Intelligent testing method and system based on object model, terminal and storage medium

Abstract

The invention discloses an intelligent testing method and system based on an object model, a terminal and a storage medium, and the method comprises the steps: obtaining the equipment information of to-be-tested intelligent equipment, and constructing the object model according to the equipment information; generating a test case according to the object model; using the test case to test the object model; collecting feedback information of the object model in a test process, and analyzing according to the feedback information to obtain a test result; and evaluating the performance and the stability of the intelligent equipment according to the test result. By constructing the physical model, the function, performance, stability and other aspects of the intelligent equipment are tested, the test efficiency is improved, the test cost is reduced, and an effective test guarantee is provided for intelligent equipment research and development and production enterprises.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent device testing, and particularly to an intelligent testing method, system, terminal and computer-readable storage medium based on a thing model. Background Art

[0002] An intelligent device refers to a device integrated with computing power, sensors, network connections and software functions, which can perform specific tasks through data collection, analysis and interaction to improve efficiency, convenience and user experience. With the development of technologies such as the Internet of Things, big data, and artificial intelligence, intelligent devices are increasingly widely used in various fields. The thing model is a tool for abstracting and modeling objects in the real world, mainly used in the field of the Internet of Things (IoT). It can describe the attributes, behaviors and relationships of objects, helping developers better understand and manage physical devices. In practical applications, the correctness and stability of the thing model are crucial for system operation.

[0003] However, the performance and stability of intelligent devices are directly related to the user experience. Therefore, it is particularly important to conduct comprehensive testing on intelligent devices. Traditional testing methods have problems such as low testing efficiency, high testing cost, and incomplete coverage, making it difficult to meet the testing requirements of intelligent devices.

[0004] Therefore, the existing technology still needs to be improved and developed. Summary of the Invention

[0005] The main purpose of the present invention is to provide an intelligent testing method, system, terminal and computer-readable storage medium based on a thing model, aiming to solve the problems in the existing technology that when testing intelligent devices, there are problems such as low testing efficiency, high testing cost, incomplete coverage, and difficulty in meeting the testing requirements of intelligent devices.

[0006] To achieve the above purpose, the present invention provides an intelligent testing method based on a thing model. The intelligent testing method based on a thing model includes the following steps:

[0007] Obtain the device information of the intelligent device to be tested, and construct a thing model according to the device information;

[0008] Generate test cases according to the thing model;

[0009] Use the test cases to test the thing model;

[0010] Collect the feedback information during the testing process of the thing model, and analyze the feedback information to obtain a test result;

[0011] Evaluate the performance and stability of the intelligent device according to the test result.

[0012] Optionally, in the intelligent testing method based on the physical model, the obtaining of the device information of the intelligent device to be tested and constructing the physical model according to the device information specifically includes:

[0013] Obtain the device information of the intelligent device to be tested, and collect the attribute data of the entity objects related to the functions of the intelligent device according to the test requirements;

[0014] Construct a virtual physical model by using computer-aided design software according to the device information and the attribute data;

[0015] Wherein, the device information includes device type, device function, communication protocol, data format, device status and device attributes, and the attribute data includes size, weight and material.

[0016] Optionally, in the intelligent testing method based on the physical model, the generating of test cases according to the physical model is specifically:

[0017] Generate corresponding test cases according to the attributes, services and events in the physical model, and the test cases cover all function points and boundary conditions of the device.

[0018] Optionally, in the intelligent testing method based on the physical model, the using of the test cases to test the physical model specifically includes:

[0019] Generate characteristic data by using the physical model, put the characteristic data into the resource pool, and simulate the test scenarios in the real environment, where the test scenarios include normal scenarios, abnormal scenarios and stress scenarios;

[0020] Run the test cases to test the physical model under different test scenarios.

[0021] Optionally, in the intelligent testing method based on the physical model, the collecting of the feedback information during the testing process of the physical model and analyzing according to the feedback information to obtain the test result specifically includes:

[0022] Collect the feedback information during the testing process of running the test cases on the physical model, where the feedback information includes processing accuracy rate, device response time, abnormal handling ability and device stability;

[0023] Record the test log in real time, where the test log includes time stamp, input data, output result and resource occupancy rate, and generate a visual curve graph;

[0024] Conduct summary analysis according to the feedback information and the visual curve graph to obtain the test result of the physical model.

