1133 results about "E testing" patented technology

The invention provides a DFT test task management method and device, electronic equipment and a storage medium, and belongs to the technical field of chip design verifier.The DFT test task management method comprises the steps that a data model is constructed on the basis of a design module list and a test step list, the data model is used for indicating testability design DFT test steps of all design modules, and the test steps of all the design modules are stored in the test step list; the data model comprises a plurality of DFT test tasks, attributes of each DFT test task comprise a selection state, and the selection state comprises a selected state and a non-selected state; based on the interactive input, determining at least one DFT test task of which the selection state is selected as an executable DFT regression object; and according to the DFT regression object, driving a DFT test task to be executed. According to the method, the DFT test tasks are normalized through the data model, only the DFT test tasks need to be selected for making the test plan, efficient management of the DFT test tasks is achieved, and the regression test efficiency is improved.

A method for planning and executing a test of a DUT includes receiving a test description from a user via a GUI, where the test description identifies the DUT and an objective of the test; composing a prompt for querying a large language model (LLM) based on the test description, where LLM includes a trained machine learning algorithm; sending the prompt to the LLM via an API; determining, using the LLM, a test plan for executing the test to be performed in response to the prompt to achieve the objective of the test based on the test description and general testing information, where the test plan identifies a type of test, test instruments for performing the test, a test procedure using the instrument, and parameters of the DUT to be measured according to the test procedure; providing, via the GUI, the test plan to the user for testing the DUT.

The invention relates to a multi-driving-style high-risk automatic driving cut-in scene test method and system, and the method comprises the steps: collecting original driving track data, carrying out the clustering of driving styles, and generating a risk cut-in scene track cluster with consistent driving styles through employing a Cutin-TimeGAN network model in combination with physical feasibility constraints; constructing a cost function, calculating a cost function value for each risk cut-in scene trajectory cluster, and selecting a target cut-in reference trajectory as a target reference state vector; constructing a game framework, and combining a target reference state vector to construct a utility function according to the state vectors of the VUT and the test confrontation vehicle in the framework; constructing a risk confrontation utility function based on the predicted collision time; a game optimization problem is constructed and solved, an optimal interaction track of the test confrontation vehicle is obtained, and a closed-loop high-risk automatic driving scene switching test is carried out based on the optimal interaction track; the system is used for implementing the method. Compared with the prior art, the method has the advantages that testing of authenticity and high-risk confrontation of multiple driving styles is considered.

The invention discloses a Web automatic testing method, system and device, a medium and a program product, and belongs to the technical field of artificial intelligence. The method comprises the steps that test case abstract representation information is generated according to interactive input of a user and a test case mapping template, and the test case abstract representation information comprises a target test task type indicated by the interactive input and intention natural language description information; based on the test case abstract representation information, obtaining a target screenshot of the tested Web page and attribute information of interaction elements; a multi-mode large language model is called to conduct reasoning based on the target screenshot, the attribute information of the interaction elements and the intention natural language description information, reasoning result information is output, and the reasoning result information represents operation executed on the target interaction elements located at the target position in the tested Web page; and converting the reasoning result information into a machine executable instruction, and executing the machine executable instruction. According to the embodiment of the invention, the stability of Web automatic testing can be 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 a large language model agent security test method and device based on a model context agreement, and the method comprises the steps: firstly deploying a test tool in a test server, defining an application program interface which comprises function parameters and test probe parameters, describing the test probe parameters as necessary technical requirements for executing nominal functions, and executing the nominal functions according to the test probe parameters; and inducing the tested LLM agent to transmit complete session context data when calling. The test server receives a tool call request including a function parameter value and session context data, a back-end concurrently processes the request, executes a nominal function to generate a benign result, and extracts the session context data at the same time. Afterwards, a benign result is returned to the tested LLM agent, and the extracted data is asynchronously transmitted to a remote log server for recording as a test log. And finally, comparing the test log with the actual operation history, judging whether a session context data leakage vulnerability exists or not, and quantifying the severity level so as to detect whether the LLM agent leaks session memories such as the user interaction history or not.

