Automatically Discovering, Reporting and Reproducing Android Application Crashes

Kevin Moran, M. Vásquez, Carlos Bernal-Cárdenas, Christopher Vendome, D. Poshyvanyk
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引用次数: 160

Abstract

Mobile developers face unique challenges when detecting and reporting crashes in apps due to their prevailing GUI event-driven nature and additional sources of inputs (e.g., sensor readings). To support developers in these tasks, we introduce a novel, automated approach called CRASHSCOPE. This tool explores a given Android app using systematic input generation, according to several strategies informed by static and dynamic analyses, with the intrinsic goal of triggering crashes. When a crash is detected, CRASHSCOPE generates an augmented crash report containing screenshots, detailed crash reproduction steps, the captured exception stack trace, and a fully replayable script that automatically reproduces the crash on a target device(s). We evaluated CRASHSCOPE's effectiveness in discovering crashes as compared to five state-of-the-art Android input generation tools on 61 applications. The results demonstrate that CRASHSCOPE performs about as well as current tools for detecting crashes and provides more detailed fault information. Additionally, in a study analyzing eight real-world Android app crashes, we found that CRASHSCOPE's reports are easily readable and allow for reliable reproduction of crashes by presenting more explicit information than human written reports.
自动发现,报告和再现Android应用程序崩溃
由于GUI事件驱动的特性和额外的输入来源(如传感器读数),移动开发者在检测和报告应用崩溃时面临着独特的挑战。为了支持开发人员完成这些任务,我们引入了一种新颖的自动化方法,称为CRASHSCOPE。该工具根据静态和动态分析提供的几种策略,使用系统输入生成来探索给定的Android应用,其内在目标是触发崩溃。当检测到崩溃时,CRASHSCOPE生成一个增强的崩溃报告,其中包含屏幕截图、详细的崩溃再现步骤、捕获的异常堆栈跟踪和一个完全可重放的脚本,该脚本可自动在目标设备上再现崩溃。我们评估了CRASHSCOPE在发现崩溃方面的有效性,并将其与五种最先进的Android输入生成工具在61个应用程序上进行了比较。结果表明,CRASHSCOPE的性能与当前检测崩溃的工具一样好,并提供更详细的故障信息。此外,在一项分析八个真实Android应用程序崩溃的研究中,我们发现CRASHSCOPE的报告很容易阅读,并且通过提供比人类书面报告更明确的信息,可以可靠地再现崩溃。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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