Collaborative bug finding for Android apps
Shin Hwei Tan, Ziqiang Li
Abstract
Many automated test generation techniques have been proposed for finding crashes in Android apps. Despite recent advancement in these approaches, a study shows that Android app developers prefer reading test cases written in natural language. Meanwhile, there exist redundancies in bug reports (written in natural language) across different apps that have not been previously reused. We propose collaborative bug finding, a novel approach that uses bugs in other similar apps to discover bugs in the app under test. We design three settings with varying degrees of interactions between programmers: (1) bugs from programmers who develop a different app, (2) bugs from manually searching for bug reports in GitHub repositories, (3) bugs from a bug recommendation system, Bugine. Our studies of the first two settings in a software testing course show that collaborative bug finding helps students who are novice Android app testers to discover 17 new bugs. As students admit that searching for relevant bug reports could be time-consuming, we introduce Bugine, an approach that automatically recommends relevant GitHub issues for a given app. Bugine uses (1) natural language processing to find GitHub issues that mention common UI components shared between the app under test and other apps in our database, and (2) a ranking algorithm to select GitHub issues that are of the best quality. Our results show that Bugine is able to find 34 new bugs. In total, collaborative bug finding helps us find 51 new bugs, in which eight have been confirmed and 11 have been fixed by the developers. These results confirm our intuition that our proposed technique is useful in discovering new bugs for Android apps. CCS CONCEPTS • Software and its engineering → Software libraries and repositories; Software maintenance tools.
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