Android的自动化测试输入生成:我们做到了吗?(E)

Shauvik Roy Choudhary, Alessandra Gorla, A. Orso
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引用次数: 441

摘要

像所有软件一样,移动应用程序(“应用程序”)必须经过充分的测试,以获得对其正确运行的信心。因此,近年来,研究人员和实践者都开始研究自动化应用程序测试的方法。特别是,由于Android的开源特性及其巨大的市场份额,对于运行在Android操作系统上的应用程序的输入生成技术已经进行了大量的研究。在这个时间点上,实际上在文献中有许多这样的技术,它们在生成输入的方式,它们用于探索被测应用行为的策略以及它们使用的特定启发式方面有所不同。为了更好地理解这些现有方法的优势和弱点,并获得更有效的方法,我们在本文中对Android上现有的主要测试输入生成工具进行了全面的比较。在我们的比较中,我们根据四个指标来评估这些工具的有效性,以及它们相应的技术:易用性、在多个平台上工作的能力、代码覆盖率和检测故障的能力。我们的研究结果为Android应用的输入生成提供了一幅清晰的画面,并确定了未来的研究方向,如果进行适当的调查,可能会为Android带来更有效和高效的测试工具。
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Automated Test Input Generation for Android: Are We There Yet? (E)
Like all software, mobile applications ("apps") must be adequately tested to gain confidence that they behave correctly. Therefore, in recent years, researchers and practitioners alike have begun to investigate ways to automate apps testing. In particular, because of Android's open source nature and its large share of the market, a great deal of research has been performed on input generation techniques for apps that run on the Android operating systems. At this point in time, there are in fact a number of such techniques in the literature, which differ in the way they generate inputs, the strategy they use to explore the behavior of the app under test, and the specific heuristics they use. To better understand the strengths and weaknesses of these existing approaches, and get general insight on ways they could be made more effective, in this paper we perform a thorough comparison of the main existing test input generation tools for Android. In our comparison, we evaluate the effectiveness of these tools, and their corresponding techniques, according to four metrics: ease of use, ability to work on multiple platforms, code coverage, and ability to detect faults. Our results provide a clear picture of the state of the art in input generation for Android apps and identify future research directions that, if suitably investigated, could lead to more effective and efficient testing tools for Android.
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