WO2019056720A1 - Automated test case management method and apparatus, device, and storage medium - Google Patents

Abstract

The present application relates to the field of software automated test technology, and provides an automated test case management method and apparatus, a device, and a storage medium. The automated test case management method comprises: establishing a mapping table in a database according to test cases, each row of the mapping table indicating each step of a test case script; modifying the test cases by modifying the row of the mapping table, and performing automated regression test on the modified mapping table; if the automated regression test is passed, saving the modified mapping table; if the automated regression test is not passed, not saving the modified mapping table. According to the present application, test cases are developed by establishing a mapping table, and furthermore, in a development process, automated regression test is performed on new test cases, thereby improving the efficiency of automated test case development and regression test.

Description

Automated test case management method, device, device and storage medium

This patent application is based on the Chinese invention patent application filed on September 21, 2017, with the application number of 201710857308.1, entitled "Automated Test Case Management Method, Apparatus, Equipment and Storage Medium", and requires its priority.

Technical field

The present application relates to the field of software automated testing technologies, and in particular, to an automated test case management method, apparatus, device, and storage medium.

Background technique

Automated testing of software is a process of turning manual test behavior into a machine that automatically performs tests. Usually, after the test case is designed and passed the review, the tester performs the test step by step according to the procedure described in the test case, and compares the actual result with the expected result. In this process, in order to save manpower, time or hardware resources, and improve test efficiency, automated testing was introduced.

In the process of developing automated test cases, regression testing is required. Among them, the regression test means that after the old code is modified, the test is re-tested to confirm that the modification does not introduce a new error or cause other code to generate an error.

At present, the speed of software development is getting faster and faster. In order to keep up with the speed of software development, it is necessary to further improve the speed of developing automated test cases and conduct effective regression tests at the same time.

Summary of the invention

The embodiment of the present application provides a method, device, device and storage medium for automated test case management, which can improve the speed of developing an automated test case and perform effective regression test at the same time.

This application is implemented as follows:

The first aspect of the present application provides an automated test case management method, including:

Establishing a mapping table in the database according to the test case, each step in the mapping table being each step of the test case script;

Modifying the test case by modifying the row of the mapping table, and performing an automatic regression test on the modified mapping table;

If the automatic regression test is passed, the modified mapping table is saved;

If the automatic regression test is not passed, the modified mapping table is not saved.

The second aspect of the present application provides an automated test case management apparatus, where the automated test case management apparatus includes:

a mapping table obtaining module, configured to establish a mapping table in the database according to the test case, each action in the mapping table is performed in each step of the test case script;

An automatic regression test module, configured to modify the test case by modifying a row of the mapping table, and perform an automatic regression test on the modified mapping table, and save the modified mapping table by using the automatic regression test If the automatic regression test is not passed, the modified mapping table is not saved.

A third aspect of the present application provides a terminal device including a memory, a processor, and computer readable instructions stored in the memory and executable on the processor, the processor executing the computer readable instructions Implement the following steps:

Establishing a mapping table in the database according to the test case, each step in the mapping table being each step of the test case script;

Modifying the test case by modifying the row of the mapping table, performing an automatic regression test on the modified mapping table, and determining whether the modified mapping table passes the automatic regression test;

If the automatic regression test is passed, the modified mapping table is saved;

If the automatic regression test is not passed, the modified mapping table is not saved.

A fourth aspect of the present application provides one or more non-transitory readable storage mediums storing computer readable instructions, the computer readable instructions being executed by one or more processors such that the one or more processes Perform the following steps:

Establishing a mapping table in the database according to the test case, each step in the mapping table being each step of the test case script;

Modifying the test case by modifying the row of the mapping table, performing an automatic regression test on the modified mapping table, and determining whether the modified mapping table passes the automatic regression test;

If the automatic regression test is passed, the modified mapping table is saved;

If the automatic regression test is not passed, the modified mapping table is not saved.

The beneficial effects of the automated test case management method, apparatus, device and storage medium provided by the embodiments of the present application are: developing test cases by establishing a mapping table, and performing automatic regression test on new test cases during the development process, thereby improving automation Test case development and regression testing efficiency.

