30 results about "User testing" patented technology

The invention discloses a penetration test method and device based on a large language model, and the method comprises the steps: carrying out the analysis processing of input data according to the type of the obtained input data, and obtaining a penetration test target; the penetration test target comprises a user test target, first structured key information, second structured key information and an analysis result; based on the penetration test target, reasoning by constructing a penetration test task tree to obtain an optimized sub-task; the execution terminal executes the command to carry out penetration test to obtain a penetration test result; the terminal execution command is obtained by converting the preferable subtask. According to the invention, an automatic penetration test process driven by multi-source input data analysis and task reasoning can be realized, and the intelligent level and test efficiency of penetration test are improved.

The invention provides a comprehensive testing method and device for an agricultural machine microcontroller and a storage medium, and relates to the technical field of microcontroller testing. The method comprises the steps of firstly building a bidirectional data transmission link with a microcontroller to be tested, then converting a user test demand into a corresponding test instruction, issuing the test instruction, collecting original test data after a test is executed, carrying out standardization processing on the original data, evaluating a test state, if a result is abnormal, creating a correction response flow according to an abnormal type, and if the result is abnormal, completing the test. Re-establishing a link or evaluating to obtain a new result; according to the invention, automation and integration of the whole testing process are realized through a closed-loop process, a splitting link is not needed, manual equipment switching is not needed, comprehensive testing is completed in a one-stop manner, operation is greatly simplified, and efficiency is improved; the abnormality correction mechanism can optimize the process automatically, avoids test interruption, guarantees test continuity and reliability, and provides an efficient and stable solution for factory detection and regular maintenance of the agricultural machine microcontroller.

The invention belongs to the technical field of vehicle testing, and particularly relates to an intelligent analysis method, system and device for intelligent network connection vehicle test data and a medium, initial test data is received, and a test item identifier is printed based on a test event; generating a candidate test item option set according to a user test demand, and aggregating related data to form a target test item; generating a test strategy including test scenes, steps and evaluation indexes in combination with the knowledge base; analyzing data required by the strategy, and outputting an execution scheme; monitoring the environment and the data flow in real time during execution, and automatically repairing and recording when the environment and the data flow are abnormal; and if the test case fails, re-checking the associated exception record, and retrying after repairing if it is confirmed that the test case is caused by the exception. According to the invention, the intelligent and automatic formulation of the test scheme is realized, the reuse rate of historical test data is improved, and the reliability of test execution and the result accuracy are improved through environment monitoring and failure analysis.

The application discloses a dynamic plugging method in Java unit testing and belongs to the technical field of big data, and comprises defining three types of point interfaces, a point declaration and a point embedding, so as to solve the technical problem of providing different point implementation contents according to different user test scenes through the point declaration and the point embedding. The application is comprehensive and can cover more test scenes through plugging, including but not limited to extreme test condition construction, multi-thread scene testing, process / service shutdown testing and the like, and is flexible. In comparison with JMockit, the point embedding declaration position follows business code instead of unit test code.

The invention discloses a test case management method and device, equipment, a medium and a product. The method comprises the following steps: analyzing historical test data through a large model and a fault mode recognition model to obtain a private knowledge base of the large model; the private knowledge base comprises a base knowledge base and a dynamic association rule; based on user test requirements and a private knowledge base, test parameters meeting the user test requirements are determined through a large model; and generating a target SQL test case meeting the test requirements of the user according to the test parameters. According to the embodiment of the invention, the coverage rate and accuracy of the test case can be improved.

The FPGA prototype verification platform of the verifiable EMMC user interface of the application, by introducing the testcase module to output the user test instruction data corresponding to the same test operation of the EMMC chip connected with the user design interface to the EMMC chip, so as to determine whether the user design interface is correctly connected to the hardware link in the external EMMC chip through the FPGA prototype verification platform, and the problem positioning process is simplified.

The invention discloses an automatic test method and device for a vehicle, the vehicle and a storage medium, and the method comprises the steps: obtaining a plurality of vehicle test instructions and a user test demand, and the plurality of vehicle test instructions comprise a use case generation instruction, a task generation instruction and a use case execution instruction; generating a vehicle test case according to a user test demand and the case generation instruction; generating a vehicle test task according to the vehicle test case and the task generation instruction; and automatically testing the vehicle according to the vehicle test task and the use case execution instruction. The technical problem that in the prior art, when a large model is used for carrying out automatic testing on a vehicle, due to the fact that the large model is prone to illusion, the testing accuracy is low is solved.

