API compatibility issues in Android: Causes and effectiveness of data-driven detection techniques

ndroid fragmentation is a well-known issue referring to the adoption of different versions in the multitude of devices supporting such an operating system. Each Android version features a set of APIs provided to developers. These APIs are subject to changes and may cause compatibility issues. To support app developers, approaches have been proposed to automatically identify API compatibility issues. CiD , the state-of-the-art approach, is a data-driven solution learning how to detect those issues by analyzing the change history of Android APIs (“ API side ” learning). In this paper (extension of our MSR 2019 paper), we present an alternative data-driven approach, named ACRyL . ACRyL learns from changes implemented in apps in response to API changes (“ client side ” learning). When comparing these two solutions on 668 apps, for a total of 11,863 snapshots, we found that there is no clear winner, since the two techniques are highly complementary, and none of them provides a comprehensive support in detecting API compatibility issues: ACRyL achieves a precision of 7.0