Software Process Analysis via Revision Partitioning: Methodology and Case Study

Open source systems often produce a variety of software artifacts during their development, such as source code, version control records, bug reports, and email discussions. Since the actual work is distributed across different tool environments and developer practices, any analysis of developer behaviour must be inferred from whatever common artifacts happen to be available. In this paper, we propose an approach to characterizing the behaviour of developers around the time of major and minor releases; we do this by partitioning the observed activities, such as artifact check-ins, around the dates or major and minor releases, and looking for recognizable patterns. We validate this approach by means of an exploratory case study on the MySQL database system; in this case study, we found that more testing and documenting took place before a release than after and that source code changes dipped in frequency around release time. 1