The invention provides an automatic testing method and device for man-machine interaction software of a Kylin system, and solves the technical problem that an existing testing method consumes a large number of testing manpower resources. The method comprises the following steps: preparing a test environment and test data according to a test scene, and forming behavior quantitative data of user interaction according to an interaction purpose of a test process; forming a test script according to the behavior quantification data to simulate user operation in the test process; continuously capturing an interactive interface feedback area formed by user operation feedback in the test process, and identifying effective information of the feedback area to form test feedback data; and forming a test report by analyzing the test expected data and the test feedback data. The test efficiency is improved through simulation of user test behaviors, human errors are reduced, and the test reliability is improved. Meanwhile, the consumption of human resources is reduced, the time and cost of manual testing can be greatly reduced, more testing scenes and function points are covered, and the coverage rate of testing is increased.

The application discloses a user identification method, device, equipment and computer storage medium. The specific scheme comprises the following steps: obtaining user test report MR data of a target area to be identified in a preset time period, wherein the user MR data comprises latitude and longitude data of the user; determining a first user of the target area by using a preset clustering algorithm and the latitude and longitude data of the user, wherein the first user is a resident user in the target area; determining a first area in the target area according to the latitude and longitude data of the first user and a preset extension parameter; determining a second user in the first area by using a preset search algorithm according to the latitude and longitude data of the user in the first area and a preset distance threshold; and taking the first user and the second user as target users of the target area. According to the embodiment of the application, the accuracy of user identification of the target area can be improved.

The invention provides a system development workload determination method and device, equipment, a medium and a program product. Relates to the technical field of computers. The method comprises the steps of determining a first workload and a second workload according to a function point unit workload, a function point modification proportion, a function point complexity and a function point number corresponding to a stage in a demand analysis stage and a design development stage aiming at a data line demand in a system development process; in the integration testing stage, third workloads needed by stock function regression integration testing and difference function integration testing are determined, and in the user testing stage, fourth workloads needed by participation of developers are determined on the basis of the third workloads; and determining the total workload corresponding to the data line demand in the system development process. According to the scheme, the workload required for executing the function points can be subjected to fine-grained determination, and the workload can be determined more comprehensively and accurately by considering the investment of developers in a user test stage.

A method is provided for generating tests to distinguish between humans and computers. The computer may include a machine learning model. A reference sample is selected from a first category. A first plurality of samples are selected from the first category. The samples may be images. Adversarial examples are created for one or more of the first plurality of samples. Each of the adversarial examples is created for one or more other categories different from the first category. A second plurality of samples are selected from the one or more other categories different from the first category. Adversarial examples are created for the first category from one or more of the second plurality of samples. The reference sample and the first and second plurality of samples modified into adversarial examples are presented to a user for testing to determine whether the user is a human or a computer.

This invention discloses a method for rapid and stable temperature control of a refrigeration system compartment. The method includes: acquiring the current target temperature and the actual temperature of the temperature-controlled compartment; obtaining the current temperature deviation of the temperature-controlled compartment based on the current target temperature and the actual temperature; determining the current control mode of the electronic expansion valve of the temperature-controlled compartment based on the current temperature deviation and the preset temperature deviation; and adjusting the opening degree of the electronic expansion valve according to the current control mode. This method enables rapid and stable temperature regulation of the compartment, shortening the time for the compartment temperature to reach a stable state, allowing the equipment to quickly reach the testing state, improving user testing efficiency, and simultaneously reducing the output of the heater during temperature balancing, achieving energy-saving operation of the equipment.