DRAWINGS

In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings used in the embodiments or the prior art description will be briefly described below. Obviously, the drawings in the following description are only the present application. For some embodiments, other drawings may be obtained from those of ordinary skill in the art without departing from the drawings.

1 is a flowchart of an automated test case management method provided by Embodiment 1 of the present application;

2 is another flowchart of an automated test case management method provided by Embodiment 1 of the present application;

3 is another flowchart of an automated test case management method provided by Embodiment 1 of the present application;

4 is a flowchart of an automated test case management method provided by Embodiment 2 of the present application;

5 is a schematic structural diagram of an automated test case management apparatus provided in Embodiment 3 of the present application;

6 is another schematic structural diagram of an automated test case management apparatus provided in Embodiment 3 of the present application;

FIG. 7 is a schematic structural diagram of a terminal device according to another embodiment of the present application.

Detailed ways

In order to make the objects, technical solutions, and advantages of the present application more comprehensible, the present application will be further described in detail below with reference to the accompanying drawings and embodiments. It is understood that the specific embodiments described herein are merely illustrative of the application and are not intended to be limiting.

Embodiment 1

Please refer to FIG. 1 , which is a flowchart of an automated test case management method provided by an embodiment of the present application.

In step S10, a mapping table is established according to the test cases in the database, and each step of the behavior test case script in the table is mapped.

Among them, the database is a collection of all test cases, the original developed test cases and newly developed test cases are stored in the database, as the development progress database has been updated.

In the process of developing automated test cases, if you directly modify the test cases, you need to perform text-level operations on the test cases themselves. Because there are a large number of programming languages in the test cases, direct modification requires modification of the programming language. The programming ability is very strong and the efficiency is not high. Once there is a problem in the development process, the modification may not be saved, or the important ones may be lost. The progress needs to be checked and re-developed from the beginning, and the mapping table is modified to test the test cases, which can solve these problems and greatly improve the speed of test case development.

The mapping table is a table established for the test case to be developed, and has a mapping relationship with the test case to be developed, and the modification of the test case can be implemented by modifying the mapping table, without directly modifying the test case.

The mapping table can be used to encapsulate the functions of the test case itself. The developer only needs to modify the defined function without paying attention to the function itself, making the script easier to develop and maintain.

Specifically, the table is set in the database, and the test case includes a plurality of script units, and each row of the table is specified to display a name stored in the database by the script unit, and the column of the table displays the content included in the script unit, and each script unit is stored. The ID in the database corresponds to the row on the table, and then the operation type and the control number contained in the script unit corresponding to each row are displayed in the column of the table in turn, and the obtained table is the mapping table, wherein each script unit corresponds to In a way of processing.

Edit the test case Select the test script to be edited, click Edit, and generate a mapping table according to the test script to be edited and the preset table. The operation types include click, long press, drag and drop, button, delay, checkpoint, etc. . You can select any row of the mapping table, call the database, find the data row corresponding to the script unit in the database according to the ID corresponding to the selected row, select any operation and execute, such as deleting a certain step.

Step S20: Modify the test case by modifying the row of the mapping table, and perform an automatic regression test on the modified mapping table.

As an implementation manner, before the automatic regression test, a backup test case and a cache test case are generated. As shown in FIG. 2, step S20 specifically includes:

In step S201, the original test case is backed up.

When the original test case is modified, the original test case is backed up.

Step S202, generating a backup test case.

Generate backup test cases for comparison with later cached test cases.

In step S203, the mapping table is modified.

Begin further development of the original test case.

Step S204, generating a cache test case.

After completing the development of the original test case, the cache test case is generated according to the mapping table, and compared with the previously generated backup test case.

In order to verify the results of the development, the developer should perform a regression test on the modified test case. The regression test refers to a process of re-verifying the program with the test case after the code is modified. The automatic regression test is adopted in the technical solution. Among them, the automatic regression test refers to a comparison between the number of times of checking errors and the detection time in the cache test case and the backup test case regression test.

