We present AndroidRipper, an automated technique that tests Android apps via their Graphical User Interface (GUI).AndroidRipper is based on a user-interface driven ripper that automatically explores the app's GUI with the aim of exercising the application in a structured manner. We evaluate AndroidRipper on an open-source Android app. Our results show that our GUI-based test cases are able to detect severe, previously unknown, faults in the underlying code, and the structured exploration outperforms a random approach.

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.

As mobile devices become increasingly smarter and more powerful, so too must the engineering of their software. User-interface-driven system testing of these devices is gaining popularity, with each vendor releasing some automation tool. However, these tools are inappropriate for amateur programmers, an increasing portion of app developers. MobiGUITAR (Mobile GUI Testing Framework) provides automated GUI-driven testing of Android apps. It's based on observation, extraction, and abstraction of GUI widgets' run-time state. The abstraction is a scalable state machine model that, together with test coverage criteria, provides a way to automatically generate test cases. When applied to four open-source Android apps, MobiGUITAR automatically generated and executed 7,711 test cases and reported 10 new bugs. Some bugs were Android-specific, stemming from the event- and activity-driven nature of Android

Graphical user interfaces (GUIs) are by far the most popular means used to interact with today's software. The functional correctness of a GUI is required to ensure the safety, robustness and usability of an entire software system. GUI testing techniques used in practice are resource intensive; model‐based automated techniques are rarely employed. A key reason for the reluctance in the adoption of model‐based solutions proposed by researchers is their limited applicability; moreover, the models are expensive to create. Over the past few years, the present author has been developing different models for various aspects of GUI testing. This paper consolidates all of the models into one scalable event‐flow model and outlines algorithms to semi‐automatically reverse‐engineer the model from an implementation. Earlier work on model‐based test‐case generation, test‐oracle creation, coverage evaluation, and regression testing is recast in terms of this model by defining event‐space exploration strategies (ESESs) and creating an end‐to‐end GUI testing process. Three such ESESs are described: for checking the event‐flow model, test‐case generation, and test‐oracle creation. Two demonstrational scenarios show the application of the model and the three ESESs for experimentation and application in GUI testing. Copyright © 2007 John Wiley & Sons, Ltd.

Abstract-Software is increasingly being developed/maintained by multiple, often geographically distributed developers working concurrently. Consequently, rapid-feedback-based quality assurance mechanisms such as daily builds and smoke regression tests, which help to detect and eliminate defects early during software development and maintenance, have become important. This paper addresses a major weakness of current smoke regression testing techniques, i.e., their inability to automatically (re)test graphical user interfaces (GUIs). Several contributions are made to the area of GUI smoke testing. First, the requirements for GUI smoke testing are identified and a GUI smoke test is formally defined as a specialized sequence of events. Second, a GUI smoke regression testing process called Daily Automated Regression Tester (DART) that automates GUI smoke testing is presented. Third, the interplay between several characteristics of GUI smoke test suites including their size, fault detection ability, and test oracles is empirically studied. The results show that: 1) the entire smoke testing process is feasible in terms of execution time, storage space, and manual effort, 2) smoke tests cannot cover certain parts of the application code, 3) having comprehensive test oracles may make up for not having long smoke test cases, and 4) using certain oracles can make up for not having large smoke test suites.