ARM-based test method, apparatus and device, and storage medium

Abstract

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.

Description

Technical Field

[0001] This application relates to the field of computer technology, and in particular to a test method, apparatus, device and storage medium based on ARM. Background Technology

[0002] Currently, with the increasing level of industrial automation, traditional manual testing methods can no longer meet the demands for fast, accurate, and efficient testing. In industrial production, especially in fields such as electronic products and mechanical components, the efficiency and accuracy of testing systems are directly related to the quality control and output capacity of the production line.

[0003] Low-power, high-performance ARM-based test systems are increasingly becoming a research focus in the industrial sector, offering more efficient, economical, and flexible solutions. Traditional test systems suffer from high labor costs and require significant manual intervention, particularly in data entry, troubleshooting, and test setup. This not only increases labor costs but also makes them susceptible to factors such as staff turnover and insufficient training, reducing system stability and efficiency. Furthermore, traditional test systems employ limited algorithms, resulting in unsatisfactory test performance when using ARM-based embedded platforms.

[0004] The above content is only used to help understand the technical solution of this application and does not represent an admission that the above content is prior art. Summary of the Invention

[0005] The main objective of this invention is to provide an ARM-based testing method, which aims to solve the technical problem of poor testing results when testing based on the ARM embedded platform in the prior art.

[0006] To achieve the above objectives, this application provides an ARM-based testing method, which is applied to an ARM-based testing system. The ARM-based testing system includes a test acquisition module, an artificial intelligence module, a test algorithm module, and a user interface module. The method includes: Obtain the test requirement command input by the user, parse the test requirement command, and obtain the user test requirement information; Based on the user testing requirement information, extract the testing requirement type; Based on the test requirement type, obtain the first test dataset corresponding to the test requirement type; The test data is analyzed based on a preset artificial intelligence module, and the first test data is updated based on the analysis results to obtain a second test dataset. The second test dataset is tested, the test results are obtained, and the test results are displayed through a preset user interface module.

[0007] In one possible implementation of this application, the test requirement type includes a fault detection type, a target detection type, and a surface defect detection type. The step of obtaining a first test dataset corresponding to the test requirement type includes: If the test requirement type is fault detection, then temperature data, vibration data, pressure data, and current data will be collected. If the test requirement type is target detection, then the image of the target to be detected is collected; If the test requirement type is product surface defect detection, an image of the surface of the product to be inspected is collected.

[0008] In one possible implementation of this application, the step of testing the second test dataset and obtaining test results includes: The second test dataset is divided proportionally into a third test dataset and a fourth test dataset; The third test dataset is tested based on a preset test algorithm module to obtain preliminary test results; The preliminary test results are analyzed, and the fourth test dataset is updated based on the analysis results to obtain the updated fourth test dataset; Test results were obtained by conducting tests based on the updated fourth test set.

[0009] In one possible implementation of this application, if the test requirement type is product surface defect detection, after the step of testing the second test dataset, obtaining the test results, and displaying the test results through a preset user interface module, the method includes: If the test requirement type is product surface defect detection, the product surface defect detection results are classified according to the degree of defect to obtain level 1 defect, level 2 defect and level 3 defect; The causes of the defects in the first-level products, the second-level products, and the third-level products are investigated respectively to obtain the first cause, the second cause, and the third cause in sequence. The first reason, the second reason, and the third reason are pushed to the user so that the user can improve the product.

[0010] In one possible implementation of this application, the ARM-based test system further includes a test control module. Multiple test acquisition modules are connected to a preset server. After the step of obtaining the first test dataset corresponding to the test requirement type, the system includes: Add data type, data creation time and data source terminal identifier to the first test dataset to obtain the processed first test dataset; The processed first test dataset is uploaded to the server; Upon receiving a call instruction for the processed first test dataset, the system retrieves the first test dataset of the corresponding data type from the server based on the data type indicated by the call instruction, retrieves the first test dataset of the corresponding data creation time from the server based on the data creation time indicated by the call instruction, and retrieves the first test dataset of the corresponding data source terminal identifier from the server based on the data source terminal identifier indicated by the call instruction.

