiency of test code in the target programming language.

The application discloses a software simulation environment building method, device, medium and program product, and relates to the field of software development. The software simulation environment building method comprises the following steps: obtaining a network resource arrangement instruction; arranging target managed resources according to the network resource arrangement instruction to obtain a target environment network topology; configuring a node image file according to the target environment network topology to obtain a network topology to be instantiated; and performing code testing and verification according to target test code, the network topology to be instantiated and topology node usage state data. The technical scheme of the embodiment of the application can improve the building efficiency of a software development simulation environment and break the strong dependence of simulation environment building and instantiation on manpower.