Mining usage data and development artifacts

Abstract

Software repository mining techniques generally focus on analyzing, unifying, and querying different kinds of development artifacts, such as source code, version control meta-data, defect tracking data, and electronic communication. In this work, we demonstrate how adding real-world usage data enables addressing broader questions of how software systems are actually used in practice, and by inference how development characteristics ultimately affect deployment, adoption, and usage. In particular, we explore how usage data that has been extracted from web server logs can be unified with product release history to study questions that concern both users' detailed dynamic behaviour as well as broad adoption trends across different deployment environments. To validate our approach, we performed a study of two open source web browsers: Firefox and Chrome. We found that while Chrome is being adopted at a consistent rate across platforms, Linux users have an order of magnitude higher rate of Firefox adoption. Also, Firefox adoption has been concentrated mainly in North America, while Chrome users appear to be more evenly distributed across the globe. Finally, we detected no evidence in age-specific differences in navigation behaviour among Chrome and Firefox users; however, we hypothesize that younger users are more likely to have more up-to-date versions than more mature users.