A Recommender System of Buggy App Checkers for App Store Moderators

Maria Gomez 1 Romain Rouvoy 1 Martin Monperrus 1 Lionel Seinturier 2, 1
1 SPIRALS - Self-adaptation for distributed services and large software systems
Inria Lille - Nord Europe, CRIStAL - Centre de Recherche en Informatique, Signal et Automatique de Lille (CRIStAL) - UMR 9189
Abstract : The popularity of smartphones is leading to an ever growing number of mobile apps that are published in official app stores. However, users might experience bugs and crashes for some of these apps. In this paper, we perform an empirical study of the official Google Play Store to automatically mine for such error-suspicious apps. We use the knowledge inferred from this analysis to build a recommender system of buggy app checkers. More specifically, we analyze the permissions and the user reviews of 46,644 apps to identify potential correlations between error-sensitive permissions and error-related reviews along time. This study reveals error-sensitive permissions and patterns that potentially induce the errors reported online by users. As a result, our systems give app store moderators efficient static checkers to predict buggy apps before they harm the reputation of the app store as a whole.
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Maria Gomez, Romain Rouvoy, Martin Monperrus, Lionel Seinturier. A Recommender System of Buggy App Checkers for App Store Moderators. 2nd ACM International Conference on Mobile Software Engineering and Systems, May 2015, Firenze, Italy. ⟨10.1109/MobileSoft.2015.8⟩. ⟨hal-01117376⟩

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