[0011] In one possible implementation of this application, the step of testing the second test dataset and obtaining test results includes: Generate a suite test package from the second test dataset and write the suite test package to the target storage device; Determine whether the ARM server under test meets the certification test requirements; If the ARM server under test meets the certification test requirements, then connect the target storage device to the ARM server under test and start the ARM server under test; Retrieve the certification test script from the suite test package according to the certification test items; Restart the ARM server under test, load the target storage device to start the ARM server under test from the target storage device, and perform server authentication test based on the authentication test script.

[0012] In one possible implementation of this application, the step of determining whether the ARM server under test meets the certification test requirements includes: Determine whether the hardware configuration of the ARM server under test meets the certification test requirements; If the hardware configuration meets the certification test requirements, then the ARM server under test is determined to meet the certification test requirements. If the hardware configuration does not meet the certification test requirements, then the ARM server under test is determined to not meet the certification test requirements.

[0013] Furthermore, to achieve the above objectives, this application also provides an ARM-based testing device, which includes: The first acquisition module is used to acquire the test requirement instruction input by the user, parse the test requirement instruction, and obtain the user test requirement information. The extraction module is used to extract the test requirement type based on the user test requirement information; The second acquisition module is used to acquire a first test dataset corresponding to the test requirement type based on the test requirement type. An analysis module is used to analyze the test data and update the first test data based on the analysis results to obtain a second test dataset; The testing module is used to test the second test dataset, obtain test results, and display the test results through a preset user interface.

[0014] In addition, to achieve the above objectives, this application also provides a system automatic installation device, which is a physical node device. The system automatic installation device includes: a memory, a processor, and a system automatic installation program stored on the memory and capable of running on the processor. The processor executes the system automatic installation program to implement the steps of an ARM-based testing method.

[0015] In addition, to achieve the above objectives, this application also provides a storage medium storing a program that implements an ARM-based testing method, wherein the system automatically installs the program and executes the steps of the ARM-based testing method described above when the processor is executed.

[0016] This application provides a testing method, apparatus, device, and storage medium based on ARM. Compared with the technical problem of poor testing results when testing based on ARM embedded platforms in the prior art, this application obtains user-inputted test requirement instructions, parses the test requirement instructions to obtain user test requirement information; extracts test requirement types based on the user test requirement information; obtains a first test dataset corresponding to the test requirement type based on the test requirement type; analyzes the test data based on a preset artificial intelligence module, and updates the first test data based on the analysis results to obtain a second test dataset; tests the second test dataset to obtain test results, and displays the test results through a preset user interface module. In this application, the corresponding first test dataset is accurately obtained for the type of test requirement, and the artificial intelligence module further updates the first test dataset, resulting in more accurate testing and solving the technical problem of poor testing results when testing based on ARM embedded platforms. Attached Figure Description

[0017] Figure 1 This is a flowchart illustrating an embodiment of the ARM-based testing method of this application; Figure 2 This is a schematic diagram of the ARM-based testing device in the embodiment of the ARM-based testing method of this application; Figure 3 This is a schematic diagram of the device structure of the hardware operating environment involved in the ARM-based testing method embodiment of this application. Detailed Implementation

[0018] To make the above-mentioned objects, features, and advantages of the present invention more apparent and understandable, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0019] Example 1 This application provides an ARM-based testing method. In the first embodiment of the ARM-based testing method of this application, reference is made to... Figure 1 The ARM-based testing method is applied to an ARM-based testing system, which includes a test acquisition module, an artificial intelligence module, a test algorithm module, and a user interface module.

