Towards Dynamic Adaptive Automated Test Generation for Graphical User Interfaces

Abstract

Graphical user interfaces (GUIs) present an enormous number of potential event sequences to users. During testing it is necessary to cover this space, however the complexity of modern GUIs has made this an increasingly difficult task. Our past work has demonstrated that it is important to incorporate "context'' into GUI test cases, in terms of event combinations, event sequence length, and by considering all possible starting and ending positions for each event. Despite the use of our most refined modeling techniques, many of the generated test cases remain unexecutable. In this paper, we posit that due to the dynamic state-based nature of GUIs, it is important to incorporate feedback from the execution of tests into test case generation algorithms. We propose the use of an evolutionary algorithm to generate test suites with fewer unexecutable test cases and higher event interaction coverage.