Testing Android Apps via Guided Gesture Event Generation

Abstract

Mobile applications (apps) are mostly driven by touch gestures whose interactions are natural to human beings. However, generating gesture events for effective and efficient testing of such apps remains to be a challenge. Existing event generation techniques either feed the apps under test with random gestures or exhaustively enumerate all possible gestures. While the former strategy leads to incomplete test coverage, the latter suffers from efficiency issues. In this paper, we study the particular problem of gesture event generation for Android apps. We present a static analysis technique to obtain the gesture information: each UI component's potentially relevant gestures, so as to reduce the amount of gesture events to be delivered in the automated testing. We implemented our technique as a prototype tool GAT and evaluated it with real-world Android apps. The experimental results show that GAT is both effective and efficient in covering more code as well as detecting gesturerelated bugs.