ADGE: Automated Directed GUI Explorer for Android Applications

With the continuous growth in the number of Android applications and the size of their codebases, it has become increasingly difficult for testers to manually analyze and trigger the functionalities of interest in each application. For instance, it is hard to trigger vulnerability points reported by scanners or reproduce captured crash scenarios. On the other hand, most existing automated exploration techniques exhibit slow performance when triggering specified targets due to the extensive exploration of different paths. Target-directed techniques can effectively address this issue but are relatively underexplored in existing research. The only target-directed exploration tool, GOALEXPLORER, is constrained by the limitations in the precision of its static analysis, which negatively impacts both exploration efficiency and effectiveness. To boost the efficiency of target-directed exploration, we propose an automated GUI testing method guided by target functions called Automated Directed GUI Explorer (ADGE). Specifically, ADGE first generates a tainted Inter-procedural Control Flow Graph with the GUI widgets by modeling the role of GUI widgets in the control flow as well as their relationship with the target using static analysis. In the dynamic exploration phase, ADGE constructs the real-time model of the fragments and menus on the current screen to guide its exploration decisions with the knowledge of static model. To validate the effectiveness of ADGE, we conduct extensive comparisons of ADGE with the state-of-the-art baseline GOALEXPLORER on 55 benchmark applications. The results demonstrate that ADGE reduced the average time to trigger targets by 44% compared to GOALEXPLORER, while also successfully triggering more than 5.24% targets. Furthermore, during the testing process, ADGE successfully triggered 5 crash events.