A Recommender System of Buggy App Checkers ...
Document type :
Communication dans un congrès avec actes
Title :
A Recommender System of Buggy App Checkers for App Store Moderators
Author(s) :
Gomez, Maria [Auteur]
Self-adaptation for distributed services and large software systems [SPIRALS]
Rouvoy, Romain [Auteur]
Self-adaptation for distributed services and large software systems [SPIRALS]
Monperrus, Martin [Auteur]
Self-adaptation for distributed services and large software systems [SPIRALS]
Seinturier, Lionel [Auteur]
Self-adaptation for distributed services and large software systems [SPIRALS]
Institut universitaire de France [IUF]
Self-adaptation for distributed services and large software systems [SPIRALS]
Rouvoy, Romain [Auteur]

Self-adaptation for distributed services and large software systems [SPIRALS]
Monperrus, Martin [Auteur]
Self-adaptation for distributed services and large software systems [SPIRALS]
Seinturier, Lionel [Auteur]

Self-adaptation for distributed services and large software systems [SPIRALS]
Institut universitaire de France [IUF]
Scientific editor(s) :
Danny Dig and Yael Dubinsky
Conference title :
2nd ACM International Conference on Mobile Software Engineering and Systems
City :
Firenze
Country :
Italie
Start date of the conference :
2015-05-16
Publisher :
IEEE
English keyword(s) :
Android App Bugs
App Checkers
Android Permissions
Online reviews
App Checkers
Android Permissions
Online reviews
HAL domain(s) :
Informatique [cs]/Génie logiciel [cs.SE]
English abstract : [en]
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 ...
Show more >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.Show less >
Show more >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.Show less >
Language :
Anglais
Peer reviewed article :
Oui
Audience :
Internationale
Popular science :
Non
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