[0020] Currently, with the increasing level of industrial automation, traditional manual testing methods can no longer meet the demands for rapid, accurate, and efficient testing. In industrial production, especially in fields such as electronic products and mechanical components, the efficiency and accuracy of testing systems directly affect the quality control and output capacity of the production line. Because traditional testing systems use simplistic algorithms and lack integration of artificial intelligence technology, the following problems arise: Traditional testing solutions are inflexible, inaccurate, inefficient, and have limited scalability. Traditional testing solutions do not integrate the latest artificial intelligence technologies, are technically inefficient, and their overly mechanical testing methods cannot meet the complex testing needs of the modern era. Traditional testing systems lack intelligent adaptive capabilities and cannot make dynamic adjustments based on real-time data. Furthermore, they lack the ability to predict potential future problems, meaning that the testing process may be inefficient or even fail to detect potential faults or quality issues in advance. Traditional testing systems have high labor costs, requiring significant manual intervention, especially in data entry, troubleshooting, and test setup. This not only increases labor costs but is also susceptible to factors such as staff turnover and insufficient training, reducing the system's stability and efficiency. Traditional testing systems lack sufficient data analysis capabilities, relying heavily on manual processing and analysis, which is slow and unable to efficiently extract valuable information from large datasets. This makes problem diagnosis and product optimization cumbersome and hinders the rapid development of solutions. Consequently, existing technologies suffer from poor testing performance when using ARM (Advanced RISC Machines) embedded platforms.

[0021] The method includes steps S110-S150: Step S110: Obtain the test requirement instruction input by the user, parse the test requirement instruction, and obtain the user test requirement information; Test request instructions are test tasks submitted by users through the interface. Users select specific test items, test objects, and test start times, and save after submission.

[0022] When an ARM-based testing system detects a test requirement instruction, it obtains the test requirement instruction input by the user, and then parses the test requirement instruction to obtain user test requirement information such as the test project, test object, and test time submitted by the user.

[0023] Step S120: Extract the test requirement type based on the user test requirement information; Test requirement types include fault detection, target detection, and surface defect detection.

[0024] The ARM-based testing system extracts the test requirement type based on the user's test requirement information.

[0025] Step S130: Based on the test requirement type, obtain the first test dataset corresponding to the test requirement type; The ARM-based testing system selects a preset data acquisition module based on the test requirement type. The acquisition module is closely related to the test requirement type. For example, if the test requirement type is fault detection, and temperature data is required, then the preset acquisition module will be the temperature acquisition module.

[0026] Based on the test requirement type, the first test dataset corresponding to the test requirement type is obtained through the corresponding test acquisition module.

[0027] The ARM-based testing system also includes a test control module. Multiple test acquisition modules are connected to a preset server. Following step S130, steps A1-A3 are included: Step A1: Add data type, data creation time, and data source terminal identifier to the first test dataset to obtain the processed first test dataset; In an ARM-based testing system, the test control module controls the entire testing process. The module adds data type, creation time, and source terminal identifier to the first test dataset, resulting in a processed first test dataset. In addition to these additions, the data creator's name can also be added to facilitate tracing the cause of a fault back to a specific individual.

[0028] Step A2: Upload the processed first test dataset to the server; After processing operations such as adding data types, the first test dataset is uploaded to the preset server.

[0029] Step A3: Upon receiving a call instruction for the processed first test dataset, obtain the first test dataset of the corresponding data type from the server based on the data type indicated by the call instruction, obtain the first test dataset of the corresponding data creation time from the server based on the data creation time indicated by the call instruction, and obtain the first test dataset of the corresponding data source terminal identifier from the server based on the data source terminal identifier indicated by the call instruction.

[0030] If a user needs to access the first test dataset, they can issue a call command on the interface. The user can then specifically access dedicated data, such as data within a certain data creation time range, or data from the same data source terminal.

[0031] If the user sends data of a certain type, the ARM-based test system will retrieve the first test dataset of that data type from the server based on the data type indicated by the call instruction.

[0032] If the user submits data whose creation time is within a certain month, the ARM-based test system will retrieve the first test dataset with the corresponding data creation time from the server based on the month indicated by the call instruction.

[0033] If the user issues a call to a certain data source terminal identifier, the ARM-based test system obtains the first test dataset corresponding to the data source terminal identifier from the server based on the data source terminal identifier indicated by the call instruction.

[0034] The test requirement types include fault detection type, target detection type, and surface defect detection type. Step S130 includes steps S1301-S1303: Step S1301: If the test requirement type is fault detection type, then collect temperature data, vibration data, pressure data and current data. ARM-based testing systems can perform tests including fault detection and target detection.

[0035] If the test requirement type is fault detection, then temperature data is collected through a preset temperature acquisition module, vibration data is collected through a preset vibration acquisition module, pressure data is collected through a preset pressure acquisition module, and current data is collected through a preset current acquisition module.