[0025] Optionally, in the above-described object model-based intelligent testing method, the evaluating the performance and stability of the intelligent device according to the test result specifically includes:

[0026] Statistically analyze the test result, and extract key index data from the test result;

[0027] Evaluate the performance and stability of the intelligent device according to the key index data.

[0028] Optionally, in the above-described object model-based intelligent testing method, after collecting the feedback information of the object model during the test and analyzing the feedback information to obtain a test result, it further includes:

[0029] Compare the performance of the object model in different test scenarios to obtain potential problems;

[0030] Generate an object model optimization plan according to the potential problems;

[0031] Adjust the object model parameters according to the object model optimization plan, and retest the object model with the adjusted parameters using the test case until the object model meets the design requirements.

[0032] In addition, to achieve the above object, the present invention further provides an object model-based intelligent testing system, wherein the object model-based intelligent testing system includes:

[0033] An object model construction module, configured to obtain device information of an intelligent device to be tested, and construct an object model according to the device information;

[0034] A test case generation module, configured to generate test cases according to the object model;

[0035] An object model testing module, configured to test the object model using the test cases;

[0036] A test analysis module, configured to collect feedback information of the object model during the test, and analyze the feedback information to obtain a test result;

[0037] A performance evaluation module, configured to evaluate the performance and stability of the intelligent device according to the test result.

[0038] In addition, to achieve the above object, the present invention further provides a terminal, wherein the terminal includes: a memory, a processor, and an object model-based intelligent testing program stored on the memory and executable on the processor. When the object model-based intelligent testing program is executed by the processor, the steps of the above-described object model-based intelligent testing method are implemented.

[0039] In addition, to achieve the above object, the present invention further provides a computer-readable storage medium, wherein the computer-readable storage medium stores an intelligent test program based on an object model, and when the intelligent test program based on the object model is executed by a processor, the steps of the intelligent test method based on the object model as described above are implemented.

[0040] In the present invention, device information of an intelligent device to be tested is obtained, and an object model is constructed according to the device information; test cases are generated according to the object model; the object model is tested using the test cases; feedback information during the test process of the object model is collected, and a test result is obtained by analyzing the feedback information; the performance and stability of the intelligent device are evaluated according to the test result. The present invention realizes the testing of functions, performance, stability, etc. of an intelligent device by constructing an object model, improves the testing efficiency, reduces the testing cost, and provides an effective testing guarantee for intelligent device R & D and production enterprises. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1 is a flowchart of a preferred embodiment of the intelligent test method based on an object model of the present invention;

[0042] Figure 2 is a structural diagram of a preferred embodiment of the intelligent test system based on an object model of the present invention;

[0043] Figure 3 is a structural diagram of a preferred embodiment of a terminal of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0044] To make the object, technical solution and advantages of the present invention clearer and more definite, the present invention will be further described in detail below with reference to the accompanying drawings and by way of examples. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0045] The intelligent test method based on an object model according to a preferred embodiment of the present invention, as Figure 1 shown, the intelligent test method based on an object model includes the following steps:

[0046] Step S10: Obtain device information of an intelligent device to be tested, and construct an object model according to the device information.

[0047] Specifically, obtain the device information of the intelligent device to be tested, and collect the attribute data of the entity objects related to the functions of the intelligent device according to the test requirements; construct a virtual physical model using computer-aided design software based on the device information and the attribute data; wherein, the device information includes device type (such as intelligent door lock, intelligent light bulb, intelligent socket, intelligent thermostat, etc.), device functions (the list of functions supported by the device, such as switch, brightness adjustment, temperature control, etc.), communication protocol (the communication protocol used by the device, such as Wi-Fi, Zigbee, Bluetooth, etc.), data format (the data format for sending and receiving by the device, such as JSON, XML, etc.), device status (the possible status of the device, such as on / off, online / offline, etc.) and device attributes (such as measurable attributes like temperature, humidity, brightness, etc.), and the attribute data includes size, weight and material.

[0048] For example, collect the attribute data of objects in the real world (specifically the entity objects related to the functions of the intelligent device to be tested, such as face, fingerprint, card key, palm vein, finger vein), such as size, weight, material, etc., and determine the quantity through collaborative collection according to the test requirements (such as single device test requires a single object model, multi-device linkage test requires multiple associated object models).

