Research Article

Open source software development and Lotka's Law: Bibliometric patterns in programming

  1. Gregory B. Newby,
  2. Jane Greenberg,
  3. Paul Jones

Article first published online: 10 DEC 2002

DOI: 10.1002/asi.10177

Issue

Journal of the American Society for Information Science and Technology

Journal of the American Society for Information Science and Technology

Volume 54, Issue 2, pages 169–178, 15 January 2003

Additional Information

How to Cite

Newby, G. B., Greenberg, J. and Jones, P. (2003), Open source software development and Lotka's Law: Bibliometric patterns in programming. J. Am. Soc. Inf. Sci., 54: 169–178. doi: 10.1002/asi.10177

Author Information

  1. University of North Carolina at Chapel Hill, 100 Manning Hall, CB3360, Chapel Hill, NC 27599-3360

Publication History

  1. Issue published online: 3 JAN 2003
  2. Article first published online: 10 DEC 2002
  3. Manuscript Accepted: 28 MAR 2002
  4. Manuscript Revised: 7 MAR 2002
  5. Manuscript Received: 5 OCT 2001

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Abstract

This research applies Lotka's Law to metadata on open source software development. Lotka'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's Law for scientific and scholarly publishing. Lotka's Law was found to be effective in understanding software development productivity patterns, and offer promise in predicting aggregate behavior of open source developers.

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