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 an automatic UI self-healing test method and system based on multi-agent AI, and belongs to the technical field of automatic UI tests.The automatic UI self-healing test method comprises the steps that an original test script is semantized through a test reasoning interpretation class, and an expected intention is output; when the test fails, synchronously collecting multi-source data and extracting multi-modal features, constructing a fault propagation graph according to an expected intention and the multi-modal features, and performing fault propagation analysis by using a graph attention network to obtain a fault diagnosis result; according to a fault diagnosis result, a deep Q network, a greedy strategy and a Byzantine fault-tolerant algorithm are adopted to negotiate and decide a repair strategy through a distributed agent cooperation mechanism, and feedback is obtained; optimizing and dynamically adjusting the repair strategy and the test reasoning interpretation class through a meta-learning algorithm based on feedback; a test intention is deeply understood by constructing a test reasoning interpretation class, and fault diagnosis and automatic repair are cooperatively completed by adopting a distributed intelligent agent, so that the semantic understanding capability, the diagnosis accuracy and the repair success rate are improved.

Disclosed in the present application are an aircraft final assembly and integration testing platform and testing method. On the basis of a rational platform architecture, structured process data preparation, model-based operation guideline document preparation, and dispatch assistance decision-making are realized by means of an application layer, such that uniform data sources in the field of final assembly can be achieved. Data uploading and issuing between an industrial control network and an internal network, and data interaction control between layers are implemented by means of the mutually collaborative operation of the application layer, a storage layer, an edge layer and an execution layer, thereby improving the information acquisition efficiency and the operating efficiency. The edge layer and the execution layer collaboratively operate, so as to realize the interactive collaboration between the assembly guidance work for operators and automatic testing, thereby improving the efficiency of data information acquisition, operation instruction and fault handling during a final assembly and testing process of an aircraft.

An autonomous driving system test method, comprising: sampling scenario data of a plurality of scenarios (S10), and sending the scenario data of the plurality of scenarios to a plurality of simulation emulators (200) for distributed testing, so as to obtain test result data of the plurality of scenarios, the plurality of simulation emulators (200) being each integrated with an autonomous driving domain controller; and determining a dangerous scenario boundary for an autonomous driving system on the basis of the test result data of the plurality of scenarios (S20). The method is an improvement on the a scenario-based simulation test technology for autonomous driving systems, and using a server and a plurality of simulation emulators integrated with autonomous driving system domain controllers to perform joint testing can greatly improve the simulation test efficiency and the test effect for autonomous driving systems.

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.

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 discloses a shield tunneling stratum intelligent identification method and system based on strict single sample prototype network and verification set scale calibration, and the method comprises the steps: dividing samples collected from a shield tunneling machine in real time into a training set, a verification set and a test set according to a set time and an engineering interval; carrying out normalized preprocessing on the multi-dimensional mechanism parameters by adopting a training set, and then carrying out supervised pre-training on the lightweight MLP encoder by adopting a cosine interval classifier to obtain a discriminative embedding space; according to the method, a high-precision, reproducible and low-time-delay online recognition function on the shield tunneling stratum under the condition of extremely few labels is achieved, the overall precision and minority class recall can be considered on the premise that the labeling cost is not increased, so that the output probability is more calibrated, the expandability and rapid deployment capacity are achieved, and the method is suitable for popularization and application. And the real-time performance and the reliability of shield tunneling stratum identification are obviously improved.

The invention relates to the technical field of electronic measurement, in particular to a multifunctional comprehensive test method and system for a direct-current power supply, and the method comprises the steps: initializing a test; a static performance test step; a dynamic performance test step: driving a direct-current electronic load module to execute a time sequence instruction sequence in the dynamic load test file, and acquiring an output voltage and an output current waveform through a high-speed data acquisition module in the execution process; a ripple noise test step: switching the high-speed data acquisition module to an alternating current coupling mode and acquiring a high-frequency noise waveform in a constant load current section in the time sequence instruction sequence; a correlation analysis step; and a test termination step: controlling the load to return to zero and closing the tested DC power supply. Through automatic configuration and test execution of the system, the complexity of manual operation is reduced, and the test efficiency is improved. And especially in a high-frequency test scene, the test time is remarkably saved through automatic execution.

