Iterative execution-feedback model-directed GUI testing

Yuan, Xun; Memon, Atif M.

doi:10.1016/j.infsof.2009.11.009

Cited by 34 publications

(19 citation statements)

References 28 publications

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“…As, even for small programs, the number of test cases, which can be generated from an EIG (or EFG) tends to become large, the combination of models that capture possible user interactions and those that help to identify relevant sequences of user interactions (e.g., ESIG) is extremely important. The importance of these combined models is also visibly stated in recent research, e.g., in [57,55,10].…”

Section: Discussionmentioning

confidence: 84%

Trends in Model-based GUI Testing

Arlt

Bertolini²,

Pahl

et al. 2012

Advances in Computers

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This chapter gives an overview of the recent advances in GUI testing. Considering the increasing popularity and fast software development cycles (e.g., desktop and mobile applications), GUI testing gains more importance as it allows us to verify the behavior of a system from the user's perspective. Thus, it can quickly uncover relevant bugs, which a user could face.Traditional capture-replay GUI testing approaches do not meet the demands of developers anymore. Therefore, there is an increasing research activity in modelbased GUI testing, where the user interaction behavior is simulated using a graphbased model. In the following, we outline different graphical notations to describe feasible user interactions, and methods to generate and execute test cases from these models. We discuss the benefits and limitations of the state-of-the-art in GUI testing research and give a brief outlook about new trends and possibilities to improve the GUI testing automation.

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Section: Discussionmentioning

confidence: 84%

Trends in Model-based GUI Testing

Arlt

Bertolini²,

Pahl

et al. 2012

Advances in Computers

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“…This approach differs from our work in two ways: (a) in our work, model creation and testing forms a feedback loop, (b) we use ELTS, a more richer model than Event Flow Graph (EFG). Yuan and Memon [47] also investigated a way to reflect runtime information on top of EFG model to guide testing.…”

Section: Related Workmentioning

confidence: 99%

Guided GUI testing of android apps with minimal restart and approximate learning

ChoiWontae¹,

NeculaGeorge²,

SenKoushik³

2013

SIGPLAN Not.

169

127

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Smartphones and tablets with rich graphical user interfaces (GUI) are becoming increasingly popular. Hundreds of thousands of specialized applications, called apps, are available for such mobile platforms. Manual testing is the most popular technique for testing graphical user interfaces of such apps. Manual testing is often tedious and error-prone. In this paper, we propose an automated technique, called SwiftHand, for generating sequences of test inputs for Android apps. The technique uses machine learning to learn a model of the app during testing, uses the learned model to generate user inputs that visit unexplored states of the app, and uses the execution of the app on the generated inputs to refine the model. A key feature of the testing algorithm is that it avoids restarting the app, which is a significantly more expensive operation than executing the app on a sequence of inputs. An important insight behind our testing algorithm is that we do not need to learn a precise model of an app, which is often computationally intensive, if our goal is to simply guide test execution into unexplored parts of the state space. We have implemented our testing algorithm in a publicly available tool for Android apps written in Java. Our experimental results show that we can achieve significantly better coverage than traditional random testing and L * -based testing in a given time budget. Our algorithm also reaches peak coverage faster than both random and L * -based testing.

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“…Memon has described an approach to automated testing of GUI applications that consist of hierarchically organized modal dialogs [16]. In later work, Memon and Yuan employed execution feedback to enhance coverage by taking interactions between event handlers into account and refining test cases iteratively in batches [25,26]. Although the underlying structure of the GUI application code is different compared to JavaScript applications, it may be possible to adapt their notion of event semantic interactions into our general framework, which we will explore in future work.…”

Section: Related Workmentioning

confidence: 99%

A framework for automated testing of javascript web applications

Artzi

Dolby

Jensen

et al. 2011

Proceedings of the 33rd International Conference on Software Engineering

168

166

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Current practice in testing JavaScript web applications requires manual construction of test cases, which is difficult and tedious. We present a framework for feedback-directed automated test generation for JavaScript in which execution is monitored to collect information that directs the test generator towards inputs that yield increased coverage. We implemented several instantiations of the framework, corresponding to variations on feedback-directed random testing, in a tool called Artemis. Experiments on a suite of JavaScript applications demonstrate that a simple instantiation of the framework that uses event handler registrations as feedback information produces surprisingly good coverage if enough tests are generated. By also using coverage information and read-write sets as feedback information, a slightly better level of coverage can be achieved, and sometimes with many fewer tests. The generated tests can be used for detecting HTML validity problems and other programming errors.

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Iterative execution-feedback model-directed GUI testing

Cited by 34 publications

References 28 publications

Trends in Model-based GUI Testing

Trends in Model-based GUI Testing

Guided GUI testing of android apps with minimal restart and approximate learning

A framework for automated testing of javascript web applications

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