CN111639036A - Continuous integration test development method and system based on AI test - Google Patents

Abstract

The invention discloses a continuous integration test development method and a system based on AI test, the method comprises the following steps: s1, submitting a code to a remote warehouse; s2, triggering a script running code; s3, triggering a script to execute the MABL; s4, MABL executes AI test; s5, pushing a test result to a developer; and S6, storing the file into a local archive. The invention also provides a continuous integration test development system based on the AI test. By using the CI/CD environment and integrating the existing AI test product MABL, the invention can carry out the project code test in the project development stage, finds the problem in the development stage, modifies the problem in time, indirectly shortens the development period of the project, lightens the pressure of the test team and reduces the manual test cost of the company.

Description

Continuous integration test development method and system based on AI test

Technical Field

The invention relates to the field of computers, in particular to a continuous integration test development method and system based on AI test.

Background

Software testing describes a process used to facilitate the identification of the correctness, integrity, security, and quality of software. In other words, software testing is a process of auditing or comparing between actual output and expected output. The classical definition of software testing is: the process of operating a program under specified conditions to discover program errors, to measure software quality, and to evaluate whether it meets design requirements.

Software testing industry standards (IEEE/ANSI) have been established, and the definition given under software testing in the software engineering terminology proposed by IEEE in 1983 is: "a process for running or testing a software system using manual or automatic means, with the purpose of checking whether it meets specified requirements or to figure out differences between expected and actual results". This definition explicitly states that the purpose of software testing is to verify that a software system meets requirements. It is not disposable any more, and is only the activity of development later stage, but fuses with the whole development flow. Software testing has become a specialty, requiring the use of specialized methods and tools, specialized talents and experts to undertake.

At present, an AI test-based tool is used for testing a project by a testing team after the project is finished, and pushing problems to developers after BUG is found, so that countless versions of the final project appear through one iteration of the form, the project development cycle time is indirectly prolonged, and the project development cost is increased.

Disclosure of Invention

The invention aims to overcome the defects of the prior art and provide a continuous integration test development method and system based on AI test, which provides a code test for project developers in the project development stage, solves the problem of BUG in the development process, shortens the development cycle of the project and reduces the software test cost of the project.

The purpose of the invention is realized by the following technical scheme:

a continuous integration test development method based on AI test comprises the following steps:

s1, submitting the code to a remote warehouse;

s2, triggering script running codes;

s3, triggering the script to execute the MABL;

s4, MABL performs AI testing;

s5, directly pushing the test result to a developer;

and S6, storing the data into a local archive.

Optionally, the submitting the code to the remote repository in step S1 includes the following sub-steps:

s101, building a CI/CD environment and developing projects based on the built environment;

s102, using Jenkins as a core management tool to complete continuous integration/continuous deployment of project tests;

s103, for different development voices, when codes are submitted, different scripts are triggered through Jenkins, development project classifications are packaged, and the development projects are submitted and issued to a remote warehouse.

Alternatively, in step S2, the script code must be executed based on the CI/CD environment, and the item execution address is acquired.

Optionally, in step S3, after the script code is successfully executed, executing script operation MABL, where the main steps are as follows:

s301, handing the MABL to Jenkins for management: configuring a MALL startup SHELL script into a build item in Jenkins, and triggering to run at regular time;

s302, writing a script program for running the MABL;

s303, directly triggering the written script program after the step S302 is finished;

s304, starting the MABL.

Optionally, in the step S4, the AI test executed by the MABL is to start testing the operated item after the MABL is successfully operated, and the main steps are as follows:

s401, writing the operation address of the item in the step S2 into a script;

s402, the MABL acquires the item operation address in the script;

and S403, reading the specified file in the disk by the MABL according to the configuration, acquiring the address of the item to be tested, and executing the AI intelligent test through automatic retrieval of the MABL.

A continuous integrated test development system based on AI test comprises

The project development module is used for developing projects based on the CI/CD environment by developers;

the code submitting module is used for acquiring project codes by a user, classifying, packaging and submitting the project codes to a test platform;

the project testing platform is used for a developer to locally test and run a project application program and generate a corresponding test report;

the test result pushing module is used for directly pushing the test report to the project developer after the project test is finished;

and the data storage module is used for storing the project test results into a local archive for machine learning.

The invention has the beneficial effects that: the scheme integrates the existing AI test technology into a CI/CD environment, tests the project in the development phase, finds the project problem, solves some BUG problems in the development phase, reduces the pressure of a test team, and indirectly shortens the project development period.

Drawings

FIG. 1 is a flow chart of the method of the present invention.

Fig. 2 is a schematic diagram of the system architecture of the present invention.

Detailed Description

In order to more clearly understand the technical features, objects, and effects of the present invention, embodiments of the present invention will now be described with reference to the accompanying drawings.

