Large-Scale Analysis of Framework-Specific Exceptions in Android Apps
Lingling Fan, Ting Su, Sen Chen, Guozhu Meng, Yang Liu, Lihua Xu,, Geguang Pu, Zhendong Su

TL;DR
This study provides a large-scale analysis of framework-specific exceptions in Android apps, revealing their characteristics, impact, and fixes, and demonstrates practical tools for bug detection and localization.
Contribution
It offers the first comprehensive analysis of Android framework exceptions, introduces optimized bug detection and localization tools, and shares a valuable dataset for future research.
Findings
Framework exceptions account for most app crashes.
Tools like Stoat and ExLocator effectively detect and locate exceptions.
The dataset and tools are publicly available for community use.
Abstract
Mobile apps have become ubiquitous. For app developers, it is a key priority to ensure their apps' correctness and reliability. However, many apps still suffer from occasional to frequent crashes, weakening their competitive edge. Large-scale, deep analyses of the characteristics of real-world app crashes can provide useful insights to guide developers, or help improve testing and analysis tools. However, such studies do not exist -- this paper fills this gap. Over a four-month long effort, we have collected 16,245 unique exception traces from 2,486 open-source Android apps, and observed that framework-specific exceptions account for the majority of these crashes. We then extensively investigated the 8,243 framework-specific exceptions (which took six person-months): (1) identifying their characteristics (e.g., manifestation locations, common fault categories), (2) evaluating their…
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