DATAR: A Dataset for Tracking App Releases
Yasaman Abedini, Mohammad Hadi Hajihosseini, Abbas Heydarnoori · 2024
Android apps continuously evolve to meet user expectations and thrive in the competitive environment of app stores. Hence, making informed decisions is crucial for the success of upcoming releases. In recent years, researchers have sought to aid developers in release planning by studying, analyzing, and modeling evolutionary information derived from tracking releases of various apps. They have demonstrated how the types of information provided on different platforms can effectively predict and assess the quality or success of an app. Nevertheless, this field needs a comprehensive dataset containing evolutionary information that tracks various releases of open-source Android apps. Existing datasets lack release-level information, are not publicly available, or do not cover a wide range of up-to-date apps. This paper introduces a dataset comprising diverse metadata adapted from GitHub and Google Play, along with impactful metrics extracted from the source code of 8,041 published releases of 1,363 open-source Android apps.