SetDroid:通过变形模糊检测Android应用程序的用户可配置设置问题

Jingling Sun
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引用次数: 2

摘要

最流行的移动系统Android提供了许多独立于应用程序、用户可配置的设置(例如,网络、位置和权限)来控制设备和应用程序。然而,当这些设置被改变时,应用程序可能无法适当地适应它们的行为,从而让用户感到沮丧。我们将这种问题称为设置问题,它存在于应用程序中,是由设置的变化引起的。根据我们的调查,大多数设置问题都是非崩溃(逻辑)错误,但是由于缺乏测试oracle,现有的自动化应用测试技术无法检测到这些问题。为此,我们设计并引入了基于设置的变形模糊测试,这是第一个自动化测试技术,用于克服检测设置问题的oracle问题。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,应用程序的行为应该保持一致,然后适当地恢复。我们将此技术作为自动化GUI测试工具SetDroid实现,并将其应用于26个流行的开源Android应用程序。SetDroid成功地在这些应用程序中发现了32个独特的,以前未知的设置问题。到目前为止,已经确认了25个,已经修复了17个。我们进一步将SetDroid应用于4个月活跃用户达数十亿的商业应用,并成功检测到15个之前未知的设置问题,所有这些问题都已得到确认并正在修复。所有这些错误中的大多数(47个中的37个)都是非崩溃错误,无法通过任何先前的测试技术检测到。
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SetDroid: Detecting User-Configurable Setting Issues of Android Apps via Metamorphic Fuzzing
Android, the most popular mobile system, offers a number of app-independent, user-configurable settings (e.g., network, location and permission) for controlling the devices and the apps. However, apps may fail to properly adapt their behaviors when these settings are changed, and thus frustrate users. We name such issues as setting issues, which reside in the apps and are induced by the changes of settings. According to our investigation, the majority of setting issues are non-crash (logic) bugs, which however cannot be detected by existing automated app testing techniques due to the lack of test oracles. To this end, we designed and introduced, setting-wise metamorphic fuzzing, the first automated testing technique to overcome the oracle problem in detecting setting issues. Our key insight is that, in most cases, the app behaviors should keep consistent if a given setting is changed and later properly restored. We realized this technique as an automated GUI testing tool, SetDroid, and applied it on 26 popular, open-source Android apps. SetDroid successfully found 32 unique, previously-unknown setting issues in these apps. So far, 25 have been confirmed and 17 were already fixed. We further applied SetDroid on 4 commercial apps with billions of monthly active users and successfully detected 15 previously unknown setting issues, all of which have been confirmed and under fixing. The majority of all these bugs (37 out of 47) are non-crash bugs, which cannot be detected by any prior testing technique.
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