  This paper explores the application of functional data analysis (FDA) as a
means to study the dynamics of software evolution in the open source context.
Several challenges in analyzing the data from software projects are discussed,
an approach to overcoming those challenges is described, and preliminary
results from the analysis of a sample of open source software (OSS) projects
are provided. The results demonstrate the utility of FDA for uncovering and
categorizing multiple distinct patterns of evolution in the complexity of OSS
projects. These results are promising in that they demonstrate some patterns in
which the complexity of software decreased as the software grew in size, a
particularly novel result. The paper reports preliminary explorations of
factors that may be associated with decreasing complexity patterns in these
projects. The paper concludes by describing several next steps for this
research project as well as some questions for which more sophisticated
analytical techniques may be needed.