In step S30, it is determined whether the modified mapping table passes the automatic regression test.

Determining whether the modified mapping table passes the automatic regression test, and the specific steps are as shown in FIG. 3, including:

In step S301, the number of check errors and the detection time of the cache test case are compared with the backup test case.

That is, the cache test case and the backup test case are respectively run for regression test, and the data of the number of check errors and the time of detection are obtained, and the two sets of data are compared.

In step S302, when the number of check errors of the cache test case is greater than the backup test case and the detection time of the cache test case is less than the backup test case, it is regarded as passing the automatic regression test.

That is to say, the error detection rate and detection efficiency of the cache test case are better than the backup test case.

Step S303, when the number of check errors of the cache test case is less than the backup test case or the test time of the cache test case is greater than the backup test case, it is deemed not to pass the automatic regression test.

That is to say, the cache test case is not more advanced than the backup test case.

Through the above steps, it can be determined whether the modified mapping table is more advanced than the backup test case, thereby determining whether the modified mapping table passes the automatic regression test.

In step S40, when the cache test case passes the automatic regression test, the modified mapping table is saved.

If the cache test case passes the automatic regression test, the modified map table is saved, the test case is updated, and the test case database is updated to complete a stage development of the original test case.

If the cache test case does not pass the automatic regression test, the map table is not saved, the original test case is restored, the original database is maintained, and the next round of development and testing is performed.

The beneficial effects of the embodiment of the present application are: developing the original test case by establishing a mapping table, and modifying and then passing the automatic regression test. If the new test case is superior to the original test case, the new test case is saved and the database is updated simultaneously. , restore the original test case, carry out the next round of development and testing, accelerate the development of automated test cases, and improve the efficiency of regression testing.

Embodiment 2

In the first embodiment, a plurality of new test cases that can pass the automatic regression test can be generated for one original test case, and then a subset is established in the database to save the new test cases.

In order to optimize these new test cases, Bayesian classification can be prioritized, so that the target of new software defects can be found more quickly and with fewer test cases, and the regression test can be improved. s efficiency.

The method processing flow of the embodiment of the present application includes four modules of historical data preprocessing, classification mining training set construction, classification mining training and prediction, and test case prioritization.

The historical data preprocessing module is responsible for collecting and extracting test result execution results of different versions and historical data of module changes, and converting into test case execution result data matrix and module change data matrix of different versions required for subsequent processing.

The classification mining training set building module uses the test case execution result data matrix and the module change data matrix under different versions to establish a training set required for the classification mining training for each test case.

The classification mining training and prediction module uses different classification mining models, training based on the training set of each test case, and using the post-training model to predict the execution results of the test cases in the new version.

The test case prioritization sorting module prioritizes all test cases based on the predicted execution results, prioritizing the execution of the preceding test cases.

Please refer to FIG. 4, which shows the implementation steps of each module described above:

The data preprocessing module includes two parts: test data preprocessing and module change data preprocessing, namely steps S402 and S403, and the processing flow thereof includes:

First, collect and organize the execution result information of the test cases under each version. The first step is to determine the version number n of the test case execution result matrix and the number of test cases m. Let the number of versions of the software system be n, the version set V={v1, v2,..., vn}; there are m different test cases, test case set T={t1, t2,...,tm} . Then, a test case execution result matrix R(m,n)=[rij]m×n is established, where rrj is a matrix element, indicating the execution result of the test case ti on the version vj.

Rij has three values: 0 means the test passes; 1 means the test fails; null (null) means that the test case ti has not been executed in version vj.

All elements rij in the matrix are initialized to null first, and then the elements rij in the matrix are assigned according to the execution result of the test case ti on the version vj.

The process of pre-processing the version change data includes:

First determine the number of modules included in the software system, so that the software system contains 1 module (the module's partitioning criteria are defined according to the software system characteristics and test coverage granularity, such as defining an object of the Java program as a module), so the software system System= {Mod1, Mod2,...,Modl}.

