Methods and systems for testing mobile applications

• US 10,055,339 B2
• Filed: 11/17/2016
• Issued: 08/21/2018
• Est. Priority Date: 09/28/2016
• Status: Active Grant

• Current Assignee: Wipro Limited
• Original Assignee: Wipro Limited
• Inventors: Bhojan, Rajkumar Joghee
• Primary Examiner(s): Brophy, Matthew J
• Application Number:
  US15/354,741
• Publication Number:
  US 20180089068A1
• Time in Patent Office: 642 Days
• Field of Search: None
• CPC Class Codes: G06F 11/3664 Environments for testing or debugging software
• CPC Class Codes: G06F 11/3684 for test design, e.g. generating new test cases
• CPC Class Codes: G06F 11/3688 for test execution, e.g. scheduling of test suites
• CPC Class Codes: G06F 8/61 Installation
• CPC Class Codes: H04W 4/50 Service provisioning or reconfiguring

Abstract

A method, device, and non-transitory computer readable medium for testing mobile applications in a mobile application testing system is disclosed. The method includes creating at least one Docker container in the mobile application testing system. After creating the at least one docker container, the method identifies a mobile application for testing. The method automatically generates at least one test artifact in response to identifying the mobile application for testing. Thereafter, the method installs the at least one test artifact for the mobile application for testing in the at least one Docker container. Further, the method selects at least one mobile device in response to installing the at least one test artifact for the mobile application for testing in the at least one Docker container. Thereafter, the method executes the at least one test artifact for the at least one selected mobile device in the at least one Docker container.

Claims

1. A method for testing mobile applications implemented by a mobile application testing computing device, the method comprising:

creating at least one Docker container in the mobile application testing computing device;

identifying a mobile application for testing;

automatically generating at least one test artifact in response to identifying the mobile application for testing, wherein the test artifact comprises one or more test conditions;

installing the at least one test artifact for testing in the at least one Docker container;

selecting at least one mobile device in response to installing the at least one test artefact based on a decision tree algorithm that comprises a decision tree having a plurality of nodes, wherein at least a node of the decision tree is indicative of a mobile device or an observation corresponding to a mobile device, and the observation is derived based on the one or more test conditions, and a pruning of the nodes is performed on each node of the decision tree to select one or more nodes of the decision tree that assist in classification of instances leading to the selection; and

executing the at least one test artifact for the at least one selected mobile device in the at least one Docker container.

2. The method of claim 1 further comprising installing at least one of a mobile testing tool, a continuous integration tool, a test data management tool, or a mobile driver file in the at least one Docker container.

3. The method of claim 1, further comprising:

creating at least one test case based on the mobile application;

creating test data for the at least one created test case; and

generating a test script based on the at least one test case and the test data.

4. The method of claim 1, further comprising selecting the at least one mobile device based on an input received from a user device.

5. The method of claim 1, further comprising:

converting the at least one Docker container into an image file; and

deploying the image file for parallel execution in the at least one Docker container.

6. The method of claim 1 further comprising generating a test report in response to executing the at least one test artifact for the at least one selected mobile device in the at least one Docker container, wherein the test report comprises information associated with outcome of the execution of the at least one test artifact.

19. The method of claim 1, wherein a count of the generated Docker container is based on at least one or more user stories for generating the test artifacts, one or more user requirements for generating the test artifacts, computing power associated with each Docker container, a cost function associated with the testing of the mobile application, and a time function associated with the mobile application.

7. A mobile application testing computing device comprising a memory comprising programmed instructions stored thereon and one or more processors coupled to the memory and configured to be capable of executing the stored programmed instructions to:

create at least one Docker container in the mobile application testing computing device;

identify a mobile application for testing;

automatically generate at least one test artifact in response to identifying the mobile application for testing, wherein the test artifact comprises one or more test conditions;

install the at least one test artifact for testing in the at least one Docker container;

select at least one mobile device in response to installing the at least one test artefact based on a decision tree algorithm that comprises a decision tree having a plurality of nodes, wherein at least a node of the decision tree is indicative of a mobile device or an observation corresponding to a mobile device, the observation is derived based on the one or more test conditions, and a pruning of the nodes is performed on each node of the decision tree to select one or more nodes of the decision tree that assist in classification of instances leading to the selection; and

execute the at least one test artifact for the at least one selected mobile device in the at least one Docker container.

8. The mobile application testing computing device of claim 7, wherein the one or more processors are further configured to be capable of executing the stored programmed instructions to install at least one of a mobile testing tool, a continuous integration tool, a test data management tool, or a mobile driver file in the at least one Docker container.

9. The mobile application testing computing device of claim 7, wherein the one or more processors are further configured to be capable of executing the stored programmed instructions to:

create at least one test case based on the mobile application;

create test data for the at least one created test case; and

generate a test script based on the at least one test case and the test data.

10. The mobile application testing computing device of claim 7, wherein the one or more processors are further configured to be capable of executing the stored programmed instructions to select the at least one mobile device based on an input received from a user device.

11. The mobile application testing computing device of claim 7, wherein the one or more processors are further configured to be capable of executing the stored programmed instructions to:

convert the at least one Docker container into an image file; and

deploy the image file for parallel execution in the at least one Docker container.

12. The mobile application testing computing device of claim 7, wherein the one or more processors are further configured to be capable of executing the stored programmed instructions to generate a test report in response to executing the at least one test artifact for the at least one selected mobile device in the at least one Docker container, wherein the test report comprises information associated with outcome of the execution of the at least one test artifact.

13. A non-transitory computer readable medium comprising programmed instructions stored thereon for testing mobile applications that when executed by one or more processors cause the one or more processors to:

create at least one Docker container in a mobile application testing computing device;

identify a mobile application for testing;

automatically generate at least one test artifact in response to identifying the mobile application for testing;

install the at least one test artifact for testing in the at least one Docker container, wherein the test artifact comprises one or more test conditions;

select at least one mobile device in response to installing the at least one test artefact based on a decision tree algorithm that comprises a decision tree having a plurality of nodes, at least a node of the decision tree is indicative of a mobile device or an observation corresponding to a mobile device, and the observation is derived based on the one or more test conditions, and a pruning of the nodes is performed on each node of the decision tree to select one or more nodes of the decision tree that assist in classification of instances leading to the selection; and

execute the at least one test artifact for the at least one selected mobile device in the at least one Docker container.

14. The non-transitory computer readable medium of claim 13, wherein the programmed instructions, when executed by the one or more processors, further cause the one or more processors to install at least one of a mobile testing tool, a continuous integration tool, a test data management tool, or a mobile driver file in the at least one Docker container.

15. The non-transitory computer readable medium of claim 13, wherein the programmed instructions, when executed by the one or more processors, further cause the one or more processors to:

create at least one test case based on the mobile application;

create test data for the at least one created test case; and

generate a test script based on the at least one test case and the test data.

16. The non-transitory computer readable medium of claim 13, wherein the programmed instructions, when executed by the one or more processors, further cause the one or more processors to select the at least one mobile device based on an input received from a user device.

17. The non-transitory computer readable medium of claim 13, wherein the programmed instructions, when executed by the one or more processors, further cause the one or more processors to:

convert the at least one Docker container into an image file; and

deploy the image file for parallel execution in the at least one Docker container.

18. The non-transitory computer readable medium of claim 13, wherein the programmed instructions, when executed by the one or more processors, further cause the one or more processors to generate a test report in response to executing the at least one test artifact for the at least one selected mobile device in the at least one Docker container, wherein the test report comprises information associated with outcome of the execution of the at least one test artifact.