@article {123,
	title = {Open source software development and Lotka{\textquoteright}s Law: Bibliometric patterns in programming},
	journal = {Journal of the American Society for Information Science and Technology},
	volume = {54},
	number = {2},
	year = {2003},
	note = {"Two lead- ing metadata repositories are the Linux Software Map (LSM) and Sourceforge, both of which were used for this research."
"For this article, we examined data listing the number of registered developers for each software project hosted by Sourceforge."
"The data we obtained from the LSM collection were taken mainly from the Author: field of LSM records. The Author: field in LSM records gives us the ability to track the author of record for a software package. LSM metadata also include a list of maintainers, primary software distribution sites, date of update and other items."
"The data we obtained from Sourceforge consist of a list of developer ID numbers, followed by the number of projects on which the individual is listed as a developer, then the number of projects on which the individual is listed as an administrator. These data were provided for all 33,892 individuals registered to work on projects hosted by Sourceforge in July 2001."},
	pages = {169-178},
	abstract = {This research applies Lotka{\textquoteright}s Law to metadata on open source software development. Lotka{\textquoteright}s Law predicts the proportion of authors at different levels of productivity. Open source software development harnesses the creativity of thousands of programmers worldwide, is important to the progress of the Internet and many other computing environments, and yet has not been widely researched. We examine metadata from the Linux Software Map (LSM), which documents many open source projects, and Sourceforge, one of the largest resources for open source developers. Authoring patterns found are comparable to prior studies of Lotka{\textquoteright}s Law for scientific and scholarly publishing. Lotka{\textquoteright}s Law was found to be effective in understanding software development productivity patterns, and offer promise in predicting aggregate behavior of open source developers.},
	keywords = {developers, linux, linux software map, lsm, sourceforge, team size},
	doi = {10.1002/asi.10177},
	author = {Newby, G. B. and Greenberg, J. and Jones, P.}
}