[0049] For example, taking an intelligent door lock as an example, collect the biometric and physical verification data directly related to the unlocking function of the intelligent door lock through devices such as dedicated sensors and cameras, specifically including:

[0050] (1) Biometric data:

[0051] Face data: Collect face images / video streams (including different angles, lighting conditions, occlusion scenarios) through an infrared camera or an RGB camera;

[0052] Fingerprint data: Collect fingerprint images or feature templates (including wet / dry fingers, worn fingerprints) through a capacitive or optical fingerprint sensor;

[0053] Palm vein / finger vein data: Collect vein distribution maps (including different hand postures, temperature changes) through a near-infrared sensor.

[0054] (2) Physical verification data:

[0055] Card key data: Collect the unique identifier of the card, encryption protocol and signal strength through an RFID / NFC reader;

[0056] Temporary password data: Collect the generation logic of the dynamic password and transmission encryption parameters through a Bluetooth / Wi-Fi module.

[0057] (3) Environmental auxiliary data:

[0058] Illumination intensity: The environmental light parameter that affects face recognition (such as lux value);

[0059] Temperature and humidity: Environmental parameters that affect sensor performance (such as the error tolerance of the fingerprint module under high humidity);

[0060] Electromagnetic interference: Test the stability of the card key in a complex electromagnetic environment.

[0061] Data normalization processing: Convert the original data into a unified format (such as normalizing the face image to 256×256 pixels and encoding the fingerprint template as a binary file), and add metadata tags (such as acquisition time, environmental parameters, device model) to facilitate subsequent model construction and testing.

[0062] Use 3D scanning technology to obtain the appearance and structural data of the object, and conduct mechanical, thermal and other performance tests on the object to obtain relevant parameters.

[0063] According to the collected data, use computer-aided design software (CAD) to construct a physical model, including appearance, structure, behavior, etc. Add attributes such as materials and textures to the physical model to make it closer to the real object, set the behavior rules of the physical model, such as movement, deformation, etc., and construct a scene, such as lighting, humidity, temperature, and various external factors affecting unlocking.

[0064] Step S20, generate test cases according to the physical model.

[0065] Specifically, the physical model is an abstract description of the device's functions, usually including properties: describing the device's state, such as temperature, humidity, etc.; services: the functions provided by the device, such as switching, adjusting brightness, etc.; events: the events triggered by the device, such as alarms, status changes, etc. The virtual physical model can not only simulate the behavior of the device, but also provide strong support for the development and optimization of the device.

[0066] Generate corresponding test cases according to the properties, services and events in the physical model, including normal use scenarios, extreme working conditions, etc. The test cases cover all functional points and boundary conditions of the device (that is, the test cases should cover the properties, services and events of the device, and consider normal situations, boundary situations and abnormal situations).

[0067] Attributes, services, and events of the analyte model. List all attributes, services, and events, and understand the semantics and constraints of each attribute, service, and event. Determine the test scenarios: normal scenario - the behavior of the device under normal conditions; boundary scenario - the behavior of the device under boundary conditions (such as minimum and maximum values); abnormal scenario - the behavior of the device under abnormal conditions (such as invalid input, communication interruption). Design test cases for each attribute, service, and event to ensure coverage of all scenarios; through the attributes, services, and events of the analyte model, test cases can be systematically generated to cover normal, boundary, and abnormal scenarios. Automatically generating test cases can improve efficiency and ensure the comprehensiveness and accuracy of testing. Ultimately, the execution and optimization of test cases will help verify the functionality and stability of intelligent devices.

[0068] Step S30: Use the test cases to test the thing model.

[0069] Specifically, use the thing model to generate feature data, put the feature data into the resource pool, and simulate test scenarios in the real environment. The test scenarios include normal scenarios, abnormal scenarios, and stress scenarios; run the test cases to test the thing model under different test scenarios, and record the performance of the thing model in each test scenario.

[0070] The following are the detailed steps for testing the thing model using test cases:

[0071] Step 1: Load the thing model and test cases: Load the thing model and the generated test cases from a file. Ensure that the virtual implementation of the thing model is consistent with the test cases.

[0072] Step 2: Implement the virtual thing model: Implement a virtual device according to the thing model to simulate the behavior of an actual device. The virtual device should support attribute reading, service invocation, and event triggering.

[0073] Step: Write test scripts: Use a test framework (such as pytest) to write test scripts to execute the test cases and verify the results.