[0036] Step S1302: If the test requirement type is target detection type, then collect the image of the target to be detected; If the test requirement type is target detection, then the image of the target to be tested is acquired by a preset image acquisition module. There can be more than one image acquisition module. Images acquired by different image acquisition modules can avoid personalized data and improve test accuracy.

[0037] Step S1303: If the test requirement type is product surface defect detection, then collect an image of the surface of the product to be inspected.

[0038] In addition to the image acquisition module required for target detection, the image acquisition module can also be used for product surface defect detection to identify defects on the product surface based on the acquired images.

[0039] If the test requirement type is product surface defect detection, then the image of the surface of the product to be inspected is acquired through a preset image acquisition module.

[0040] Step S140: Analyze the test data based on the preset artificial intelligence module, and update the first test data based on the analysis results to obtain the second test dataset; The ARM-based testing system also includes an artificial intelligence module. By analyzing the test data using the artificial intelligence module, data defects in the first test dataset can be found.

[0041] The AI ​​module, through data analysis and learning, can reduce human intervention and improve testing accuracy. Through deep learning and pattern recognition, the AI ​​module can accurately identify potential problems in products, avoiding human error and improving testing precision.

[0042] The artificial intelligence module can monitor and adjust the testing process in real time, automatically optimizing it according to different product or environmental conditions. This avoids bottlenecks caused by traditional fixed processes, ensuring that each product receives optimal testing and adaptively adjusting the process.

[0043] The artificial intelligence module can automatically identify anomalies or faults during the testing process, and perform diagnosis and early warning, quickly discovering problems and reducing the time and cost of manual inspection.

[0044] The artificial intelligence module can intelligently schedule testing resources, such as equipment and personnel, to improve resource utilization efficiency, ensure unimpeded testing processes, enhance overall production efficiency, and optimize resource allocation.

[0045] The artificial intelligence module can predict potential equipment failures by analyzing historical data, perform maintenance in advance, avoid sudden downtime, extend equipment lifespan, and provide predictive maintenance.

[0046] Artificial intelligence modules can automate processes such as data analysis and troubleshooting, significantly reducing manual operations and lowering related costs.

[0047] By analyzing product test data, the artificial intelligence module can identify weaknesses in quality control, provide improvement suggestions, ensure that product quality always meets standards, and improve product quality.

[0048] Traditional testing algorithms are typically designed for specific standard test items, resulting in poor applicability and difficulty in adjusting to product characteristics. Adaptive testing algorithms, incorporating image processing and analysis algorithms, possess dynamic adjustment capabilities, automatically selecting test items and parameters based on different testing needs and product characteristics. Furthermore, additional image processing and deep learning algorithms are added. To improve testing accuracy and flexibility, the testing algorithm is allowed to adaptively adjust to different products and requirements, ensuring more accurate and efficient test results, reducing manual intervention, and significantly improving testing accuracy through the addition of multiple algorithms.

[0049] The first test data is updated based on the analysis results to obtain the second test dataset. The test data is analyzed intelligently and the test strategy is automatically adjusted. It can learn and predict based on historical data and real-time test conditions, thereby optimizing the test process, automatically adjusting test parameters, and predicting product quality and potential problems based on test results.

[0050] Step S150: Test the second test dataset, obtain the test results, and display the test results through a preset user interface module.

[0051] The first test data is updated to obtain the second test dataset, and the second test dataset is tested to obtain the test results.

[0052] The test results are displayed to the user through the user interface module.

[0053] Step S150 includes steps S1501-S1504: Step S1501: Divide the second test dataset into a third test dataset and a fourth test dataset according to the proportions. Furthermore, by filtering the first test dataset to obtain a second test dataset that truly matches the testing environment, the testing effect can be improved.

[0054] In this embodiment, the second test dataset can be further divided, and a small portion of the data can be used for pre-test training to obtain preliminary test results. These preliminary results can then be analyzed. Using a small portion of the test data to summarize the performance of all the test data allows for early prediction of potential problems, enabling proactive solutions and further improving test effectiveness.

