%0 Journal Article
%J Statistical Science
%D 2006
%T Opportunities and Challenges Applying Functional Data Analysis to the Study of Open Source Software Evolution
%A Stewart, Katherine J.
%A Darcy, David P.
%A Daniel, Sherae L.
%K complexity
%K evolution
%K fda
%K java
%K lines of code
%K loc
%K release history
%K scm
%K size
%K sourceforge
%X 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.
%B Statistical Science
%I Institute of Mathematical Statistics
%V 21
%P 167-178
%U http://www.jstor.org/stable/27645747