Next you need to determine the sample version v0. The sample version is used as a reference standard for version changes. The sample version can be selected to follow the following standards: The first version should be a stable version, the function and structure are complete, and the second version should contain all of the software system System. Module, the third sample version should be the version with the least chance of test case execution error, the most stable version.

Based on the sample version v0, the version change matrix Δ(n,l)=[δjk]n×l is constructed in units of modules, wherein the change matrix element δjk indicates whether the version vj is changed on the module Modk compared to the sample version v0. .

Δjk has two values: 0 means that the version vj is compared with the sample version v0, and no change occurs on the module Modk; 1 means that the version vj is changed on the module Modk relative to the sample version v0.

Step S404, the classification mining training set is constructed, that is, the classification mining training set building module, and the processing flow thereof comprises:

The training set builds the assumptions associated with the test case based on the module change: each test case ti has different degrees of detection capability for different module defects, and the new defect is introduced due to a change in some modules in the new version; When the module changes, some test cases will be more sensitive, that is, their defect detection capability will be higher than other test cases, so the module changes are related to the execution results of the test cases, which can be analyzed and determined by classification mining.

A classification mining training set is constructed for each test case. Given the test case ti in the test case set T, considering each version vj of the use case ti, the change information δjk of each module Modk in the version vj and the use case ti The result rij is merged into a data vector in the version vj: <δj1, δj2, ..., δjn, rij>; then the use case ti is merged into a matrix in each version of the data vector to form the training set Trainseti of the use case ti.

For the test case ti, the training set Trainseti = [Δ, Ri] is a matrix of n' × (l + 1). Where Δ(n',l) is taken from the module change data matrix Δ(n,l), regardless of the version of the unexecuted use case ti; Ri is an n'×1 vector, which is the test case execution result matrix R(m,n) The transposition of the i-th row in the middle row indicates the execution result of the test case ti in the n versions, and the version of the unused use case ti is also not considered.

In classification mining, a training set consists of a set of records, each of which is divided into an attribute (Attribute) and a class label (Class Label), and the class label corresponds to the classification result. One row of the training set is used as a record. The change of the first l column, that is, the l module, is used as the attribute, and the last column is the execution result rij as the class tag.

Step S405, training and predicting the result, that is, the classification mining training and prediction module, the processing flow of which includes:

Two Bayesian classification models, HNB and AODE, are selected in the classification mining training and prediction part. AODE is a semi-simple Bayesian technique. Compared with the naive Bayesian technique, AODE reduces the mutual independence of attributes and can effectively improve the accuracy of classification results in practical applications. HNB is another Bayesian technique that combines the advantages of a simple Bayesian model with a Bayesian network model, while overcoming the property independent assumptions of the simple Bayesian model and the shortcomings of Bayesian network structure learning.

Load the two models separately and initialize them. Since HNB does not need to set any parameters, it is initialized by default when loading HNB. For AODE, you need to set the minimum frequency freq, which is an integer, indicating that a combination of at least freq times occurs. Normally, 1 can be used; if the training set is large, the value of freq can be increased appropriately to reduce the influence of accidental combination.

For each test case ti, the corresponding training set Trainseti is loaded for training. When the training set is large, the maximum number of training steps and the maximum training time can be set.

Prepare the new version of the module change information and fill in the test set Testseti=[Δnew,θi] with the same format requirements of the training set. The new version change information set Δnew={δ1, new, δ2, new, ..., δl, new} represents the module change vector in the new version.

Substitute the test set into the trained classification mining model in the previous step, and predict the execution result θi of the test case ti in the new version. This value is a floating point value (between 0 and 1), which means that the test case ti can find the new version. The probability of a software defect.

Combining the prediction results of all test cases, the final output of the classification mining training and prediction module is a triple set Prof={<ti, θi, type>|ti∈t, 0<θi≤1,1≤i≤m,type ∈{HNB,AODE}}, where ti is the test case; type is the selected classification model; probability θi indicates the probability that the test case ti can find the new version of the software defect, and the higher the θi, the higher the value of the test case ti, the more worthwhile Priority test.

