On the prediction of the evolution of libre software projects

Abstract

Libre (free / open source) software development is a complex phenomenon. Many actors (core developers, casual contributors, bug reporters, patch submitters, users, etc.), in many cases volunteers, interact in complex patterns without the constrains of formal hierarchical structures or organizational ties. Understanding this complex behavior with enough detail to build explanatory models suitable for prediction is an open challenge, and few results have been published to date in this area. Therefore statistical, non-explanatory models (such as the traditional regression model) have a clear role, and have been used in some evolution studies. Our proposal goes in this direction, but using a model that we have found more useful: time series analysis. Data available from the source code management repository is used to compute the size of the software over its past life, using this information to estimate the future evolution of the project. In this paper we present this methodology and apply it to three large projects, showing how in these cases predictions are more accurate than regression models, and precise enough to estimate with little error their near future evolutions.