System and method for automated intelligent mobile application testing

• US 10,430,324 B2
• Filed: 01/11/2018
• Issued: 10/01/2019
• Est. Priority Date: 01/11/2017
• Status: Active Grant

• Current Assignee: Smartlytics, LLC
• Original Assignee: Smartlytics, LLC
• Inventors: Hamid, Syed, Hartin, Justin
• Primary Examiner(s): Vo, Ted T.
• Application Number:
  US15/869,013
• Publication Number:
  US 20180329813A1
• Time in Patent Office: 628 Days
• Field of Search: 717124-135
• CPC Class Codes: G06F 11/3688 for test execution, e.g. scheduling of test suites
• CPC Class Codes: G06F 11/3692 for test results analysis
• CPC Class Codes: G06F 11/3696 Methods or tools to render software testable

Abstract

A system for automated mobile application testing and activity monitoring where the mobile app runs on one of a plurality of available mobile devices running an operating system supported by the testing system. The automated testing system intelligently exercises each user interface element on each screen of the test mobile app for expected function, creating a graphical map of screen relationship and links in the process. Summary reports on user interface element function, mobile app usability and programming remediation hints on detailed pages may be displayed or sent to a client'"'"'s software engineer task tracking package.

Claims

1. A system for automated intelligent mobile application testing comprising:

a mobile application testing module stored in a memory of and operating on a processor of a computing device and configured to;

receive a mobile application for testing from an external source;

communicate with a mobile device via a plurality of standard application programming interfaces;

direct an operating system of the mobile device to install the mobile application;

identify and exercise each of a plurality of user interface elements on each of a plurality of screens presented by the mobile application, analyzing contextual clues present in the plurality of user interface elements to predict correct behavior of that element while simulating human interaction with those elements;

create a relationship representation of a plurality of screens presented by the mobile application;

identify any deviation in behavior of any user interface elements tested from predictively expected behavior for that element;

communicate with an issue tracking system; and

a test results output module stored in a memory of and operating on a processor of a computing device and configured to;

format a plurality of results received from the mobile application testing module to best accomplish a predetermined function of those results.

2. The system of claim 1, wherein the predictive analysis is based at least in part on a plurality of previously-learned behavioral expectations.

3. The system of claim 1, wherein the predictive analysis is based at least in part on a plurality of instructions received from the issue tracking system.

4. The system of claim 1, wherein at least one of the test result output module formats is a user interface element behavior summary report for elements of the mobile application.

5. The system of claim 1, wherein at least one of the test result output module formats is a detailed program and machine state report configured for presentation to a user for review.

6. The system of claim 1, wherein at least one of the test result output module formats is a report that provides metric derived usability scores and advice on remedy choices.

7. The system of claim 1, wherein at least one of the test result output module formats is transmitted to the issue tracking system.

8. The system of claim 1, wherein at least one relationship representation of a plurality of screens of the mobile application is in the form of a multidimensional graph.

9. A method for automated intelligent mobile application testing comprising the steps of:

a) retrieving a mobile application to be tested from an external source using a mobile application testing module stored in a memory of and operating on a processor of a computing device;

b) directing, using a plurality of application programming interfaces, the operating system of a mobile device to install and run the mobile application;

c) identifying and exercising each of a plurality of user interface elements on each of a plurality of screens presented by the mobile application, analyzing contextual clues present in the plurality of user interface elements to predict correct behavior correct behavior of that element while simulating human interaction with those elements;

d) creating a relationship representation of a plurality of screens presented by the mobile application;

e) identifying any deviation in behavior of any user interface elements tested from predictively expected behavior for that element;

f) communicating with an issue tracking system; and

g) formatting a plurality of results received from the mobile application testing module to best accomplish a predetermined function of those results using a test results output module stored in a memory of and operating on a processor of a computing device.

10. The method of claim 9, wherein the predictive analysis is based at least in part on a plurality of previously-learned behavioral expectations.

11. The method of claim 9, wherein the predictive analysis is based at least in part on a plurality of instructions received from the issue tracking system.

12. The method of claim 9, wherein at least one of the test result output module formats is a user interface element behavior summary report for elements of the mobile application.

13. The method of claim 9, wherein at least one of the test result output module formats is a detailed program and machine state report configured for presentation to a user for review.

14. The method of claim 9, wherein at least one of the test result output module formats is a report that provides metric derived usability scores and advice on remedy choices.

15. The method of claim 9, wherein at least one of the test result output module formats is transmitted to the issue tracking system.

16. The method of claim 9, wherein at least one relationship representation of a plurality of screens of the mobile application is in the form of a multidimensional graph.