Automated GUI Test Coverage Analysis Using GA

A Graphical User Interface (GUI) is a graphical front-end to a software system. A GUI contains graphical objects with certain distinct values which can be used to determine the state of the GUI at any time. Software developing organizations always desire to test the software thoroughly to get maximum confidence about its quality. But this requires gigantic effort to test a GUI application due to the complexity involved in such applications. This problem has led to the automation of GUI testing and different techniques have been proposed for automated GUI Testing. Event-flow graph is a fresh technique being used in the field of automated GUI testing. Just as control-flow graph, another GUI model that represents all possible execution paths in a program, event-flow model, in the same way, represents all promising progressions of events that can be executed on the GUI. Another challenging question in software testing is, “How much testing is enough?” As development proceeds, there are fewer measures available that can be used to provide guidance on the quality of an automatic test suite. Genetic algorithm searches for the best possible test parameter combinations that are according to some predefined test criterion. Usually this test criterion corresponds to a “coverage function” that measures how much of the automatically generated optimization parameters satisfies the given test criterion. In this paper, we have attempted to exploit the event driven nature of GUI. Based on this nature, we have presented a GUI testing and coverage analysis technique centered on genetic algorithms.