Session-Based Recommender Systems for Action Selection in GUI Test Generation
Feb. 7th, 2020
Test generation at the graphical user interface (GUI) level has proven to be an effective method to reveal faults. When doing so, a test generator has to repeatably decide what action to execute given the current state of the system under test (SUT). This problem of action selection usually involves random choice, which is often referred to as monkey testing. Some approaches leverage other techniques to improve the overall effectiveness, but only a few try to create human-like actions—or even entire action sequences.