Open Access
May 2006 Opportunities and Challenges Applying Functional Data Analysis to the Study of Open Source Software Evolution
Katherine J. Stewart, David P. Darcy, Sherae L. Daniel
Statist. Sci. 21(2): 167-178 (May 2006). DOI: 10.1214/088342306000000141


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.


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Katherine J. Stewart. David P. Darcy. Sherae L. Daniel. "Opportunities and Challenges Applying Functional Data Analysis to the Study of Open Source Software Evolution." Statist. Sci. 21 (2) 167 - 178, May 2006.


Published: May 2006
First available in Project Euclid: 7 August 2006

zbMATH: 05191858
MathSciNet: MR2324076
Digital Object Identifier: 10.1214/088342306000000141

Keywords: Functional data analysis , open source software , software complexity

Rights: Copyright © 2006 Institute of Mathematical Statistics

Vol.21 • No. 2 • May 2006
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