The embodiment of the invention discloses an automatic testing method and device for an intelligent mattress, equipment, a medium and a product. The automatic testing method comprises the steps that at least one to-be-tested module is determined from a function module set of the intelligent mattress according to the testing requirement of a user; for any to-be-tested module, detection information corresponding to a test item of the to-be-tested module is extracted from the automatic standard test library, and the detection information comprises detection steps and detection standards; executing a detection step on the to-be-tested module to obtain detection data, the detection data including normal data and abnormal data; determining a test result of the to-be-tested module based on an analysis result of the abnormal data and the normal data; the test result comprises a reference judgment result of abnormal data; and determining a test report of the intelligent mattress based on the test result of each to-be-tested module. According to the technical scheme, automatic testing of the intelligent mattress is achieved, the labor cost and personal errors are reduced, and the accuracy and reliability of intelligent mattress testing are improved.

The application provides a multi-user test method, system and electronic device, comprising: in response to receiving a session creation request, generating a test session corresponding to the session creation request and storing; in response to receiving at least one test instruction, obtaining a target test session corresponding to each test instruction in the at least one test instruction in at least one configured test session respectively, and respectively delivering test engineering information of each target test session to a corresponding test head, so that the test head corresponding to each target test session tests a device under test based on the corresponding test engineering in parallel. Thus, the same chip test equipment can support differentiated test tasks of different devices under test, greatly improving the utilization rate, test concurrency rate and execution efficiency of the chip test equipment, and significantly enhancing the business competitiveness.

The invention discloses an ARM-based test method, device and equipment and a storage medium, and belongs to the technical field of computers, the method comprises the following steps: obtaining a test demand instruction input by a user, and analyzing the test demand instruction to obtain user test demand information; extracting a test demand type based on the user test demand information; based on the test demand type, obtaining a first test data set corresponding to the test demand type; analyzing the test data, and updating the first test data based on an analysis result to obtain a second test data set; and testing the second test data set to obtain a test result. According to the method and the device, the corresponding first test data set is accurately acquired according to the type of the test requirement, and the first test data set is analyzed and further updated, so that the test is more accurate, and the technical problem that the test effect is poor when the test is performed based on the ARM embedded platform is solved.

The embodiment of the invention discloses a fault management method of a comprehensive signal analyzer. The method comprises the following steps: acquiring equipment position information and user information of the comprehensive signal analyzer; based on the equipment position information and the user information, simulation test parameters are determined, and the simulation test parameters are sent to a comprehensive signal analyzer; the simulation test parameters comprise emission parameters of the comprehensive signal analyzer; in response to the obtained user analysis result of the comprehensive signal analyzer, determining a user test score of the user based on the user analysis result of the comprehensive signal analyzer, the analysis difficulty of the simulation test parameters and the evaluation difficulty of the user; the difficulty assessment refers to assessment according to the ability level of the user participating in the test, and then matching and determining the acceptable test difficulty of the user; and determining first fault information based on the user test score of the user, wherein the first fault comprises whether the integrated signal analyzer has a fault or not.

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.

Hardness tester (100), comprising: an intruder (1); a test force loading unit (11, 12) that applies a test force to the indenter (1) and presses the indenter (1) against a sample; a detector (13) that records a value for the test force applied to the indenter (1) by the test force loading unit (11, 12); and a control unit (19) which, in a state in which a predetermined test force is applied to the indenter (1) by the test force load unit (11, 12), and when the value of the test force detected by the detector (13) exceeds a predetermined permissible tolerance relative to the predetermined test force, executes a predetermined process, where the predetermined process includes at least one of an interruption process that interrupts the currently executed test, and a notification process that notifies a user that the value of the test force has exceeded the permissible tolerance during the execution of the test, characterized in that: when the controller (19) executes the interruption process, and after the interruption process has been executed, the controller (19) controls the test force loading unit (11, 12) and reduces the test force applied to the indenter (1) to a preset predetermined value; and The hardness testing device (100) further comprises: a sample table (15) on which the sample is to be placed; and a sample table lifting device (16) which raises and lowers the sample table (15), wherein, after the test force applied to the indenter (1) reaches the predetermined value, the control unit (19) controls the sample table lifting device (16) to lower the sample table (15).

An online concierge system generates an aggregated lift score for a test feature for the online concierge system. The online concierge presents prioritized items from a set of item groups to two sets of users: a test set and a control set. The online concierge system uses the test feature to present prioritized items to users in the test set, and the online concierge system uses existing functionality to present prioritized items to users in the control set. For each test group, the online concierge system creates holdout subsets out of the test set and the control set. The online concierge system tracks user interactions with items in an item group and computes a group lift score for the item group. The online concierge system generates an aggregated lift score for the test feature based on the group lift scores and presents items to users based on the aggregated lift score.

