Dynamic intelligent testing method, system, computer device and storage medium

Abstract

The present invention provides a dynamic intelligent testing method, which includes: when performing a project test on a target to be tested, calling a data distribution model of the project; obtaining a test range corresponding to the project based on the data distribution model; testing the target to be tested according to the test range to obtain a test value when the target to be tested is at a minimum power consumption value; and updating the data distribution model and test range corresponding to the project according to the test value. The present invention also provides a dynamic intelligent testing system, a computer device, and a storage medium. The present invention can improve testing efficiency.

Description

Technical Field

[0001] The present invention relates to the field of testing technology, and in particular to a dynamic intelligent testing method, a computer device and a storage medium. Background Art

[0002] In order to reduce system power consumption during the design of new products, more projects will be added to the test station of the target to be tested (such as the motherboard). Each project requires the target to be tested to run at different frequencies and voltages and currents under different loads, so as to find a minimum power consumption value. Then write this minimum power consumption value into the machine register. When the operating system runs in different states, the minimum power consumption value can be called to set the current and voltage supply to achieve the purpose of saving battery energy to the maximum extent. However, when obtaining this minimum power consumption value, it is necessary to step down from the standard voltage and current values ​​little by little until it drops to the point where the target to be tested issues a prompt due to undervoltage or insufficient energy, and then find the critical value, that is, the minimum power consumption value. The whole process takes a long time, and due to performance differences, the test time will be extended, which seriously affects the test capacity and increases equipment and labor costs for mass production testing. Summary of the invention

[0003] In view of the above, it is necessary to provide a dynamic intelligent testing method, system, computer device and storage medium to improve testing efficiency.

[0004] The dynamic intelligent testing method includes: when performing a project test on a target to be tested, calling a data distribution model of the project; obtaining a test range corresponding to the project based on the data distribution model; testing the target to be tested according to the test range to obtain a test value when the target to be tested is at a minimum power consumption value; and updating the data distribution model and test range corresponding to the project according to the test value.

[0005] The dynamic intelligent testing system includes: a calling module, which is used to call the data distribution model of the project when performing project testing on the target to be tested; an acquisition module, which is used to obtain the test range corresponding to the project based on the data distribution model; a testing module, which is used to test the target to be tested according to the test range to obtain the test value when the target to be tested is at the minimum power consumption value; and an updating module, which is used to update the data distribution model and test range corresponding to the project according to the test value.

[0006] The computer-readable storage medium stores at least one instruction, and when the at least one instruction is executed by a processor, the dynamic intelligent testing method is implemented.

[0007] The computer device includes a memory and at least one processor. The memory stores at least one instruction. When the at least one instruction is executed by the at least one processor, the dynamic intelligent testing method is implemented.

[0008] Compared with the prior art, the dynamic intelligent testing method, system, computer device and storage medium can update the test scope corresponding to the project and improve the testing efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0009] Figure 1 It is a structural diagram of a computer device according to a preferred embodiment of the present invention.

[0010] Figure 2 It is a functional module diagram of a dynamic intelligent testing system of a preferred embodiment of the present invention.

[0011] Figure 3 It is a flow chart of the dynamic intelligent testing method of the preferred embodiment of the present invention.

[0012] Main component symbols

[0013]

[0014]

[0015] The following specific implementation manner will further illustrate the present invention in conjunction with the above-mentioned drawings. DETAILED DESCRIPTION

[0016] In order to more clearly understand the above-mentioned purpose, features and advantages of the present invention, the present invention is described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be noted that the embodiments of the present invention and the features in the embodiments can be combined with each other without conflict.

[0017] In the following description, many specific details are set forth to facilitate a full understanding of the present invention. The embodiments described are only a part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0018] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art of the present invention. The terms used in the specification of the present invention herein are only for the purpose of describing specific embodiments and are not intended to limit the present invention.

[0019] See also Figure 1 , which is an architectural diagram of a computer device provided in a preferred embodiment of the present invention.

[0020] In this embodiment, the computer device 1 includes a memory 11 and at least one processor 12 which are electrically connected to each other.

[0021] Those skilled in the art should understand that Figure 1 The structure of the computer device 1 shown does not constitute a limitation of the embodiment of the present invention. The computer device 1 may also include Figure 1 More or less other hardware or software, or a different arrangement of components.

