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Automated cross-platform inconsistency detection for mobile apps

机译:自动化的跨平台不一致性移动应用程序检测

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Testing of Android apps is particularly challenging due to the fragmentation of the Android ecosystem in terms of both devices and operating system versions. Developers must in fact ensure not only that their apps behave as expected, but also that the apps' behavior is consistent across platforms. To support this task, we propose DiffDroid, a new technique that helps developers automatically find cross-platform inconsistencies (CPIs) in mobile apps. DiffDroid combines input generation and differential testing to compare the behavior of an app on different platforms and identify possible inconsistencies. Given an app, DiffDroid (1) generates test inputs for the app, (2) runs the app with these inputs on a reference device and builds a model of the app behavior, (3) runs the app with the same inputs on a set of other devices, and (4) compares the behavior of the app on these different devices with the model of its behavior on the reference device. We implemented DiFFDRoiD and performed an evaluation of our approach on 5 benchmarks and over 130 platforms. our results show that DiFFDRoiD can identify CPis on real apps efficiently and with a limited number of false positives. DiFFDRoiD and our experimental infrastructure are publicly available.
机译:由于Android生态系统在设备和操作系统版本方面的支离破碎,因此对Android应用程序的测试尤其具有挑战性。实际上,开发人员不仅必须确保其应用程序的行为符合预期,而且还必须确保应用程序的行为在各个平台之间保持一致。为了支持此任务,我们提出了DiffDroid,这是一种新技术,可帮助开发人员在移动应用程序中自动查找跨平台不一致(CPI)。 DiffDroid结合了输入生成和差异测试,以比较应用程序在不同平台上的行为并确定可能的不一致之处。给定一个应用程序,DiffDroid(1)为该应用程序生成测试输入,(2)使用这些输入在参考设备上运行该应用程序,并构建该应用程序行为的模型,(3)使用一组相同的输入运行该应用程序(4)将应用在这些不同设备上的行为与其在参考设备上的行为模型进行比较。我们实施了DiFFDRoiD,并在5个基准和130多个平台上对我们的方法进行了评估。我们的结果表明,DiFFDRoiD可以有效地识别误报,并且可以有效识别真实应用上的CPis。 DiFFDRoiD和我们的实验性基础结构是公开可用的。

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