[0055] Specifically, the second test dataset is first divided proportionally into the third and fourth test datasets. Here, a 2:8 ratio can be used to divide them, resulting in the third and fourth test datasets respectively.

[0056] Step S1502: Test the third test dataset based on the preset test algorithm module to obtain preliminary test results; We first conducted a small-scale test using the third test dataset to obtain preliminary test results.

[0057] Step S1503: Analyze the preliminary test results and update the fourth test dataset based on the analysis results to obtain the updated fourth test dataset; Then, based on the preliminary test results described in the artificial intelligence module, analysis is performed to identify problems in the test and to learn from them.

[0058] The preliminary test results from the artificial intelligence module are analyzed, and the fourth test dataset is updated based on the analysis results to obtain the updated fourth test dataset. Problems are identified from the analysis results, and the remaining fourth test datasets are updated accordingly, thus avoiding these problems in advance.

[0059] Step S1504: Perform tests based on the updated fourth test set to obtain test results.

[0060] Finally, the test results were obtained by conducting tests based on the updated fourth test set.

[0061] Therefore, by processing the test data from the initial first test dataset to the updated fourth test dataset, we can improve the test results.

[0062] Step S150 further includes steps S1505-S1508: Step S1505: Generate a kit test package from the second test dataset and write the kit test package to the target storage device; When testing the second test dataset based on the preset test algorithm module, a suite test package is generated from the second test dataset, and the suite test package is written to the target storage device.

[0063] Step S1506: Determine whether the ARM server under test meets the certification test requirements; An ARM-based testing system determines whether an ARM server under test meets certification testing requirements.

[0064] Step S1506 includes steps B1-B3: Step B1: Determine whether the hardware configuration of the ARM server under test meets the certification test requirements; Whether the ARM server under test meets the certification test requirements depends mainly on the hardware configuration.

[0065] Step B2: If the hardware configuration meets the certification test requirements, then it is determined that the ARM server under test meets the certification test requirements. If the hardware configuration meets the certification test requirements, then the ARM server under test is determined to meet the certification test requirements. If the hardware configuration does not meet the certification test requirements, then the ARM server under test is determined to not meet the certification test requirements.

[0066] Step B3: If the hardware configuration does not meet the certification test requirements, then it is determined that the ARM server under test does not meet the certification test requirements.

[0067] Step S1507: If the ARM server under test meets the certification test requirements, then connect the target storage device to the ARM server under test and start the ARM server under test. If the ARM server under test meets the certification test requirements, then connect the target storage device to the ARM server under test and start the ARM server under test.

[0068] Step S1508: Obtain the certification test script from the kit test package according to the certification test item; The certification test script is obtained from the suite test package according to the certification test items.

[0069] Restart the ARM server under test, load the target storage device to start the ARM server under test from the target storage device, and perform server authentication test based on the authentication test script.

[0070] If the test requirement type is product surface defect detection, after step S150, steps S160-S180 are included: Step S160: If the test requirement type is product surface defect detection, the product surface defect detection results are classified according to the degree of defect based on the artificial intelligence module to obtain first-level defects, second-level defects and third-level defects. If the test requirement is for product surface defect detection, the degree of defect can be graded as follows: Level 1 defect, Level 2 defect, and Level 3 defect. The artificial intelligence module then categorizes the product surface defect detection results according to their degree of defect.

[0071] Step S170: The causes of the first-level defective products, the second-level defective products, and the third-level defective products are investigated respectively to obtain the first cause, the second cause, and the third cause in sequence. Based on the aforementioned artificial intelligence module, the causes of defects are identified, finding the first cause of products with level 1 defects, the second cause of products with level 2 defects, and the third cause of products with level 3 defects.

[0072] Step S180: Push the first reason, the second reason, and the third reason to the user so that the user can improve the product.

[0073] The first reason, the second reason, and the third reason are pushed to the user so that the user can improve the product, and the user can change their decision based on the reasons.