Disclosed are a system, method, and computer program product for developing and evaluating a prototype parameterized cell (P-PCELL) for a specific integrated circuit component. The P-PCELL is developed using multiple graphic design system (GDS) files for the component and a mapping file. Optionally, P-PCELL development is performed using a first machine learning model. Optionally, the P-PCELL is also evaluated based on test feedback acquired through user-testing including, for example, design rule checking (DRC) errors. Updates (e.g., design manual and / or parameter range updates) can be developed given the DRC errors. Optionally, development of the updates is performed using a second machine learning model. P-PCELL evaluation can further include determining P-PCELL code functionality, de-bugging the P-PCELL code, detecting any irregularities in the P-PCELL (e.g., based on a comparison of user-customized configurations with specifications and the GDS files) and correcting such irregularities.

The invention relates to the technical field of intelligent product design, and discloses an intelligent product design method and system based on big data and axiom design. According to the method, user comment data is analyzed, and an improvement-needing degree quantitative index fusing attention and satisfaction is constructed to determine a design priority; taking the index as input, driving an axiom design theory to perform zigzag mapping and decomposition, guiding design decoupling according to data priority in the process, and outputting a design parameter set meeting the independence axiom; and finally, quantitatively evaluating the effectiveness of different design elements through a hierarchical generation scheme and user testing, and feeding back to a front end to form a closed loop. According to the method, automatic and precise conversion from subjective user feedback to an objective and non-coupling design scheme is achieved, the core problems that in a traditional design process, requirements are fuzzy, experience is relied on, and attribution is difficult to verify are solved, and design scientificity and efficiency are remarkably improved.

The invention relates to a configurable NPU general test framework and test method, electronic equipment and a storage medium. The method comprises the following steps that: an application layer receives a user test demand analysis configuration file, and initializes a scheduling module, a log module and a performance statistics module of a core framework; the hardware layer provides a software development kit SDK of neural network processor NPU hardware; the adaptation layer selects to dynamically load a manufacturer adaptation library according to configuration information analyzed by a user test requirement, and calls a hardware initialization interface of the hardware layer; and the core framework layer carries out common logic testing according to task demand analysis. According to the invention, through parameterization demand configuration, generalization module packaging and differentiation interface adaptation test methods, the problem of existing NPU test pain points is solved; a standardized test process is provided, bottom layer hardware differences are shielded, the method can be applied to NPU hardware tests in numerous scenes, test cost is reduced, adaptation efficiency is improved, unification of test standards is achieved, and NPU test efficiency and compatibility in complicated scenes are remarkably improved.

A system is provided.SOLUTION: A means for a user to upload curriculum vitae and a skill sheet, a means for an end company to input detailed matter information, and a means for comparing the curriculum vitae and the skill sheet with the detailed matter information by a AI algorithm; Means for generating a matching talent list, means for notifying an end company and a user of the generated matching candidate list, means for generating a skill check test based on detailed matter information, means for transmitting the skill check test to the user and receiving a test result of the user, means for transmitting the received skill check test result to the end company, means for uploading a self-PR moving image by the user, and means for analyzing the uploaded moving image by an AI algorithm, this system includes a means for evaluating a non-technical aspect, a means for transmitting an evaluation result to an end enterprise, a means for allowing the end enterprise to select the optimal personnel on the basis of collected information, and a means for notifying a user of a final selection result.SELECTED DRAWING: Figure 1

The invention discloses a minium automatic script generation system and method based on an AI large model, and belongs to the technical field of software test automation. Analyzing a user test intention through an artificial intelligence model, generating a test logic sequence, and synchronously generating an expected data change for each operation step; and when the generated test script is executed, starting a parallel whole-course visual verification process, extracting visual observation data through real-time screen capture and an OCR / image recognition technology, and comparing the visual observation data with corresponding expected data in real time so as to verify the semantic correctness of each step of operation. And when script execution fails or visual verification is not passed, the system feeds back an error context to the AI model for intelligent diagnosis and repair. The method further comprises element positioning based on multi-modal fusion, and the self-evolution of the system is realized through reinforcement learning and a graph semantic knowledge base.