The invention discloses a website testing method and device based on multiple agents and a medium, and relates to the technical field of computers, the method comprises the steps of receiving a testing task, analyzing the testing task, determining a testing type contained in the testing task, and dividing the testing task into a plurality of testing subtasks based on the testing type; acquiring a corresponding test capability label, matching the test capability label with the test type, and respectively determining execution agents corresponding to the plurality of test sub-tasks; the test subtasks are concurrently sent to the corresponding execution agents, so that the test subtasks are concurrently executed through the execution agents; receiving test result data returned by the execution agent, and generating structured result data; and constructing a test result visual chart, and sending the test result visual chart to a front-end interface for display. The task is split according to the test type, and the intelligent agent with the corresponding capability is matched for testing, so that the website testing efficiency and the coverage integrity are improved, and the limitation of the traditional single-thread testing is broken through.

The invention relates to a method and device for predicting online open course learner satisfaction and electronic equipment, and the method comprises the steps: predicting the online open course satisfaction of students through an MLP and RBF neural network model by using a virtual learning environment of a large-scale online teaching and learning platform and combining learning behavior data in a learning management system (LMS); the model comprises a data acquisition and processing module, a multilayer perceptron (MLP) module, a radial basis function (RBF) neural network module, a classification tree module and a control block, the data acquisition and processing module is used for generating a training and testing data set, and the MLP and RBF neural network model predicts the satisfaction degree of a learner. The MLP model carries out feature extraction through a multi-layer perceptron structure and different activation functions, the RBF model measures the distance between input data and a center by using a radial basis function to realize feature extraction, the classification tree is used for judging a prediction model to which a data point belongs, the control block integrates features from the MLP and RBF neural network models, and the RBF model is used for determining a prediction model to which the data point belongs. Experimental results show that the prediction accuracy of low-satisfaction-degree learners and high-satisfaction-degree learners can be improved at the same time through the combination scheme of the MLP and the RBF, the method can be applied to learner satisfaction degree prediction of various online open courses, an educational institution is helped to know the satisfaction degree condition of students in time, course design and teaching strategies are optimized, and the teaching efficiency is improved. And important support is provided for teaching reform and optimization in the field of online education.

The invention discloses precise temperature control aging test equipment and a test method thereof.The precise temperature control aging test equipment comprises an electric control box body and a test box body, a test supporting frame is installed in the test box body, and a plurality of aging test plates are installed on the test supporting frame; the aging test board comprises a test circuit substrate and a plurality of aging test modules fixedly installed on the test circuit substrate, each aging test module comprises a test base and a heating control module, a material carrying groove is fixedly formed in each test base, each heating control module comprises an outer shell, a first circuit board, a second circuit board and a temperature measuring sensor, according to the invention, the independent temperature control aging test of a single chip is realized through the plurality of independent modular aging test modules, and the heating circuit and the control circuit are arranged separately, so that the service life of the test circuit is prolonged.

The invention discloses a test failure root cause diagnosis method, which relates to the technical field of electric digital data processing, and is characterized in that after a test failure signal is captured, comprehensive analysis is carried out in combination with multi-source log information of a test case and test environment configuration data, so that the influence of environment configuration on a test is fully considered, and information in a log is fully mined; according to the method, a more accurate diagnosis result is obtained, and a corresponding solution is matched according to a test failure root cause to solve the problem of test failure, so that the problems of low efficiency and high misjudgment probability of manual analysis, neglect of the influence of a test environment on the test failure, difficulty in identifying implicit connection between texts in a log and difficulty in testing failure in the prior art can be solved. Therefore, the technical problem that the obtained analysis result is difficult to be used for accurate root cause diagnosis is solved, the diagnosis efficiency of test failure root causes is improved, the diagnosis precision is improved, and the overall test period is shortened.