[0022] It should be noted that the computer device 1 is only an example, and other existing or future computer devices that are adaptable to the present invention should also be included in the protection scope of the present invention and included herein by reference.

[0023] In some embodiments, the memory 11 can be used to store the program code and various data of the computer program. For example, the memory 11 can be used to store the dynamic intelligent test system 10 installed in the computer device 1, and realize high-speed and automatic access to the program or data during the operation of the computer device 1. The memory 11 can be a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), a one-time programmable read-only memory (OTPROM), an electronically erasable rewritable read-only memory (EEPROM), a compact disc (CD-ROM) or other optical disc storage, a magnetic disk storage, a magnetic tape storage, or any other non-volatile computer-readable storage medium that can be used to carry or store data.

[0024] In some embodiments, the at least one processor 12 may be composed of an integrated circuit. For example, it may be composed of a single packaged integrated circuit, or it may be composed of multiple integrated circuits with the same or different functions, including one or more central processing units (CPUs), microprocessors, digital processing chips, graphics processors, and a combination of various control chips. The at least one processor 12 is the control core (Control Unit) of the computer device 1, and uses various interfaces and lines to connect the various components of the entire computer device 1. By executing programs, modules, or instructions stored in the memory 11, and calling data stored in the memory 11, it can execute various functions of the computer device 1 and process data, such as dynamic intelligent testing functions (for details, see the following). Figure 3 ).

[0025] In this embodiment, the dynamic intelligent test system 10 may include one or more modules, which are stored in the memory 11 and executed by at least one or more processors (processor 12 in this embodiment) to implement the dynamic intelligent test function (for details, see the following). Figure 3 ).

[0026] In this embodiment, the dynamic intelligent testing system 10 can be divided into multiple modules according to the functions it performs. Figure 2 As shown, the multiple modules include a calling module 101, an acquiring module 102, a testing module 103, an updating module 104 and a confirming module 105. The module referred to in the present invention refers to a series of computer-readable instruction segments that can be executed by at least one processor (such as the processor 12) and can complete fixed functions, which are stored in a memory (such as the memory 11 of the computer device 1). In this embodiment, the functions of each module will be described in detail later in conjunction with Figure 3 Describe in detail.

[0027] In this embodiment, the integrated unit implemented in the form of a software function module can be stored in a non-volatile readable storage medium. The above-mentioned software function module includes one or more computer-readable instructions, and the computer device 1 or the at least one processor 12 (processor) implements part of the method of each embodiment of the present invention by executing the one or more computer-readable instructions, such as Figure 3 The dynamic intelligent testing method shown.

[0028] In a further embodiment, in combination Figure 2The at least one processor 12 can execute various application programs (such as the dynamic intelligent testing system 10 ), program codes, etc. installed in the computer device 1 .

[0029] In a further embodiment, the memory 11 stores program codes of a computer program, and the at least one processor 12 can call the program codes stored in the memory 11 to execute related functions. For example, Figure 2 The modules of the dynamic intelligent test system 10 are program codes stored in the memory 11 and executed by the at least one processor 12, so as to realize the functions of the modules and achieve the purpose of the dynamic intelligent test function (see below for details). Figure 3 description).

[0030] In one embodiment of the present invention, the memory 11 stores one or more computer-readable instructions, and the one or more computer-readable instructions are executed by the at least one processor 12 to achieve the purpose of dynamic intelligent testing function. Specifically, the specific implementation method of the at least one processor 12 for the above-mentioned computer-readable instructions is described in detail below. Figure 3 Description.

[0031] Figure 3 It is a flow chart of the dynamic intelligent testing method provided by the preferred embodiment of the present invention.

[0032] In this embodiment, the dynamic intelligent testing method can be applied to a computer device 1. For a computer device 1 that needs to perform dynamic intelligent testing, the function for dynamic intelligent testing provided by the method of the present invention can be directly integrated on the computer device 1, or run on the computer device 1 in the form of a software development kit (SDK).

[0033] like Figure 3 As shown, the dynamic intelligent testing method specifically includes the following steps. According to different requirements, the order of the steps in the flowchart can be changed, and some steps can be omitted.

[0034] Step S1: When performing a project test on a target to be tested, the calling module 101 calls a data distribution model of the project.

[0035] In one embodiment, the target to be tested is a motherboard. When a certain project test is required for the motherboard (such as the minimum power consumption value test of the motherboard voltage at different frequencies), the test software of the test station calls the data distribution model of the project in the toolkit on the server to obtain the test range corresponding to the project. It should be noted that the toolkit includes data distribution models of different projects.