[0074] This application provides a testing method, apparatus, device, and storage medium based on ARM. Compared with the technical problem of poor testing results when testing based on ARM embedded platforms in the prior art, this application obtains user-inputted test requirement instructions, parses the test requirement instructions to obtain user test requirement information; extracts test requirement types based on the user test requirement information; obtains a first test dataset corresponding to the test requirement type based on the test requirement type; analyzes the test data based on a preset artificial intelligence module, and updates the first test data based on the analysis results to obtain a second test dataset; tests the second test dataset to obtain test results, and displays the test results through a preset user interface module. In this application, the corresponding first test dataset is accurately obtained for the type of test requirement, and the artificial intelligence module further updates the first test dataset, resulting in more accurate testing and solving the technical problem of poor testing results when testing based on ARM embedded platforms.

[0075] Example 2 Furthermore, based on all the above embodiments, another embodiment of this application is provided, in which, as... Figure 2 This invention provides an ARM-based testing device, the device comprising: The first acquisition module is used to acquire the test requirement instruction input by the user, parse the test requirement instruction, and obtain the user test requirement information. The extraction module is used to extract the test requirement type based on the user test requirement information; The second acquisition module is used to acquire a first test dataset corresponding to the test requirement type based on the test requirement type. An analysis module is used to analyze the test data and update the first test data based on the analysis results to obtain a second test dataset; The testing module is used to test the second test dataset, obtain test results, and display the test results through a preset user interface.

[0076] In one possible implementation of this application, the test requirement type includes a fault detection type, a target detection type, and a surface defect detection type. The step of obtaining a first test dataset corresponding to the test requirement type includes: The first acquisition module is used to acquire temperature data, vibration data, pressure data, and current data if the test requirement type is a fault detection type. The second acquisition module is used to acquire an image of the target to be inspected if the test requirement type is a target detection type. The third acquisition module is used to acquire images of the surface of the product to be inspected if the test requirement type is product surface defect detection.

[0077] In one possible embodiment of this application, the apparatus for the step of testing the second test dataset and obtaining test results includes: The partitioning module is used to divide the second test dataset into a third test dataset and a fourth test dataset according to a certain ratio; The first testing module is used to test the third test dataset based on a preset testing algorithm module to obtain preliminary test results; An update module is used to analyze the preliminary test results and update the fourth test dataset based on the analysis results to obtain the updated fourth test dataset; The second testing module is used to perform tests based on the updated fourth test set to obtain test results.

[0078] In one possible implementation of this application, if the test requirement type is product surface defect detection, after the step of testing the second test dataset, obtaining test results, and displaying the test results through a preset user interface module, the device includes: The classification module is used to classify the product surface defect detection results according to the degree of defect if the test requirement type is product surface defect detection, resulting in first-level defects, second-level defects and third-level defects. The cause-finding module is used to find the causes of the products with the first-level defects, the products with the second-level defects, and the products with the third-level defects, and obtain the first cause, the second cause, and the third cause in sequence. The push module is used to push the first reason, the second reason, and the third reason to the user so that the user can improve the product.

[0079] In one possible implementation of this application, the ARM-based test system further includes a test control module, and there are multiple test acquisition modules, each of which is connected to a preset server. After the step of obtaining a first test dataset corresponding to the test requirement type, the device includes: The control module adds data type, data creation time, and data source terminal identifier to the first test dataset to obtain the processed first test dataset. An upload module is used to upload the processed first test dataset to the server; The second acquisition module is configured to, upon receiving a call instruction for the processed first test dataset, acquire the first test dataset of the corresponding data type from the server based on the data type indicated by the call instruction, acquire the first test dataset of the corresponding data creation time from the server based on the data creation time indicated by the call instruction, and acquire the first test dataset of the corresponding data source terminal identifier from the server based on the data source terminal identifier indicated by the call instruction.

[0080] In one possible embodiment of this application, the apparatus for the step of testing the second test dataset and obtaining test results includes: A test package generation module is used to generate a suite test package from the second test dataset and write the suite test package to the target storage device; The first judgment module is used to determine whether the ARM server under test meets the certification test requirements. The startup module is used to connect the target storage device to the ARM server under test and start the ARM server under test if the ARM server under test meets the certification test requirements. The third acquisition module is used to acquire the authentication test script from the suite test package according to the authentication test item; The restart module is used to restart the ARM server under test, load the target storage device to start the ARM server under test from the target storage device, and perform server authentication test based on the authentication test script.