The invention provides a test data processing method and device, electronic equipment and a system, and relates to the technical field of data processing, and the method comprises the steps: obtaining at least one test picture and a test record table corresponding to a PCBA test; each test picture is used for representing the waveform change of the PCBA test; the test record table is used for representing a test value of the PCBA test; for each test picture, determining target naming data corresponding to the test picture based on a target test type of a target worksheet where a record file name corresponding to the test picture recorded in the test record table is located; renaming the test picture based on the target naming data; and filing the renamed test picture into a target folder corresponding to the target test type. According to the invention, automatic renaming and automatic filing of the test picture can be realized, and the processing efficiency and accuracy of the test data are improved.

The invention provides an intelligent test data generation and verification method and system based on a hierarchical architecture, and relates to the technical field of data generation, and the method comprises the steps: constructing a cross-layer constraint dependency graph by analyzing each layer of data mode and constraint and conversion logic of a hierarchical architecture software system; generating candidate test data meeting the constraint based on the dependency graph in a back-stepping manner, and verifying the candidate test data through projection; and iteratively optimizing the dependency graph and the test data by monitoring the difference between the actual execution and the prediction form. According to the method, cross-layer data consistency verification is realized, the test coverage rate and the defect detection efficiency are improved, and the quality risk of a software system is reduced.

A method is performed by a session management module and includes the steps described below. An update instruction sent by a target test module is received; a session table is queried according to identifier information corresponding to the target test module so that a listening module identifier set corresponding to the target test module is obtained; a demand instruction is sent to a listening module corresponding to each listening module identifier in the listening module identifier set; an acquisition instruction sent by the listening module is received and the acquisition instruction is sent to the target test module so that the target test module sends shared information to the session management module; the shared information corresponding to the shared information identifier sent by the target test module is received, and the shared information corresponding to the shared information identifier is sent to the listening module.

A data processing system implements after determining that a test in a target branch of a code repository starts failing, receiving a pull request (PR) onto the target branch and blocking the PR (invoking a build policy and a test policy); after determining that the failing test in the target branch is disabled, tracking the disabled test in a disabled test file; in response to a request to requeue the test policy, determining whether artifact in the build policy is identical with artifact in the test policy; when not identical, fetching all versions of the file within a time period, generating a union content of all versions of the file, and applying the requeued test policy using the union content, the time period being between a start time of the build policy and a start time of the requeued test policy; and unblocking the PR.

The invention relates to the technical field of probe testing, in particular to a PCB flying probe test path optimization method based on electrical characteristics, which comprises the following steps: calculating accessibility scores of test points according to the distribution of board surface test points and elements to determine risk types of the test points; determining a risk area grade corresponding to the grid unit according to the accessibility score in combination with the potential shadow area; optimizing the test path of the probe according to the risk area grade corresponding to the grid unit, and adjusting the initial moving speed of the test path of the probe in different grid units; for the same moving time sequence of different probe groups, determining overlapped grids according to the initial probe angles and the test paths corresponding to the probes, and determining whether there is a collision risk between the probes in combination with the initial moving speeds of the probes in different grid units; and when a collision risk exists between the probes, corresponding adjustment measures are taken according to the number of the overlapped grids. According to the invention, the test path is optimized in combination with multi-dimensional design based on the electrical characteristics and testability of the board.

The embodiment of the invention discloses an automatic testing method and system. The method comprises the following steps: constructing a dual-mode test architecture, and switching an upper computer and a test client between a cloud mode and a local mode to select a test mode; the test resources are communicated with the upper computer through the corresponding connection; starting an upper computer, automatically identifying and acquiring test resources, and establishing a test resource index table; the test client is started, and the test client receives the idle test resources and creates a test report. According to the method, the automatic testing method can be seamlessly switched between a cloud mode and a local mode by constructing a dual-mode testing architecture, the testing requirements of different scales and different scenes can be met, and the adaptability and flexibility of automatic testing are improved; by automatically identifying the test resources, automatic discovery of the test resources is realized, and the test resource index table is automatically established, so that the labor cost of access and configuration of the test resources is greatly reduced, and the utilization rate and the allocation efficiency of the test resources are improved.

