  Software maintenance constitutes a large portion of the software development
lifecycle. To carry out maintenance tasks, developers often need to understand
and reproduce bug reports. As such, there has been increasing research activity
coalescing around the notion of automating various activities related to bug
reporting. A sizable portion of this research interest has focused on the
domain of mobile apps. However, as research around mobile app bug reporting
progresses, there is a clear need for a manually vetted and reproducible set of
real-world bug reports that can serve as a benchmark for future work. This
paper presents ANDROR2: a dataset of 90 manually reproduced bug reports for
Android apps listed on Google Play and hosted on GitHub, systematically
collected via an in-depth analysis of 459 reports extracted from the GitHub
issue tracker. For each reproduced report, ANDROR2 includes the original bug
report, an apk file for the buggy version of the app, an executable
reproduction script, and metadata regarding the quality of the reproduction
steps associated with the original report. We believe that the ANDROR2 dataset
can be used to facilitate research in automatically analyzing, understanding,
reproducing, localizing, and fixing bugs for mobile applications as well as
other software maintenance activities more broadly.
