Using methods & measures from network analysis for gui testing

Graphical user interfaces (GUIs) for today's applications are extremely large. Moreover, they provide many degrees of freedom to the end-user, thus allowing the user to perform a very large number of event sequences on the GUI. The large sizes and degrees of freedom create severe problems for GUI quality assurance, including GUI testing. In this paper, we leverage methods and measures from network analysis to analyze and study GUIs, with the goal of aiding GUI testing activities. We apply these methods and measures on the event-flow graph model of GUIs. Results of a case study show that "network centrality measures" are able to identify the most important events in the GUI as well as the most important sequences of events. These events and sequences are good candidates for test prioritization. In addition, the "betweenness clustering" method is able to partition the GUI into regions that can be tested separately.