[0036] In one embodiment, the items include, but are not limited to, voltage, current, frequency and radio frequency (RF). In this embodiment, the data distribution model is based on the original test data, and the distribution of all test values ​​of the project is obtained after big data analysis, and a model is generated according to the test value of the project. Among them, the original test data includes test data when the target to be tested is a good product and test data when the target to be tested is a defective product. A data distribution model is established by inserting an artificial intelligence (AI) convolutional deep learning module into the test data in the database. And according to each verification result, the model prediction accuracy is re-stated, and it is determined whether the model prediction accuracy obtained by re-statistics is less than the default threshold. When the model prediction accuracy is less than the default threshold, the data distribution model is uploaded to the server. It should be noted that each project can generate its own data distribution model. The data distribution model of each project is uploaded to the server.

[0037] Step S2: The acquisition module 102 acquires the test scope corresponding to the project based on the data distribution model.

[0038] In one embodiment, the test range corresponding to the project includes: obtaining the data distribution range corresponding to the project by calling the data distribution model; obtaining the data interval into which the data with a preset probability falls according to the data distribution range; and setting the data interval as the test range. For example, when testing the voltage of the motherboard, the test software of the test station calls the data distribution model of the project in the toolkit on the server, obtains the voltage distribution range through data analysis by the data distribution model, obtains the data interval into which the data with a preset probability falls according to the voltage distribution range, and defines the data interval as the test range. For example, the voltage distribution range obtained by data analysis by the data distribution model is 1.0V~0.9V, and 95% of the test data falls into the data interval of 1.0V~0.95V, then the test range is defined as 1.0V~0.95V. It should be noted that the preset probability can be set according to the actual situation, and the desired reasonable range can be obtained by adjusting the preset probability.

[0039] In one implementation, the confidence interval of the test range or the preset probability may also be set.

[0040] Step S3: the test module 103 compares whether the acquired test range is smaller than the preset range. When the acquired test range is smaller than the preset range, step S4 is executed; when the acquired test range is greater than or equal to the preset range, step S5 is executed.

[0041] In this embodiment, the test software of the factory test station calls the data distribution model on the server and defines the test range according to the data distribution model. For example, if the preset test voltage range is 1.2V to 0.8V, and the test range obtained on the data model is 1.0V to 0.9V, the test software will only test the voltage within the obtained test range of 1.0 to 0.9V.

[0042] In the prior art, when the data distribution model is not used, the test data is basically distributed between 1.1V and 0.85V. When the voltage test is performed on the target to be tested, the preset range is 1.2V to 0.8V. Now, by analyzing the data and obtaining 95% of the test data distribution range of 1.0V to 0.9V according to the data distribution model, the test range is defined as 1.0 to 0.9V, which is smaller than the test range when the dynamic model is not used.

[0043] Step S4: The testing module 103 tests the mainboard according to the acquired testing range to obtain a testing value when the mainboard is at a minimum power consumption value.

[0044] In one embodiment, the target to be tested is tested by a preset test method according to the acquired test range, and the preset test method includes a binary search algorithm, a Fibonacci search algorithm, a block search algorithm, a hash search algorithm, a binary tree search algorithm, etc.

[0045] In one embodiment, the target to be tested is tested by the preset test method until the target to be tested obtains a minimum power consumption value, which is a critical value found when the target to be tested prompts due to undervoltage or insufficient energy.

[0046] For example, a binary search algorithm is used to test according to the test range. For example, if the test range of the acquired voltage is 1.0V-0.9V, the motherboard is tested after increasing by 0.05V each time from 0.95V (the interval is set by yourself); the motherboard is tested after decreasing by 0.05V each time; if the target to be tested is tested normally when the voltage value is 1.0V, and the motherboard test is abnormal when the voltage value is 0.90V, it means that the critical value is between 0.95V-0.90V, and the binary search algorithm is continued to be used for testing until the critical value is measured.

[0047] Step S5: The testing module 103 tests the item to be tested according to the preset range to obtain a test value when the item to be tested is at a minimum power consumption value.

[0048] In this embodiment, the method of testing the target to be tested according to the preset range is consistent with the method of testing the target to be tested according to the acquired test range, and will not be described in detail herein.

