利用Android应用自动随机测试中的饱和效应

Domenico Amalfitano, Nicola Amatucci, A. R. Fasolino, Porfirio Tramontana, Emily Kowalczyk, A. Memon
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引用次数: 23

摘要

猴子模糊测试(Monkey Fuzz Testing,简称MFT)是一种随机测试方法,因其简单易用而在Android应用测试中越来越受欢迎。(未经训练的)程序员使用MFT工具完全自动地检测应用程序中的某些类型的故障。这些工具面临的一个挑战是缺乏停止标准——程序员目前通常在没有时间时停止这些工具。在本文中,我们使用MFT工具在被测应用程序上的饱和效应的概念来定义一个停止准则,该准则由应用程序的先决条件和工具的配置参数化。我们已经在Android Ripper MFT工具中实现了我们的方法。我们实验报告了18个真实的Android应用对象的结果。我们表明,饱和效应能够在达到测试充分性时停止测试,而不会浪费测试周期。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Exploiting the Saturation Effect in Automatic Random Testing of Android Applications
Monkey Fuzz Testing (MFT), a form of random testing, continues to gain popularity to test Android apps because of its ease of use. (Untrained) programmers use MFT tools to fully automatically detect certain classes of faults in apps. A challenge for these tools is the lack of a stopping criterion -- programmers currently typically stop these tools when they run out of time. In this paper, we use the notion of the Saturation Effect of an MFT tool on an app under test to define a stopping criterion, parameterized by the app's preconditions and the tool's configurations. We have implemented our approach in the Android Ripper MFT tool. We experimentally report results on 18 real Android app subjects. We show that the saturation effect is able to stop testing when test adequacy has been achieved without wasting test cycles.
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