[0074] Step 4: Execute the tests: Run the test scripts to execute all test cases. Record the test results and logs.

[0075] Step S40: Collect the feedback information of the thing model during the test process, and analyze the feedback information to obtain the test results.

[0076] Specifically, collect the feedback information of the object model during the test process of running the test case. The feedback information includes processing accuracy rate, device response time, exception handling ability, and device stability. Record the test log in real time. The test log includes time stamps, input data, output results, and resource occupancy rate, and generate a visualization curve graph. Conduct summary analysis based on the feedback information and the visualization curve graph to obtain the test result of the object model.

[0077] Step S50: Evaluate the performance and stability of the intelligent device according to the test result.

[0078] Specifically, conduct statistics and analysis on the test result, and extract the key index data (such as function index, performance index, stability index, communication index) in the test result. Evaluate the performance and stability of the intelligent device according to the key index data. Evaluate the performance and stability of the intelligent device according to the key index data:

[0079] (1) Performance evaluation:

[0080] Response time: If the average response time is within the expected range, it indicates that the device performance is good; otherwise, it is necessary to optimize the device logic or communication protocol.

[0081] Throughput: If the device can still maintain a high throughput under high load, it indicates that its performance is strong; otherwise, it is necessary to optimize the resource allocation or algorithm.

[0082] Resource occupancy: If the resource occupancy is too high, it may cause the device performance to decline, and it is necessary to optimize the code or hardware configuration.

[0083] (2) Stability evaluation:

[0084] Failure rate: If the failure rate is low, it indicates that the device stability is good; otherwise, it is necessary to repair the high-frequency failure points.

[0085] Recovery time: If the device can quickly recover from the failure, it indicates that its fault tolerance ability is strong; otherwise, it is necessary to optimize the fault recovery mechanism.

[0086] Continuous operation time: If the device can run without failure for a long time, it indicates that its stability is high; otherwise, it is necessary to troubleshoot potential problems.

[0087] (3) Communication evaluation:

[0088] Communication success rate: If the communication success rate is high, it indicates that the interaction between the device and the external system is stable; otherwise, it is necessary to optimize the communication protocol or network configuration.

[0089] Communication delay: If the communication delay is within the acceptable range, it indicates that the device meets the real-time requirement; otherwise, it is necessary to optimize the communication mechanism.

[0090] Generate an evaluation report based on the analysis results, including a test overview: test objectives, test environment, and test tools; key metric data: specific data on functions, performance, stability, and communication metrics; problem analysis: list the discovered problems and their causes; improvement suggestions: put forward specific improvement suggestions for the problems. By statistically analyzing the test results and extracting key metric data, the performance and stability of intelligent devices can be comprehensively evaluated. The evaluation report provides a clear direction for the optimization and improvement of the devices, ensuring their reliability and efficiency in actual use.

[0091] In addition, compare the performance of the object model in different test scenarios to obtain potential problems; generate an object model optimization plan based on the potential problems; adjust the object model parameters according to the object model optimization plan, and retest the object model with the adjusted parameters using the test cases to verify the optimization effect. Repeat the optimization and testing until the object model meets the design requirements. For example, repair the problems of virtual devices or object models according to the test results, add new test cases based on the test coverage analysis, and optimize the performance of virtual devices to ensure their stability under high loads. By setting up a test environment, implementing a virtual object model, writing test scripts, and executing test cases, the functions and performance of the object model can be systematically verified. The analysis and optimization of test results will help improve the quality and stability of intelligent devices.

[0092] Taking an intelligent door lock as an example, the automated test process is as follows:

[0093] (1) Random selection of test objects:

[0094] Randomly select one or more unlocking object types (such as fingerprints, faces, card keys) from the database, and randomly extract the corresponding test samples (such as fingerprint images of different users, face data under different lighting conditions).

[0095] (2) Dynamic configuration of test scenarios:

[0096] Normal scenario: Simulate the standard unlocking process (such as a user normally pressing a fingerprint, facing the face camera).

[0097] Abnormal scenario: Inject interference data (such as blurred fingerprints, blocked faces, damaged card keys).

[0098] Stress scenario: High-frequency continuous unlocking requests (such as 10 fingerprint verifications per second), mixed testing of multiple types (triggering face and card unlocking simultaneously).

