Automatic Means of Identifying Evolutionary Events in Software Development

The software development process patterns in open source software projects are not well known. Consequently, the longevity of new open source software projects is left up to subjective experiences of the development team. In this study, we are investigating a data mining approach for identifying relevant patterns in software development process. We demonstrate the capabilities of wavelet analysis on 27 open source software projects for identifying similar evolutionary patterns or events in different projects. The analysis identified close to 1000 evolutionary patterns common to multiple projects. The analysis of some of the patterns shows that the end of source code evolution of a project is determined early in the project. In addition, strong fluctuations of activity in sequential periods are identified as good indicators of problems in projects. In conclusion, the analysis reveals that wavelet analysis can be a powerful and objective tool for identifying evolutionary events that can be used as estimation basis or management guide in software projects.