[0081] In one possible implementation of this application, the apparatus for determining whether the ARM server under test meets the certification test requirements includes: The second judgment module is used to determine whether the hardware configuration of the ARM server under test meets the certification test requirements. The first determining module is used to determine that the ARM server under test meets the certification test requirements if the hardware configuration meets the certification test requirements. The second determining module is used to determine that the ARM server under test does not meet the certification test requirements if the hardware configuration does not meet the certification test requirements.

[0082] The specific implementation of the ARM-based testing device in this application is basically the same as the embodiments of the ARM-based testing method described above, and will not be repeated here.

[0083] Example 3 Furthermore, based on all the above embodiments, another embodiment of this application is provided. In this embodiment, a system automatic installation device is provided. The system automatic installation device is a physical node device. The system automatic installation device includes: a memory, a processor, and a program stored in the memory for implementing an ARM-based testing method. The memory is used to store the program for implementing the ARM-based testing method; the processor is used to execute the program for implementing the ARM-based testing method to implement the steps of the ARM-based testing method in the above embodiments.

[0084] Reference Figure 3 , Figure 3 This is a schematic diagram of the device structure of the hardware operating environment involved in the embodiments of this application.

[0085] like Figure 3 As shown, the system's automatic installation device may include: a processor 1001, such as a CPU, a memory 1005, and a communication bus 1002. The communication bus 1002 is used to establish communication between the processor 1001 and the memory 1005. The memory 1005 may be a high-speed RAM or a stable, non-volatile memory, such as a disk drive. Optionally, the memory 1005 may also be a storage device independent of the aforementioned processor 1001.

[0086] In one possible implementation of this application, the automatic installation device of the system may further include a network interface, audio circuitry, display, connecting cable, sensor, input module, etc. The network interface may optionally include a standard wired interface or a wireless interface (such as a Wi-Fi interface or a Bluetooth interface). The input module may optionally include a keyboard, a system soft keyboard, voice input, wireless receiver input, etc.

[0087] Those skilled in the art will understand that the structure of the system automatic installation equipment does not constitute a limitation on the system automatic installation equipment, and may include more or fewer components than shown in the figure, or combine certain components, or have different component arrangements.

[0088] A memory, as a deterministic storage medium, may include an operating system, an information exchange module, and a system auto-installation program. The operating system is a program that manages and controls the system's automatic installation of device hardware and software resources, supporting the operation of the system auto-installation program and other software and / or programs. The information exchange module is used to enable communication between various components within the memory, as well as communication with other hardware and software in the system.

[0089] In the system automatic installation device, the processor is used to execute the system automatic installation program stored in the memory to implement the above-mentioned system automatic installation steps.

[0090] The specific implementation method of the automatic installation device in this application is basically the same as the embodiments of the above-mentioned ARM-based testing method, and will not be repeated here.

[0091] Example 4 This application provides a storage medium that stores one or more programs, which can be executed by one or more processors to implement the steps of the ARM-based testing method described above.

[0092] The specific implementation of the storage medium in this application is basically the same as the embodiments of the above-described ARM-based testing method, and will not be repeated here.

[0093] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or system. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or system that includes that element.

[0094] The sequence numbers of the embodiments in this application are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0095] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM or RAM, magnetic disk, optical disk) as described above, and includes several instructions to cause a terminal device (which may be a mobile phone, computer, server, air conditioner, or network device, etc.) to execute the methods of the various embodiments of this application.

[0096] The above are merely preferred embodiments of this application and do not limit the patent scope of this application. Any equivalent structural or procedural transformations made using the content of this application's specification and drawings, or direct or indirect applications in other related technical fields, are similarly included within the patent protection scope of this application.

Claims

1. An ARM-based testing method, characterized in that, The method comprises: obtaining a test requirement instruction input by a user, parsing the test requirement instruction to obtain user test requirement information; based on the user test requirement information, extracting a test requirement type; based on the test requirement type, obtaining a first test data set corresponding to the test requirement type; analyzing the test data and updating the first test data based on the analysis result to obtain a second test data set; testing the second test data set to obtain a test result and displaying the test result through a preset user interface.