In this embodiment, as shown in fig. 1, a method for developing a persistent integration test based on an AI test includes the following steps:

step 1: the method comprises the steps of building a CI/CD environment, finishing continuous integration/continuous deployment of project testing by using Jenkins as a core management tool based on building environment development projects, triggering different scripts through the Jenkins when submitting codes according to different development voices, packaging classification of the development projects, and submitting and releasing the development projects to a remote warehouse.

Step 2: and triggering the script running code and acquiring the item running address based on the CI/CD environment.

And step 3: and (4) handing the MABL in Jenkins management, configuring the MABL starting SHELL script into a build item in Jenkins, and triggering to run at regular time. And then writing a script program for running the MABL, and directly triggering the written script program to run and start the MABL after the writing of the MABL script program is finished.

And 4, step 4: and after the MABL is successfully operated, starting to test the operated items, writing the operation address of the item in the step 2 into the script, and acquiring the item operation address in the script by the MABL. And the MABL reads the specified file in the disk according to the configuration, acquires the address of the item to be tested, executes AI intelligent test through automatic MABL retrieval, and outputs a test result report of the item software.

And 5, directly pushing a test result report to developers after the MABL test is finished.

And 6, storing the test result into a local archive for machine learning.

In this embodiment, as shown in fig. 2, a continuous integrated test development system based on an AI test is further provided, and includes a project development module, a code submission module, a project test platform, a test including push module, and a data storage module. The project development module is used for developing projects based on a CI/CD environment by developers; the code submitting module is used for acquiring project codes, classifying, packaging and submitting the project codes to a test platform; the project testing platform is used for a developer to locally test and run a project application program and generate a corresponding test report; the test report pushing module is used for directly pushing the test report to a project developer after the project test is finished; and the data storage module is used for storing the project test results into a local archive for machine learning.

In this embodiment, an operation flow of the continuous integrated test development system based on the AI test includes: developers build a CI/CD environment in the system and develop projects in a project development module. After the project development is completed, the project development codes are submitted to a project testing platform through a code submitting module. In the project testing platform, a developer locally tests project codes, a BUG problem possibly exists in the tested project codes, and the platform outputs a testing report after the testing is finished. The system directly pushes the test report to developers who submit project tests, and stores the test report in a local archive, so that subsequent machine learning is facilitated.

The foregoing shows and describes the general principles and broad features of the present invention and advantages thereof. It will be understood by those skilled in the art that the present invention is not limited to the embodiments described above, which are described in the specification and illustrated only to illustrate the principle of the present invention, but that various changes and modifications may be made therein without departing from the spirit and scope of the present invention, which fall within the scope of the invention as claimed. The scope of the invention is defined by the appended claims and equivalents thereof.

Claims (6)

1. A continuous integration test development method based on AI test is characterized by comprising the following steps: s1, submitting the code to a remote warehouse;

s2, triggering script running codes;

s3, triggering the script to execute the MABL;

s4, MABL performs AI testing;

s5, directly pushing the test result to a developer;

and S6, storing the data into a local archive.

2. The AI-test-based persistent integration test development method according to claim 1, wherein the step of submitting code to a remote repository in step S1 comprises the sub-steps of:

s101, building a CI/CD environment and developing projects based on the built environment;

s102, using Jenkins as a core management tool to complete continuous integration/continuous deployment of project tests;

s103, for different development voices, when codes are submitted, different scripts are triggered through Jenkins, development project classifications are packaged, and the development projects are submitted and issued to a remote warehouse.

3. The AI-test-based persistent integration test development method according to claim 1, wherein the script code must be executed based on CI/CD environment in step S2 while the item execution address is obtained.

4. The AI-test-based persistent integration test development method according to claim 1, wherein the step S3 is to execute script operation MABL after the script code is successfully executed, and the main steps are as follows:

s301, handing the MABL to Jenkins for management: configuring a MALL startup SHELL script into a build item in Jenkins, and triggering to run at regular time;

s302, writing a script program for running the MABL;

s303, directly triggering the written script program after the step S302 is finished;

s304, starting the MABL.

5. The AI-test-based persistent integration test development method according to claim 1, wherein the AI test executed by the MABL in the step S4 is to start testing the running project after the MABL is successfully run, and the main steps are as follows:

s401, writing the operation address of the item in the step S2 into a script;

s402, the MABL acquires the item operation address in the script;

and S403, reading the specified file in the disk by the MABL according to the configuration, acquiring the address of the item to be tested, and executing the AI intelligent test through automatic retrieval of the MABL.

6. A continuous integration test development system based on AI test is characterized by comprising

The project development module is used for developing projects based on the CI/CD environment by developers;

the code submitting module is used for acquiring project codes by a user, classifying, packaging and submitting the project codes to a test platform;

the project testing platform is used for a developer to locally test and run a project application program and generate a corresponding test report;

the test result pushing module is used for directly pushing the test report to the project developer after the project test is finished;

and the data storage module is used for storing the project test results into a local archive for machine learning.

Images