Sauce Labs Inc.

Bradley Scott Adelberg

Christian Bromann

Yaroslav Borets

Yeh Fang

Fernando Vidal

Benjamin H Ellis

Jean Sandberg

Robert Henrikson

Methods and apparatus are described by which a rich, time-correlated information set is captured during automated testing of an application in a way that allows the application developer to understand the state of the application under test (AUT), the browser interacting with the AUT, and/or the device interacting with the AUT, as it/they changed over time. Mechanisms or features associated with browsers and/or device operating systems are exploited to capture such information, not only for the purpose of better understanding individual test runs, but also to enable the use of analytics over data sets.

Automated application testing system

Machine learning techniques are employed to model test runs of an automated test platform in ways that allow for reliable identification of various types of test behavior such as, for example, whether certain classes of failures can be characterized as test flake.

Analytics for an automated application testing platform

Methods and apparatus are described by which artificial intelligence (AI) is used to enable the rapid development of reliable test suites for web and mobile applications. An AI agent guided by reinforcement learning explores an application-under-test (AUT), interacting with the AUT to traverse the flows through the AUT by seeking novel application states. A subset of these flows is then identified as being representative of the functionality of the AUT. The interactions between the AI agent and the AUT that define these identified flows form the basis for the test suite.

Authoring automated test suites using artificial intelligence

Growing community of inventors

Portola Valley, CA, United States of America

Bradley Scott Adelberg