Exploring the integration of user feedback in automated testing of Android applications

Giovanni Grano, Adelina Ciurumelea, Sebastiano Panichella, Fabio Palomba, H. Gall
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引用次数: 53

Abstract

The intense competition characterizing mobile application's marketplaces forces developers to create and maintain high-quality mobile apps in order to ensure their commercial success and acquire new users. This motivated the research community to propose solutions that automate the testing process of mobile apps. However, the main problem of current testing tools is that they generate redundant and random inputs that are insufficient to properly simulate the human behavior, thus leaving feature and crash bugs undetected until they are encountered by users. To cope with this problem, we conjecture that information available in user reviews—that previous work showed as effective for maintenance and evolution problems—can be successfully exploited to identify the main issues users experience while using mobile applications, e.g., GUI problems and crashes. In this paper we provide initial insights into this direction, investigating (i) what type of user feedback can be actually exploited for testing purposes, (ii) how complementary user feedback and automated testing tools are, when detecting crash bugs or errors and (iii) whether an automated system able to monitor crash-related information reported in user feedback is sufficiently accurate. Results of our study, involving 11,296 reviews of 8 mobile applications, show that user feedback can be exploited to provide contextual details about errors or exceptions detected by automated testing tools. Moreover, they also help detecting bugs that would remain uncovered when rely on testing tools only. Finally, the accuracy of the proposed automated monitoring system demonstrates the feasibility of our vision, i.e., integrate user feedback into testing process.
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探索在Android应用程序的自动化测试中集成用户反馈
手机应用市场的激烈竞争迫使开发者创造并维护高质量的手机应用,以确保其商业成功并获得新用户。这促使研究团体提出解决方案,使移动应用程序的测试过程自动化。然而,当前测试工具的主要问题是,它们生成的冗余和随机输入不足以正确模拟人类行为,因此,直到用户遇到功能和崩溃错误时才会发现它们。为了解决这个问题,我们推测用户评论中可用的信息——以前的工作表明对维护和发展问题有效——可以成功地利用来识别用户在使用移动应用程序时遇到的主要问题,例如GUI问题和崩溃。在本文中,我们提供了对这个方向的初步见解,调查了(i)哪种类型的用户反馈实际上可以用于测试目的,(ii)在检测崩溃错误或错误时,用户反馈和自动化测试工具是如何互补的,以及(iii)能够监控用户反馈中报告的崩溃相关信息的自动化系统是否足够准确。我们对8款手机应用的11,296条评论进行了研究,结果表明用户反馈可以用来提供自动化测试工具检测到的错误或异常的上下文细节。此外,它们还有助于检测仅依赖测试工具时无法发现的错误。最后,所提出的自动监控系统的准确性证明了我们设想的可行性,即将用户反馈集成到测试过程中。
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