[0099] (3) Test execution and data injection:

[0100] Inject test data into the physical model in real time through a virtualized interface (such as simulating the Bluetooth protocol of a door lock), for example, sending fingerprint electrical signals through a capacitance sensor simulation module, inputting a face image stream through a virtual camera, and sending encrypted key signals through an RFID simulator, etc.

[0101] (4), Performance and stability evaluation:

[0102] Key indicators:

[0103] Recognition accuracy: Number of correct recognitions / total number of tests (e.g., fingerprint matching success rate ≥ 99.9%);

[0104] Response time: Time taken from data input to unlocking feedback (e.g., average time taken for face recognition < 0.8 seconds);

[0105] Abnormal handling ability: False recognition rate (FAR ≤ 0.01%) and missed recognition rate (FRR ≤ 0.1%) for forgery attacks (such as silicone fingerprint membranes);

[0106] Stability: Failure rate during continuous operation for 24 hours (e.g., no downtime, no memory leaks).

[0107] Automated monitoring: Real-time record of test logs (such as timestamps, input data, output results, resource occupancy rate), and generation of visualization curve graphs (such as response time trends, CPU load fluctuations).

[0108] (5), Test report generation:

[0109] Automatically summarize test results, mark non-compliant items (such as the recognition rate of a certain batch of fingerprint templates being lower than the threshold in a humid environment); provide optimization suggestions (such as adjusting fingerprint algorithm parameters, enhancing face liveness detection logic).

[0110] At the same time, store the collected data, physical model parameters, and test results in the database.

[0111] Advantages of the present invention:

[0112] (1), Through the construction of the physical model, the present invention realizes the comprehensive testing of intelligent devices and improves the test coverage.

[0113] (2), By adopting an automated testing method, the test efficiency is improved and the test cost is reduced.

[0114] (3), The test results have high consistency and reliability, providing effective test guarantees for intelligent device R & D and production enterprises.

[0115] The present invention can be widely applied to fields such as smart home, smart hardware, Internet of Things, industrial Internet, etc., providing technical support for the testing of various intelligent devices, such as:

[0116] (1), Product Design: In the product R & D stage, evaluate the performance of the design scheme through an intelligent testing system, discover problems in advance, and reduce R & D risks.

[0117] (2), Production Manufacturing: Conduct simulation tests on key links in the production process to improve production efficiency and quality.

[0118] (3), Training and Education: Use virtual object models for hands-on training to reduce training costs and improve training effects.

[0119] (4), Maintenance and Repair: Provide a reference basis for equipment maintenance and repair through simulation tests.

[0120] Furthermore, as Figure 2 shown, based on the above intelligent testing method based on the object model, the present invention also correspondingly provides an intelligent testing system based on the object model, wherein the intelligent testing system based on the object model includes:

[0121] An object model construction module 51, configured to obtain device information of an intelligent device to be tested, and construct an object model according to the device information;

[0122] A test case generation module 52, configured to generate test cases according to the object model;

[0123] An object model testing module 53, configured to test the object model using the test cases;

[0124] A test analysis module 54, configured to collect feedback information during the testing process of the object model, and analyze the feedback information to obtain a test result;

[0125] A performance evaluation module 55, configured to evaluate the performance and stability of the intelligent device according to the test result.

[0126] Furthermore, as Figure 3 shown, based on the above intelligent testing method and system based on the object model, the present invention also correspondingly provides a terminal, which includes a processor 10, a memory 20, and a display 30. Figure 3 Only some components of the terminal are shown, but it should be understood that it is not required to implement all the shown components, and more or fewer components can be alternatively implemented.

[0127] The memory 20 may be an internal storage unit of the terminal in some embodiments, such as the hard disk or memory of the terminal. The memory 20 may also be an external storage device of the terminal in other embodiments, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) card, a Flash Card, etc. equipped on the terminal. Further, the memory 20 may include both the internal storage unit of the terminal and the external storage device. The memory 20 is used to store application software installed on the terminal and various types of data, such as the program code for installing the terminal. The memory 20 may also be used to temporarily store data that has been output or will be output. In one embodiment, an intelligent test program 40 based on the object model is stored on the memory 20, and the intelligent test program 40 based on the object model can be executed by the processor 10, so as to implement the intelligent test method based on the object model in this application.

[0128] The processor 10 may be a central processing unit (CPU), a microprocessor, or other data processing chips in some embodiments, and is used to run the program code stored in the memory 20 or process data, such as executing the intelligent test method based on the object model.

