Fast Witness Generation for Readable GUI Test Scenarios via Generalized Experience Replay

Abstract

Verifying the functional behavior of graphical user interface (GUI) applications is essential for reducing post-release issues. In practice, a developer/tester performs this verification by executing a sequence of GUI actions and then witnessing the expected behavior on the GUI screen. An automated witness generator facilitates the verification process. However, creating an unambiguous and monitorable specification for the correct behavior and then generating the correct GUI actions to trigger that behavior is challenging. In this study, we propose FARLEAD2, an automated witness generator that uses unambiguous, monitorable, and easy-to-read staged test scenarios (STSs) to specify expected behavior. FARLEAD2 maximizes its effectiveness and performance using generalized experienced replay (GER) to exploit the experience gathered from previously witnessed scenarios on new, unwitnessed test scenarios. To the best of our knowledge, STS and GER are novel improvements to GUI testing. Our evaluation of Android GUI applications shows that FARLEAD2 effectively generates a witness 95.7 times out of 100 and does it in 520 seconds, on average, indicating that FARLEAD2 is approximately 65 percent faster and 6.3 percent more effective than its best predecessor.

Keywords

• Experience replay
• functional testing
• GUI testing
• reinforcement learning