[0049] Step S6: The updating module 104 updates the data distribution model and the test range corresponding to the project according to the test value.

[0050] In this embodiment, the target to be tested is tested, and the test value when the target to be tested is at the minimum power consumption value is added to the test data of the data service layer, the data distribution model of the project is updated, the data analysis is re-performed to obtain the data distribution range, and the test range is redefined according to the data distribution range and the set preset probability.

[0051] It should be noted that when the test data increases, the test results will be closer and closer to the actual threshold of the test. The more concentrated the data distribution is, the smaller the interval of the data distribution with the preset probability will be, the smaller the range to be tested will be, and the faster the test rate will be. According to the increase of the actual test value, the data distribution model will be further dynamically updated. For example, if the test value is only between 0.95V and 0.9V, the data distribution model will also dynamically update the test range corresponding to the project voltage to 0.95V~0.9V.

[0052] Step S7: the confirmation module 105 confirms whether all test items have been tested. When all test items have been tested, the process ends; when there are still test items that have not been tested, the process returns to step S1.

[0053] In this embodiment, when there are still projects that have not completed the test, the data distribution model is called to obtain the latest test range, and the target process to be tested is tested according to the latest test range until the critical value is found. After the test, the verification result data is added to the original data to update the data distribution model. Since the probability of good products is much greater than the probability of defective products, when the test data is increasing, the test result is closer to the true value. When the test data is close to infinity, the test result is approximately the true value, and the test range is getting narrower and narrower. For example, the initial test data is 100, and the data with a statistical probability of 95% is distributed between 1.0V-0.9V. When the data is increasing, the data close to the true value will increase. For example, for 1000 test data, assuming that the frequency of the test result of 0.96V is the largest, it means that it is closer to the true value. Then the data close to 0.96V in 1000 test data will increase, and the data will be more concentrated. Then the range of 95% probability is closer to 0.96V, for example, the data between 0.98-0.94V accounts for 95%. Compare the new test range with the previous test range. If the test range becomes smaller, update the test range of the data distribution model and call the new test range in the next test. Continue to use the binary search algorithm for testing in the next test. For example, the new test range becomes 0.98V-0.94V. Using the binary search algorithm, test the mainboard every time it increases by 0.02V from 0.96V, and test the mainboard every time it decreases by 0.02V from 0.96V. The range to be tested becomes smaller and smaller, and the test rate becomes faster and faster. When the data is 10,000, the test range will be smaller and the test rate will be faster, and so on, until the ideal test range is obtained.

[0054] It should be noted that, in one embodiment, the data distribution model corresponds to one project. For example, when the voltage of the mainboard needs to be tested, the test range corresponding to the voltage can be obtained by calling the first data distribution model; when the current of the mainboard needs to be tested, the test range corresponding to the current can be obtained by calling the second data distribution model. In another embodiment, the data distribution model can correspond to multiple projects. For example, when the voltage and current of the mainboard need to be tested, the test range corresponding to the voltage can be obtained by calling the data distribution model, and the test range corresponding to the current can also be obtained.

[0055] In one embodiment, multiple data distribution models corresponding to different projects can be superimposed to obtain a data distribution model including multiple projects. For example, the test range corresponding to voltage is 0.95V~0.9V, the test range corresponding to current is 50mA~10mA, and the test range corresponding to frequency is 1M-2M. The test data distribution model is uploaded to the server synchronously, and the factory test software will synchronize the data distribution model to the station test software. It can be understood that after the data distribution models of different projects are superimposed, the data distribution model can be changed from two dimensions to multiple dimensions, and the data distribution model of the minimum power consumption value of the motherboard under different test conditions can be obtained, and the minimum power consumption value test range of the motherboard under different test conditions can be obtained. If the data distribution model of the minimum power consumption value of the voltage of the motherboard under different frequencies is tested at the beginning, the number of test cycles can be superimposed on the model, and the data distribution model becomes the data distribution model of the minimum power consumption value of the voltage of the motherboard under different frequencies and different test cycles. The dimension of the model changes from two dimensions to three dimensions, and so on, the dimension of the data distribution model can be increased by superimposing other test items.

