@conference {1258,
	title = {Exploring Complexity in Open Source Software: Evolutionary Patterns, Antecedents, and Outcomes},
	booktitle = {2010 43rd Hawaii International Conference on System Sciences (HICSS 2010)},
	year = {2010},
	note = {"The sample of projects was drawn from SourceForge"
"projects were selected that were built with C++."
"Applying the selection criteria generated a total of 108 projects for analysis"
"Scientific Toolwork{\textquoteright}s Understand (version 1.4)"},
	pages = {1 - 11},
	publisher = {IEEE},
	organization = {IEEE},
	address = {Honolulu, Hawaii, USA},
	abstract = {Software complexity is important to researchers and managers, yet much is unknown about how complexity evolves over the life of a software application and whether different dimensions of software complexity may exhibit similar or different evolutionary patterns. Using cross-sectional and longitudinal data on a sample of 108 open source projects, this research investigated how the complexity of open source project releases varied throughout the life of the project. Functional data analysis was applied to the release histories of the projects and recurring evolutionary patterns were derived. There were projects that saw little evolution, according to their measures of size and structural complexity. However, projects that displayed some evolution often differed on the pattern of evolution depending on whether size or structural complexity was examined. Factors that contribute to and result from the patterns of complexity were evaluated, and implications for research and practice are presented.},
	keywords = {complexity, evolution, fda, life cycle, sourceforge, srda},
	isbn = {978-1-4244-5509-6},
	doi = {10.1109/HICSS.2010.198},
	attachments = {https://flosshub.org/sites/flosshub.org/files/10-07-02.pdf},
	author = {Darcy, David P. and Daniel, Sherae L. and Stewart, Katherine J.}
}
@article {2006,
	title = {Opportunities and Challenges Applying Functional Data Analysis to the Study of Open Source Software Evolution},
	journal = {Statistical Science},
	volume = {21},
	number = {2},
	year = {2006},
	note = {"As part of a larger project, data were collected on 105 OSS	projects hosted online at Sourceforge (sf.net)." "...we limited our data collection to projects that use only the Java programming language and were listed in the Internet and System Networking domains." "... only including these projects that use an OSI approved license..." "had to have posted at least one file on the Sourceforge site as of the time of our initial project selection Fall 2002" "Data were collected on the published release history of each project thatmet the screening criteria. Each release of each project was
analyzed to calculate CplXLCoh. The size of each release was measured using a calculation of the number of lines of code (LOC)"},
	pages = {167-178},
	publisher = {Institute of Mathematical Statistics},
	abstract = {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.},
	keywords = {complexity, evolution, fda, java, lines of code, loc, release history, scm, size, sourceforge},
	issn = {08834237},
	url = {http://www.jstor.org/stable/27645747},
	author = {Stewart, Katherine J. and Darcy, David P. and Daniel, Sherae L.}
}
