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. Index Terms—Smoke testing, GUI testing, test oracles, empirical studies, regression testing. 1

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 reluctance in adoption of model-based solutions proposed by researchers is their limited applicability; moreover, the models are expensive to create. Over the past few years, we have been developing different models for various aspects of GUI testing. This paper consolidates all the models into one scalable eventflow 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 (ESES) and creating an end-to-end GUI testing process. Three such ESES 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 ESES for experimentation and application in GUI testing.

Several rapid-feedback-based quality assurance mechanisms are used to manage the quality of continuously evolving software. Even though graphical user interfaces (GUIs) are one of the most important parts of software, there are currently no mechanisms to quickly retest evolving GUI software. We leverage our previous work on GUI testing to define a new automatic GUI re-testing process called “crash testing ” that is integrated with GUI evolution. We describe two levels of crash testing: (1) immediate feedback-based in which a developer indicates that a GUI bug was fixed in response to a previously reported crash; only select crash test cases are rerun and the developer is notified of the results in a matter of seconds, and (2) between code changes in which new crash test cases are generated on-the-fly and executed on the GUI. Since the code may be changed by another developer before all the crash tests have been executed, hence requiring restarting of the process, we use a simple rotation-based scheme to ensure that all crash tests are executed over a series of code changes. We show, via empirical studies, that our crash tests are effective at revealing serious problems in the GUI. 1

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