[0129] The display 30 may be an LED display, a liquid crystal display, a touch liquid crystal display, and an OLED (Organic Light-Emitting Diode) toucher, etc. in some embodiments. The display 30 is used to display information on the terminal and to display a visual user interface. The processor 10, the memory 20, and the display 30 of the terminal communicate with each other through a system bus.

[0130] In one embodiment, when the processor 10 executes the intelligent test program 40 based on the object model in the memory 20, the following steps are implemented:

[0131] Obtain the device information of the intelligent device to be tested, and construct an object model according to the device information;

[0132] Generate test cases according to the object model;

[0133] Use the test cases to test the object model;

[0134] Collect the feedback information of the object model during the test process, and analyze the feedback information to obtain a test result;

[0135] Evaluate the performance and stability of the intelligent device according to the test result.

[0136] Among them, obtaining the device information of the intelligent device to be tested and constructing a physical model according to the device information specifically includes:

[0137] Obtaining the device information of the intelligent device to be tested, and collecting the attribute data of the entity objects related to the functions of the intelligent device according to the test requirements;

[0138] Constructing a virtual physical model by using computer-aided design software according to the device information and the attribute data;

[0139] Among them, the device information includes device type, device function, communication protocol, data format, device status, and device attributes, and the attribute data includes size, weight, and material.

[0140] Among them, generating test cases according to the physical model specifically is:

[0141] Generating corresponding test cases according to the attributes, services, and events in the physical model, and the test cases cover all functional points and boundary conditions of the device.

[0142] Among them, using the test cases to test the physical model specifically includes:

[0143] Generating characteristic data by using the physical model, putting the characteristic data into the resource pool, and simulating test scenarios in the real environment, where the test scenarios include normal scenarios, abnormal scenarios, and stress scenarios;

[0144] Running the test cases to test the physical model under different test scenarios.

[0145] Among them, collecting the feedback information of the physical model during the test process and analyzing according to the feedback information to obtain the test result specifically includes:

[0146] Collecting the feedback information of the physical model during the test process of running the test cases, where the feedback information includes processing accuracy rate, device response time, abnormal handling ability, and device stability;

[0147] Real-time recording of the test log, where the test log includes timestamp, input data, output result, and resource occupancy rate, and generating a visualization curve graph;

[0148] Performing summary analysis according to the feedback information and the visualization curve graph to obtain the test result of the physical model.

[0149] Among them, evaluating the performance and stability of the intelligent device according to the test result specifically includes:

[0150] Statistically analyze the test results and extract the key index data from the test results;

[0151] Evaluate the performance and stability of the intelligent device according to the key index data.

[0152] Among them, collecting the feedback information of the physical model during the test process, analyzing according to the feedback information to obtain the test results, and then further including:

[0153] Compare the performance of the physical model in different test scenarios to obtain potential problems;

[0154] Generate an optimization plan for the physical model according to the potential problems;

[0155] Adjust the parameters of the physical model according to the optimization plan of the physical model, and re - test the physical model with the adjusted parameters using the test cases until the physical model meets the design requirements.

[0156] The present invention also provides a computer - readable storage medium, wherein the computer - readable storage medium stores an intelligent test program based on the physical model, and when the intelligent test program based on the physical model is executed by a processor, the steps of the above - mentioned intelligent test method based on the physical model are realized.

[0157] In summary, the present invention provides an intelligent test method, system, terminal and computer - readable storage medium based on the physical model. The method includes: obtaining the device information of the intelligent device to be tested, constructing a physical model according to the device information; generating test cases according to the physical model; testing the physical model using the test cases; collecting the feedback information of the physical model during the test process, analyzing according to the feedback information to obtain the test results; evaluating the performance and stability of the intelligent device according to the test results. The present invention realizes the testing of the functions, performance, stability, etc. of the intelligent device by constructing a physical model, improves the test efficiency, reduces the test cost, and provides effective test guarantee for the R & D and production enterprises of intelligent devices.

[0158] It should be noted that in this article, the terms "include", "comprise" or any other variant thereof are intended to cover non - exclusive inclusion, so that a process, method, article or terminal including a series of elements not only includes those elements but also includes other elements not expressly listed, or further includes elements inherent to such process, method, article or terminal. Without further limitation, an element defined by the statement "including one..." does not exclude the existence of another identical element in the process, method, article or terminal including that element.