The invention provides a storage equipment testing method and device and electronic equipment, and can be applied to the technical field of computers. The method comprises the steps that an initial test script is executed, target configuration parameters and target test strategies of the storage device are obtained, the initial test script comprises a diagnosis script and a test strategy matching script, the target configuration parameters are obtained by executing the diagnosis script, and the test strategy matching script is used for selecting the target test strategies based on the target configuration parameters; according to the target configuration parameters and the expected use duration of the equipment, a target test period is determined, and the target test period is a test period obtained after an initial test period in the initial test script is compressed; and obtaining a test evaluation report by using test execution information obtained by testing the storage device based on the target test period and the target test strategy.

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 chip test retrieval method and system based on a large model, and the method comprises the following steps: collecting chip test documents, and constructing a chip test vector knowledge base; receiving user query, and executing search in the knowledge base by using the word vector model structure; richer context information is generated based on a retrieval result and user query, and a test case or a test analysis report is generated through a fine-tuned large model. According to the method, the retrieval capability and the generation capability are effectively integrated, efficient retrieval of test instructions and knowledge and automatic generation of test cases / reports are achieved, and the chip test efficiency and quality are remarkably improved. Meanwhile, the retrieval generation system adopts a Django framework development platform, performs real-time streaming output and real-time feedback of retrieval results by means of the MyWebsocket technology, and writes question and answer data into MySQL. The system comprises a knowledge base construction module, a retrieval module, a generation module, a streaming interaction module and a data storage module. Compared with the prior art, the method has the advantages that the test instruction retrieval accuracy is improved by more than 18%, the test case generation time is shortened by 60%, and the test knowledge is shared and reused.

The invention relates to the technical field of industrial fault diagnosis, in particular to a multi-sensor and cross-working-condition industrial fault diagnosis method. The method comprises the following steps: S1, acquiring equipment operation data of a plurality of sensors under different working conditions through a data acquisition system, and dividing the equipment operation data into a training set, a verification set and a test set; s2, constructing the original data into a 3D space-time collaborative tensor as model input; s3, CBT, LMSCB, ESRM and KAN-TD are embedded into a network architecture, LightM-ConvKNet intelligent fault diagnosis modeling is completed, then pre-training of the model is completed by using a source domain sample, and fine tuning is performed on the model based on a target domain sample; and S4, inputting the target domain test set into the fine-tuned model to generate a fault diagnosis result. By adopting the method, the limitation of the CNN convolution kernel size is broken through, the local correlation among sensor data can be fully acquired, the parameter quantity is reduced, the calculation efficiency is improved, and the calculation complexity is reduced.

The invention provides a satellite-borne router network access test system and a test method thereof. The satellite-borne router network access test system comprises a constellation network node simulation platform, a performance test evaluation platform, an interface protocol conversion device, a constellation service traffic simulator and a network router digital model. Through joint simulation of the virtual nodes and the physical nodes, a simulation test platform can be provided for design and optimization of the satellite-borne router through scene simulation of a complex satellite network environment in a design stage, and the development efficiency is improved; on the other hand, in the product development and system test stage, the full-constellation operation scene can be simulated, the function and the performance of the satellite-borne router can be assessed and verified in the full-constellation scene in the ground environment, the method is particularly suitable for the low-orbit large-scale batch emission large-scale networking scene, the test coverage and the test effectiveness of the product are greatly improved, and the test cost is reduced. Development risks of insufficient verification, delayed verification time and the like before launching are effectively released, and meanwhile, the test verification cost is reduced.

The invention discloses an analog integrated circuit test method based on edge calculation, the method is executed by an edge node, and the method comprises the following steps: obtaining a step response waveform of an analog integrated circuit; extracting screening features from the step response waveform; determining an abnormal level and a test type of the screening feature; determining the demand level of the server for the original waveform data based on the abnormal level of the screening feature and the test type; and determining a sending strategy for sending the screening feature and the original waveform data to the server based on the demand level. According to the invention, waiting and repeated interaction of the server can be reduced, and test judgment efficiency and test throughput are improved.