AI Software Testing System and Method
AssigneeAppdiff, Inc.
InventorsJason Joseph Arbon, Justin Mingjay Liu, Christopher Randall Navrides
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Abstract
A system for performing software testing uses machine learning to extract features from a user interface of an app, classify screen types and screen elements of the user interface, and implement flows of test sequences to test the app. Training is performed to train the system to learn common application states of an application graph and to navigate through an application. In some implementations, the training includes Q-learning to learn how to navigate to a selected screen state. In some implementations, there is reuse of classifiers cross-application and cross platform.
Claims30
An artificial intelligence software testing system to test software applications having a sequence of screens with each screen having a set of screen elements, comprising:
- a set of intelligent machine learning bots trained to:
- crawl through a software application;
- identify screen types and screen elements of the screens using a set of trained classifiers;
- and
- apply test cases to the software application.
A computer-implemented method to test software applications having a sequence of screens with each screen having a set of screen elements, using a set of intelligent machine learning bots trained to perform a method comprising:
- crawling through a software application;
- identifying screen types and screen elements of the screens using a set of trained classifiers;
- and
- applying test cases to the software application.
Dependencies are inferred from the claim text.