2. The ARM-based testing method according to claim 1, characterized in that, The test requirement type includes fault detection type, target detection type, and surface defect detection type. The step of obtaining a first test data set corresponding to the test requirement type based on the test requirement type comprises: if the test requirement type is fault detection type, collect temperature data, vibration data, pressure data, and current data; if the test requirement type is target detection type, collect pictures of the target to be detected; if the test requirement type is product surface defect detection, collect pictures of the surface of the product to be detected.

3. The ARM-based testing method according to claim 1, characterized in that, The step of testing the second test data set to obtain a test result comprises: dividing the second test data set into a third test data set and a fourth test data set according to a proportion; testing the third test data set based on a preset test algorithm module to obtain a preliminary test result; analyzing the preliminary test result and updating the fourth test data set based on the analysis result to obtain an updated fourth test data set; testing the updated fourth test set to obtain a test result.

4. The ARM-based testing method according to claim 2, characterized in that, If the test requirement type is product surface defect detection, the step of testing the second test data set to obtain a test result and displaying the test result through a preset user interface module comprises: if the test requirement type is product surface defect detection, classify the product surface defect detection result according to defect degree to obtain first-level defects, second-level defects, and third-level defects; find the causes of the first-level defect products, the second-level defect products, and the third-level defect products respectively to obtain first reasons, second reasons, and third reasons in turn; push the first reasons, the second reasons, and the third reasons to the user for the user to improve the product.

5. The ARM-based testing method according to claim 1, characterized in that, After the step of obtaining a first test data set corresponding to the test requirement type based on the test requirement type, the method comprises: adding data type, data creation time, and data source terminal identifier to the first test data set to obtain a processed first test data set; uploading the processed first test data set to the server; When receiving the calling instruction of the processed first test data set, the first test data set of the corresponding data type is obtained from the server based on the data type indicated by the calling instruction, the first test data set of the corresponding data creation time is obtained from the server based on the data creation time indicated by the calling instruction, and the first test data set of the corresponding data source terminal identifier is obtained from the server based on the data source terminal identifier indicated by the calling instruction.

6. The ARM-based testing method according to claim 1, characterized in that, The step of testing the second test data set to obtain a test result comprises: generating a suite test package from the second test data set, and writing the suite test package into a target storage device; determining whether the ARM server to be tested meets the authentication test requirement; if the ARM server to be tested meets the authentication test requirement, connecting the target storage device to the ARM server to be tested, and starting the ARM server to be tested; obtaining an authentication test script from the suite test package according to the authentication test item; restarting the ARM server to be tested, loading the target storage device to start the ARM server to be tested from the target storage device, and performing server authentication test based on the authentication test script.

7. The ARM-based testing method according to claim 6, characterized in that, The step of determining whether the ARM server to be tested meets the authentication test requirement comprises: determining whether the hardware configuration of the ARM server to be tested meets the authentication test requirement; if the hardware configuration meets the authentication test requirement, determining that the ARM server to be tested meets the authentication test requirement; if the hardware configuration does not meet the authentication test requirement, determining that the ARM server to be tested does not meet the authentication test requirement.

8. An ARM-based testing device, characterized by, The ARM-based test device comprises: a first obtaining module configured to obtain a test requirement instruction input by a user, analyze the test requirement instruction, and obtain user test requirement information; an extracting module configured to extract a test requirement type based on the user test requirement information; a second obtaining module configured to obtain a first test data set corresponding to the test requirement type based on the test requirement type; an analyzing module configured to analyze the test data, and update the first test data to obtain a second test data set based on an analysis result; a testing module configured to test the second test data set, obtain a test result, and display the test result through a preset user interface.

9. An ARM-based test device, characterized by A system automatic installation program stored in the memory and executable on the processor, and the processor executes the system automatic installation program to implement the steps of the ARM-based test method according to any one of claims 1 to 7.

10. A storage medium for ARM-based testing, characterized in that A storage medium stores a program for implementing the ARM-based test method, and the program for implementing the ARM-based test method is executed by a processor to implement the steps of the ARM-based test method according to any one of claims 1 to 7.

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