[0056] In one embodiment, the dynamic intelligent testing method further includes: performing data analysis on the test data of the test interval within the test range to determine whether the test frequency of the test data in a certain test interval is less than the default frequency value. If the test frequency of the test data in the test interval is less than the default frequency value, it is determined that there is less or no test data in the test interval, and the minimum power consumption value is not within the test interval. The test interval is directly skipped and the test of other test intervals is continued until the minimum power consumption value is obtained. The test can be simplified in combination with data analysis to further improve the test efficiency. If the test frequency of the test data in the test interval is greater than or equal to the default frequency value, it is necessary to perform testing in the test interval.

[0057] In the several embodiments provided by the present invention, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are only illustrative, for example, the division of the modules is only a logical function division, and there may be other division methods in actual implementation.

[0058] The modules described as separate components may or may not be physically separated, and the components shown as modules may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0059] In addition, each functional module in each embodiment of the present invention may be integrated into one processing unit, each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of hardware plus software functional modules.

[0060] It is obvious to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the present invention can be implemented in other specific forms without departing from the spirit or essential features of the present invention. Therefore, from any point of view, the embodiments should be regarded as exemplary and non-restrictive, and the scope of the present invention is defined by the appended claims rather than the above description, and it is intended that all changes falling within the meaning and scope of the equivalent elements of the claims are included in the present invention. Any figure mark in the claims should not be regarded as limiting the claims involved. In addition, it is obvious that the word "comprising" does not exclude other units or, and the singular does not exclude the plural. Multiple units or devices stated in the device claim can also be implemented by one unit or device through software or hardware. The words first, second, etc. are used to indicate names, and do not indicate any particular order.

[0061] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the above preferred embodiments, those skilled in the art should understand that the technical solution of the present invention can be modified or replaced by equivalents without departing from the spirit and scope of the technical solution of the present invention.

Claims

1. A dynamic intelligent testing method, characterized in that: The method includes: When performing project testing on the target to be tested, the data distribution model of the project is called; Acquire a test scope corresponding to the project based on the data distribution model; Testing the target to be tested according to the test range to obtain a test value when the target to be tested is at a minimum power consumption value; Update the data distribution model and test range corresponding to the project according to the test value; and Confirm whether the test frequency of the test data in the test interval within the test range is less than the default frequency value; If the test frequency of the test data in the test interval is less than the default frequency value, skip the test interval and do not perform the test; or If the test frequency of the test data in the test interval is greater than or equal to the default frequency value, the test is performed in the test interval.

2. The dynamic intelligent testing method according to claim 1, characterized in that: The items mentioned include voltage, current, frequency and radio frequency.

3. The dynamic intelligent testing method according to claim 1, characterized in that: The target to be tested is tested by a preset test method, wherein the preset test method includes a binary search algorithm, a Fibonacci search algorithm, a block search algorithm, a hash search algorithm and a binary tree search algorithm.

4. The dynamic intelligent testing method according to claim 1, characterized in that: The method further includes: Check whether the obtained test range is smaller than the preset range; When the acquired test range is smaller than the preset range, testing the target to be tested according to the acquired test range; or When the acquired test range is greater than or equal to the preset range, the target to be tested is tested according to the preset range.

5. The dynamic intelligent testing method according to claim 1, characterized in that: The acquiring the test scope corresponding to the project based on the data distribution model includes: Obtaining the data distribution range corresponding to the project through the data distribution model; Obtaining a data interval into which data with a preset probability falls according to the data distribution range; The data interval is set as the test range.

6. A dynamic intelligent testing system, characterized in that: The system comprises: The calling module is used to call the data distribution model of the project when performing project testing on the target to be tested; An acquisition module, used for acquiring a test scope corresponding to the project based on the data distribution model; A testing module, used to test the target to be tested according to the test range, and obtain a test value when the target to be tested is at a minimum power consumption value; An updating module, used for updating the data distribution model and the test range corresponding to the project according to the test value; and A confirmation module is used to confirm whether the test frequency of the test data in the test interval within the test range is less than the default frequency value; if the test frequency of the test data in the test interval is less than the default frequency value, skip the test interval and do not test; if the test frequency of the test data in the test interval is greater than or equal to the default frequency value, test within the test interval.

7. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores at least one instruction, and when the at least one instruction is executed by a processor, the dynamic intelligent testing method according to any one of claims 1 to 5 is implemented.

8. A computer device, characterized in that: The computer device includes a memory and at least one processor, wherein a plurality of modules are stored in the memory, and when the plurality of modules are executed by the at least one processor, the dynamic intelligent testing method according to any one of claims 1 to 5 is implemented.

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