Graphical user interfaces (GUIs) are important parts of today's software and their correct execution is required to ensure the correctness of the overall software. A popular technique to detect defects in GUIs is to test them by executing test cases and checking the execution results. Test cases may either be created manually or generated automatically from a model of the GUI. While manual testing is unacceptably slow for many applications, our experience with GUI testing has shown that creating a model that can be used for automated test case generation is difficult.We describe a new approach to reverse engineer a model represented as structures called a GUI forest, event-flow graphs and an integration tree directly from the executable GUI. We describe "GUI Ripping", a dynamic process in which the software's GUI is automatically "traversed" by opening all its windows and extracting all their widgets (GUI objects), properties, and values. The extracted information is then verified by the test designer and used to automatically generate test cases. We present algorithms for the ripping process and describe their implementation in a tool suite that operates on Java and Microsoft Windows' GUIs.We present results of case studies which show that our approach requires very little human intervention and is especially useful for regression testing of software that is modified frequently. We have successfully used the "GUI Ripper" in several large experiments and have made it available as a downloadable tool.

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Abstract-GUI testing is an active research area. The open challenge is the judicious generation of event sequences(an event sequence encodes a user interaction). A major advance in this direction is the use of a black-box model to systematically generate event sequences that are executable on the GUI. The black-box model can be, e.g., an Event Flow Graph (EFG) or an Event Sequence Graph (ESG). In this paper we propose a new approach to select relevant event sequences among the event sequences generated by a blackbox model. We express the relevance of an event sequence by a precisely defined dependency between a fixed number of events in the event sequence. Departing from a pure blackbox approach we apply a static analysis to the bytecode of the application. This allows us to infer a dependency graph, which we call Event Dependency Graph (EDG). We use the EDG together with a black-box model to construct a set of relevant event sequences among the executable ones. We have implemented our approach in a new tool. We evaluate the approach on four open source GUI applications. With the specific choice of a lightweight static analysis, the approach scales to large applications and, at the same time, leads to an informed selection of event sequences. Using our approach we are able to find previously undetected bugs.