理解并发现Android应用中与系统设置相关的缺陷

Jingling Sun, Ting Su, Junxin Li, Zhen Dong, G. Pu, Tao Xie, Z. Su
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引用次数: 23

摘要

Android,最流行的移动系统,提供了许多用户可配置的系统设置(例如,网络,位置和权限)来控制设备和应用程序。即使是受欢迎的、经过良好测试的应用程序也可能无法适当地调整其行为以适应各种设置变化,从而使用户感到沮丧。然而,目前还没有对这些缺陷进行系统的研究。为此,我们进行了第一次实证研究,以了解这些与设置相关的缺陷(简称“设置缺陷”)的特征,这些缺陷存在于应用程序中,并由系统设置更改触发。我们投入了大量的人工工作(超过三个人月)来分析GitHub上180个流行应用程序的1,074个设置缺陷。我们调查它们的影响、根本原因和后果。我们发现,设置缺陷对应用程序的正确性有广泛而多样的影响,其中大多数缺陷(≈70.7%)会导致非崩溃(逻辑)故障,由于缺乏强大的测试oracle,现有的应用程序测试技术无法自动检测到这些缺陷。在我们的研究的激励和指导下,我们提出了设置智能的变形模糊,这是第一个自动化的测试方法,可以有效地检测设置缺陷,而不需要明确的指示。我们的关键观点是,在大多数情况下,如果一个给定的设置被改变,然后适当地恢复,应用程序的行为应该保持一致,或者如果没有恢复,表现出预期的差异。我们在SetDroid中实现了我们的方法,这是一个自动化的端到端GUI测试工具,用于检测崩溃和非崩溃设置缺陷。SetDroid已经对26个流行的开源应用程序进行了评估,并在24个应用程序中发现了42个独特的、以前未知的设置缺陷。到目前为止,已经确认了33个,确定了21个。我们还将SetDroid应用于五个非常受欢迎的工业应用程序,即微信、QQMail、抖音、CapCut和支付宝,每个应用程序都有数十亿的月活跃用户。SetDroid在这些应用的最新版本中成功检测到17个以前未知的设置缺陷,并且所有缺陷都已被应用供应商确认并修复。大多数setdroid检测到的缺陷(59个中的49个)会导致非崩溃故障,这是现有测试工具无法检测到的(正如我们的评估所证实的)。这些结果证明了SetDroid具有很强的有效性和实用性。
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Understanding and finding system setting-related defects in Android apps
Android, the most popular mobile system, offers a number of user-configurable system settings (e.g., network, location, and permission) for controlling devices and apps. Even popular, well-tested apps may fail to properly adapt their behaviors to diverse setting changes, thus frustrating their users. However, there exists no effort to systematically investigate such defects. To this end, we conduct the first empirical study to understand the characteristics of these setting-related defects (in short as "setting defects"), which reside in apps and are triggered by system setting changes. We devote substantial manual effort (over three person-months) to analyze 1,074 setting defects from 180 popular apps on GitHub. We investigate their impact, root causes, and consequences. We find that setting defects have a wide, diverse impact on apps' correctness, and the majority of these defects (≈70.7%) cause non-crash (logic) failures, and thus could not be automatically detected by existing app testing techniques due to the lack of strong test oracles. Motivated and guided by our study, we propose setting-wise metamorphic fuzzing, the first automated testing approach to effectively detect setting defects without explicit oracles. Our key insight is that an app's behavior should, in most cases, remain consistent if a given setting is changed and later properly restored, or exhibit expected differences if not restored. We realize our approach in SetDroid, an automated, end-to-end GUI testing tool, for detecting both crash and non-crash setting defects. SetDroid has been evaluated on 26 popular, open-source apps and detected 42 unique, previously unknown setting defects in 24 apps. To date, 33 have been confirmed and 21 fixed. We also apply SetDroid on five highly popular industrial apps, namely WeChat, QQMail, TikTok, CapCut, and AlipayHK, all of which each have billions of monthly active users. SetDroid successfully detects 17 previously unknown setting defects in these apps' latest releases, and all defects have been confirmed and fixed by the app vendors. The majority of SetDroid-detected defects (49 out of 59) cause non-crash failures, which could not be detected by existing testing tools (as our evaluation confirms). These results demonstrate SetDroid's strong effectiveness and practicality.
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