Step S406, the test case sorting, that is, the test case prioritization sorting module, the processing flow includes:

Two Bayesian classification mining models of HNB and AODE are used to predict respectively. First, two ternaries in the Prof set corresponding to the test case ti are taken, and the two θi sums are averaged to obtain a new version of the test case ti. The final predicted probability pi of the software defect. All test cases are sorted by finding the final probability pi of the software defect for each test case. The time to consider the regression test phase is limited. Let the total time of the regression test be timemax, and select the first m' test cases that can be completed within timemax to form the final regression test case set.

The beneficial effects of the embodiments of the present application are: by performing historical data preprocessing, classification mining training set construction, classification mining training, and prediction and test case prioritization sorting on the new test case training set, the test cases are optimized, thereby realizing Quickly and more discover the goal of new versions of software defects with fewer test cases, speed up the development of automated test cases, and improve the efficiency of regression testing.

Embodiment 3

Please refer to FIG. 5 , which illustrates an automated test case management device 40 provided by another embodiment of the present application. The automated test case management device 40 includes a mapping table obtaining module 401 and an automatic regression testing module 402 .

a mapping table obtaining module 401, configured to establish a mapping table in the database according to the test case, each step of the test case script in the mapping table;

The automatic regression test module 402 is configured to modify the test case by modifying a row of the mapping table, perform an automatic regression test on the modified mapping table, and determine whether the modified mapping table passes the automatic regression test. If the automatic regression test is passed, the modified mapping table is saved, and if the automatic regression test is not passed, the modified mapping table is not saved.

Specifically, the automatic regression test module 402 includes:

Backing up the original test case to generate a backup test case, and generating a cache test case according to the modified mapping table;

Testing the cache test case and the backup test case separately for checking the number of errors and detecting time;

If the number of check errors of the cache test case is greater than the backup test case and the detection time of the cache test case is less than the backup test case, it is considered to pass the automatic regression test and save the modified mapping table;

If the number of check errors of the cache test case is less than the backup test case or the cache test case is greater than the backup test case, it is deemed not to pass the automatic regression test and does not save the modified mapping table. .

Referring to FIG. 6, as an implementation manner, the automated test case management apparatus 40 further includes:

The prioritization module 403 is configured to prioritize test cases that are tested by the automatic regression test. Specifically, select two classification mining models, Bayesian classification HNB and AODE, and use corresponding training sets for each test case. Model training is performed to prioritize test cases based on the combined results of the model predictions.

For the specific working process of the module in the foregoing device, refer to the corresponding process in the foregoing method embodiment, and details are not described herein again.

The beneficial effects of the automated test case management device provided by the embodiment of the present application are that the test case is developed by establishing a mapping table, and the automatic test of the new test case is automatically performed during the development process, thereby improving the automatic test case development and the regression test. effectiveness

Another embodiment of the present application provides one or more non-volatile readable storage media storing computer readable instructions that, when executed by one or more processors, cause one or more processors The method for implementing the automated test case management in the above embodiments is implemented. To avoid repetition, details are not described herein again. Alternatively, when the computer readable instructions are executed by one or more processors, causing one or more processors to perform the functions of the modules/units in the automated test case management device in the above embodiments, to avoid repetition, no further details are provided herein. .

Fig. 7 is a schematic diagram of a terminal device in this embodiment. As shown in FIG. 7, terminal device 60 includes a processor 61, a memory 62, and computer readable instructions 63 stored in memory 62 and operative on processor 61. The processor 61 executes the computer readable instructions 63 to implement various steps of an automated test case management method of the above-described embodiments, such as steps S10, S20, and S30 shown in FIG. Alternatively, when the processor 61 executes the computer readable instructions 63, the functions of each module/unit of the automated test case management device in the above embodiments are implemented, for example, the mapping table obtaining module 401, the automatic regression testing module 402, and the priority shown in FIG. The function of the sorting module 403.

It will be clearly understood by those skilled in the art that, for convenience and brevity of description, only the division of each functional unit and module described above is exemplified. In practical applications, the above functions may be assigned to different functional units according to needs. The module is completed by dividing the internal structure of the device into different functional units or modules to perform all or part of the functions described above.