This invention relates to a test case recommendation method, apparatus, storage medium, and electronic device. The method classifies the popularity level of each function based on the number of times each function is called in the first test code, determines the association level between each test case and each function based on code coverage information between each test case and each function, and then automatically generates recommended test cases that best meet the user's testing needs based on the popularity level information and association level information of each function in the second test code, as well as the popularity level information and association level information of the input recommended test cases. This method can effectively improve software testing efficiency.

A system is provided.SOLUTION: Means for a user to input and register a name, an age, a language proficiency, and a learning purpose, means for a server to receive the input information and generate a user profile, and means for the server to generate a test for initial evaluation based on the user profile; Means for collecting a test result of the user by the terminal and transmitting the test result to the server, means for analyzing the test result by the server and generating an individual learning path by the server, means for selecting learning content based on the learning path generated by the server and transmitting the learning content to the terminal, means for recording a learning progress of the user by the terminal and transmitting the learning progress to the server, means for analyzing progress data and optimizing the learning path and the content by the server, and means for providing feedback on the learning content by the user, the system including means for the server to analyze the feedback and make system-wide adjustments.SELECTED DRAWING: Figure 1

The invention provides a battery management system hardware-in-the-loop test system and method, and the system comprises an intelligent case generation engine which generates a test case set through a combined test algorithm module and a reinforcement learning agent module according to the test demands of a user; the dynamic model scheduler is used for dynamically switching the battery models according to the test stage; the parallelization controller is used for intelligently analyzing and decomposing the test case set into a plurality of mutually independent test sub-tasks by applying a containerization technology and executing the test sub-tasks in parallel; the test executor obtains test case scripts of the test subtasks from the parallelization controller and sends excitation signals to the hardware interface layer strictly according to a time sequence; the hardware interface layer comprises a virtualized hardware adaptation layer and is in signal connection with the battery management system to be tested; and the real-time database is used for storing the original data from the test actuator, the task state of the parallelization controller, the model parameters of the dynamic model scheduler and the response data collected from the battery management system in real time.

The utility model provides a hinge buffer support test equipment, including test door, test buffer hinge, test frame, test device, test buffer hinge is hinged on test door and test frame respectively, and test device includes bearing detection component, angle detection component, buffer detection component, adopts the structure cooperation of bearing detection component, angle detection component and buffer detection component, simple structure, practical and reliable, and has the adjustment function, can adjust the initial angle of weight height and test door, sets up different test environment, is convenient for user test operation and uses, is favorable to the analysis underlink performance of different test parameters, can provide certain data source for research analysis for scientific researchers.

Apparatuses, methods, and systems for determining winning arms of electronic testing. One method includes obtaining historical data values related to the A / B test of a user, storing the historical data values, determining a historical weight for the historical data values, receiving new data values from the plurality of computing devices collected based on recipient actions during execution of the A / B, constructing a Dirichlet distribution, inferring corresponding central tendencies of samplings of a metric distribution, wherein each central tendency of the corresponding central tendencies is determined by sampling the Dirichlet distribution, constructing an overall utility distribution for each arms of the A / B test by combining the central tendency of each sampling of the metric distribution with a corresponding sampling of a conversion probability distribution, determining a winning arm of the A / B testing by comparing the overall utility distribution of each arm with each other arm of the A / B test.

A biological test system has receptacles for a variety of removable electro-mechanical biological blood test-based elements having multiple features such as lancets or strips. Testing is through an analysis biological test processor that provides results to a user test output with all designed to be contained in a pocket-transportable user biological test form factor that houses all elements. Biological test elements can be interchanged for multiple sensing modalities with automatic activation based on cartridge insertion of a glucose test element, an A1C test element, a ketone test element, or the like. Designs can include a user sampler configuration selector for a user sampling selection that may be analyzed so a user-personalizable, biological sampler control processor can automatically disable operation for test safety if a user sampling selection is determined to be unacceptable. The system can also provide a user cartridge action prompt, a user reselection prompt, or other action to clear the disable.