Automated Feature Identification for Android Apps

Gian Luca Scoccia

Abstract: Mobile apps are becoming increasingly complex, as nowadays a growing amount of apps no longer focuses on being a “specialized utility” but acts as an “all-around” app that offers assorted features (e.g., news feed, messaging, weather, map, and navigation, etc.). In this paper, we argue that being able to automatically and precisely identify the features offered by an app would allow researchers to investigate new technical solutions, that in turn would benefit both end-users, developers and, researchers. As a stepping stone in this direction, we describe an automated technique to identify features within Android apps. Our approach performs the identification of the features by extracting information from the app user interface and grouping together semantically similar concepts thanks to knowledge-base aided natural text processing and machine learning.