The above-mentioned embodiments are only used to explain the technical solutions of the present application, and are not limited thereto; although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that they can still implement the foregoing embodiments. The technical solutions described in the examples are modified or equivalently replaced with some of the technical features; and the modifications or substitutions do not deviate from the spirit and scope of the technical solutions of the embodiments of the present application, and should be included in Within the scope of protection of this application.

Claims (20)

1. An automated test case management method, characterized in that the automated test case management method comprises:

   Establishing a mapping table in the database according to the test case, each step in the mapping table being each step of the test case script;

   Modifying the test case by modifying the row of the mapping table, performing an automatic regression test on the modified mapping table, and determining whether the modified mapping table passes the automatic regression test;

   If the automatic regression test is passed, the modified mapping table is saved;

   If the automatic regression test is not passed, the modified mapping table is not saved.
2. The automated use case management method according to claim 1, wherein the modification of the test case is performed by modifying a row of the mapping table, including:

   Back up the original test case to generate a backup test case, and generate a cache test case based on the modified map form.
3. The automated use case management method according to claim 2, wherein the modified mapping table is subjected to an automatic regression test, and if the automatic regression test is passed, the modified mapping table is saved; if the automatic regression is not passed Test, the modified mapping table is not saved, including:

   Testing the cache test case and the backup test case separately for checking the number of errors and detecting time;

   If the number of check errors of the cache test case is greater than the backup test case and the detection time of the cache test case is less than the backup test case, it is considered to pass the automatic regression test and save the modified mapping table;

   If the number of check errors of the cache test case is less than the backup test case or the cache test case is greater than the backup test case, it is deemed not to pass the automatic regression test and does not save the modified mapping table. .
4. The automated use case management method according to claim 3, wherein the number of check errors in the cache test case is greater than the backup test case and the detection time of the cache test case is less than the backup test The use case is regarded as the step of testing and saving the modified mapping table by the automatic regression test, and the automatic use case management method further includes:

   The test cases passed the automatic regression test are prioritized.
5. The automated use case management method according to claim 4, wherein the prioritizing the test cases by the automatic regression test comprises:

   Bayesian classification HNB and AODE two classification mining models are selected. Each test case is trained by using the corresponding training set, and the test cases are prioritized according to the comprehensive results predicted by the model.
6. An automated test case management device, wherein the automated test case management device comprises:

   a mapping table obtaining module, configured to establish a mapping table in the database according to the test case, each action in the mapping table is performed in each step of the test case script;

   An automatic regression test module, configured to modify the test case by modifying a row of the mapping table, perform an automatic regression test on the modified mapping table, and determine whether the modified mapping table passes the automatic regression test, if Through the automatic regression test, the modified mapping table is saved, and if the automatic regression test is not passed, the modified mapping table is not saved.
7. The automated test case management apparatus according to claim 6, wherein the automatic regression test module is further configured to:

   Back up the original test case to generate a backup test case, and generate a cache test case based on the modified map form.
8. The automated test case management apparatus according to claim 7, wherein the automatic regression test module is further configured to:

   Testing the cache test case and the backup test case separately for checking the number of errors and detecting time;

   If the number of check errors of the cache test case is greater than the backup test case and the detection time of the cache test case is less than the backup test case, it is deemed to pass the automatic regression test and save the modified mapping table;

   If the number of check errors of the cache test case is less than the backup test case or the cache test case is greater than the backup test case, it is deemed not to pass the automatic regression test and does not save the modified mapping table. .
9. The automated test case management apparatus according to claim 8, wherein said automated test case management device further comprises a prioritization module;

   The prioritization module is configured to prioritize test cases that pass the automatic regression test.
10. The automated test case management apparatus according to claim 9, wherein the prioritization module is further configured to:

    Bayesian classification HNB and AODE two classification mining models are selected. Each test case is trained by using the corresponding training set, and the test cases are prioritized according to the comprehensive results predicted by the model.
11. A terminal device comprising a memory, a processor, and computer readable instructions stored in the memory and operable on the processor, wherein the processor executes the computer readable instructions as follows step:

    Establishing a mapping table in the database according to the test case, each step in the mapping table being each step of the test case script;

    Modifying the test case by modifying the row of the mapping table, performing an automatic regression test on the modified mapping table, and determining whether the modified mapping table passes the automatic regression test;

    If the automatic regression test is passed, the modified mapping table is saved;

    If the automatic regression test is not passed, the modified mapping table is not saved.
12. The terminal device according to claim 11, wherein the modifying the test case by modifying a row of the mapping table comprises:

    Back up the original test case to generate a backup test case, and generate a cache test case based on the modified map form.
13. The terminal device according to claim 12, wherein the modified mapping table is subjected to an automatic regression test, and if the automatic regression test is performed, the modified mapping table is saved; if the automatic regression is not passed Test, the modified mapping table is not saved, including:

    Testing the cache test case and the backup test case separately for checking the number of errors and detecting time;

    If the number of check errors of the cache test case is greater than the backup test case and the detection time of the cache test case is less than the backup test case, it is considered to pass the automatic regression test and save the modified mapping table;

    If the number of check errors of the cache test case is less than the backup test case or the cache test case is greater than the backup test case, it is deemed not to pass the automatic regression test and does not save the modified mapping table. .
14. The terminal device according to claim 13, wherein in the case that the number of check errors of the cache test case is greater than the backup test case and the detection time of the cache test case is less than the backup test case, After the step of performing the automatic regression test and saving the modified mapping table, the processor further implements the following steps when the computer readable instructions are executed:

    The test cases passed the automatic regression test are prioritized.
15. The terminal device according to claim 14, wherein said prioritizing test cases by said automatic regression test comprises:

    Bayesian classification HNB and AODE two classification mining models are selected. Each test case is trained by using the corresponding training set, and the test cases are prioritized according to the comprehensive results predicted by the model.
16. One or more non-transitory readable storage mediums storing computer readable instructions, wherein when the computer readable instructions are executed by one or more processors, cause the one or more processors to execute The following steps:

    Establishing a mapping table in the database according to the test case, each step in the mapping table being each step of the test case script;

    Modifying the test case by modifying the row of the mapping table, performing an automatic regression test on the modified mapping table, and determining whether the modified mapping table passes the automatic regression test;

    If the automatic regression test is passed, the modified mapping table is saved;

    If the automatic regression test is not passed, the modified mapping table is not saved.
17. The non-volatile readable storage medium of claim 16, wherein the modifying the test case by modifying a row of the mapping table comprises:

    Back up the original test case to generate a backup test case, and generate a cache test case based on the modified map form.
18. The non-volatile readable storage medium of claim 17, wherein the modified mapping table is subjected to an automatic regression test, and if the automatic regression test is performed, the modified mapping table is saved; If the automatic regression test is not passed, the modified mapping table is not saved, including:

    Testing the cache test case and the backup test case separately for checking the number of errors and detecting time;

    If the number of check errors of the cache test case is greater than the backup test case and the detection time of the cache test case is less than the backup test case, it is considered to pass the automatic regression test and save the modified mapping table;

    If the number of check errors of the cache test case is less than the backup test case or the cache test case is greater than the backup test case, it is deemed not to pass the automatic regression test and does not save the modified mapping table. .
19. The non-volatile readable storage medium according to claim 18, wherein said detection time of said cache test case is greater than said backup test case and said cache test case has a detection time less than The backup test case is considered to be caused by the automatic regression test and after saving the modified mapping table step, the computer readable instructions being executed by one or more processors, such that the one or more processors Also perform the following steps:

    The test cases passed the automatic regression test are prioritized.
20. The non-volatile readable storage medium of claim 19, wherein the prioritizing the test cases passed the automatic regression test comprises:

    Bayesian classification HNB and AODE two classification mining models are selected. Each test case is trained by using the corresponding training set, and the test cases are prioritized according to the comprehensive results predicted by the model.

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