[0159] Of course, those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be completed by instructing relevant hardware (such as a processor, a controller, etc.) through a computer program. The program can be stored in a computer-readable storage medium readable by a computer. When the program is executed, it can include the processes of the above method embodiments. The computer-readable storage medium can be a memory, a magnetic disk, an optical disc, etc.

[0160] It should be understood that the application of the present invention is not limited to the above examples. For those of ordinary skill in the art, improvements or transformations can be made according to the above description. All such improvements and transformations should fall within the protection scope of the appended claims of the present invention.

Claims

1. An intelligent testing method based on a physical model, characterized in that The intelligent testing method based on the physical model includes: Obtain the device information of the intelligent device to be tested, and construct a physical model according to the device information; Generate test cases according to the physical model; Use the test cases to test the physical model; Collect the feedback information of the physical model during the testing process, and analyze the feedback information to obtain the test results; Evaluate the performance and stability of the intelligent device according to the test results.

2. The intelligent testing method based on the object model according to claim 1, wherein The obtaining of the device information of the intelligent device to be tested and the construction of the physical model according to the device information specifically include: Obtain the device information of the intelligent device to be tested, and collect the attribute data of the entity objects related to the functions of the intelligent device according to the test requirements; According to the device information and the attribute data, use computer-aided design software to construct a virtual physical model; Among them, the device information includes device type, device function, communication protocol, data format, device status and device attributes, and the attribute data includes size, weight and material.

3. The intelligent testing method based on the object model according to claim 1, wherein The generating of test cases according to the physical model is specifically: Generate corresponding test cases according to the attributes, services and events in the physical model, and the test cases cover all function points and boundary conditions of the device.

4. The intelligent testing method based on the object model according to claim 1, wherein The using of the test cases to test the physical model specifically includes: Use the physical model to generate characteristic data, put the characteristic data into the resource pool, and simulate the test scenarios in the real environment, and the test scenarios include normal scenarios, abnormal scenarios and stress scenarios; Run the test cases and test the physical model under different test scenarios.

5. The intelligent testing method based on the object model according to claim 1, wherein The collecting of the feedback information of the physical model during the testing process and the analyzing of the feedback information to obtain the test results specifically include: Collect the feedback information of the physical model during the testing process of running the test cases, and the feedback information includes processing accuracy rate, device response time, abnormal handling ability and device stability; Record the test logs in real time, and the test logs include timestamps, input data, output results and resource occupancy rates, and generate a visual curve graph; Perform summary analysis according to the feedback information and the visual curve graph to obtain the test results of the physical model.

6. The intelligent testing method based on the object model according to claim 1, characterized in that, The evaluating of the performance and stability of the intelligent device according to the test results specifically includes: Statistically analyze the test results and extract the key index data in the test results; Evaluate the performance and stability of the intelligent device according to the key index data.

7. The intelligent testing method based on the physical model according to claim 1, characterized in that After the collecting of the feedback information of the physical model during the testing process and the analyzing of the feedback information to obtain the test results, it further includes: Compare the performance of the physical model under different test scenarios to obtain potential problems; Generate an optimization plan for the physical model according to the potential problems; Adjust the physical model parameters according to the optimization plan of the physical model, and use the test cases to retest the physical model with the adjusted parameters until the physical model meets the design requirements.

8. An intelligent testing system based on a physical model, characterized in that The intelligent testing system based on the physical model includes: A physical model construction module, which is used to obtain the device information of the intelligent device to be tested and construct a physical model according to the device information; A test case generation module for generating test cases according to the physical model; A physical model test module for testing the physical model using the test cases; A test analysis module for collecting feedback information during the testing of the physical model and analyzing the feedback information to obtain test results; A performance evaluation module for evaluating the performance and stability of the intelligent device according to the test results.

9. A terminal, characterized in that, The terminal includes: a memory, a processor, and an intelligent testing program based on the physical model stored on the memory and executable on the processor. When the intelligent testing program based on the physical model is executed by the processor, the steps of the intelligent testing method based on the physical model according to any one of claims 1-7 are implemented.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores an intelligent testing program based on the physical model. When the intelligent testing program based on the physical model is executed by the processor, the steps of the intelligent testing method based on the physical model according to any one of claims 1-7 are implemented.

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