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The open source development community consists of both paid and volunteerdevelopers as well as new and experienced users. Previous work has appliedsocial network analysis (SNA) to open source communities and has demonstratedvalue in expertise discovery and triaging. One problem with applying SNAdirectly to the data of the entire project lifetime is that the impact of localactivities will be drowned out. In this paper we provide a method foraggregating, analyzing, and visualizing local (small time periods) interactionsof bug reporting participants by using the SNA to measure the betweenesscentrality of these participants. In particular we mined the Android bugrepository by producing social networks from overlapping 30-day windows of bugreports, each sliding over by day. In this paper we define three patterns ofparticipant behaviour based on their local centrality. We propose a method ofanalyzing the centrality of bug report participants both locally and globally,then we conduct a thorough case study of the bug reporter's activity within theAndroid bug repository. Furthermore, we validate the conclusions of our methodby mining the Android version control system and inspecting the Android releasehistory. We found that windowed SNA analysis elicited local behaviour that wereinvisible during global analysis.

Mining the Temporal Evolution of the Android Bug Reporting Community via Sliding Windows