Empirical validation of Lotka's law
Information Processing and Management: an International Journal
A modification of Lotka's function for scientific productivity
Information Processing and Management: an International Journal
Information Processing and Management: an International Journal - Special issue: history of information science
Sendmail(2nd ed.)
A case study of open source software development: the Apache server
Proceedings of the 22nd international conference on Software engineering
Who is an open source software developer?
Communications of the ACM - Ontology: different ways of representing the same concept
Open Sources: Voices from the Open Source Revolution
Open Sources: Voices from the Open Source Revolution
The Cathedral and the Bazaar
DNS and BIND
Supporting change request assignment in open source development
Proceedings of the 2006 ACM symposium on Applied computing
Applications of data mining in software engineering
International Journal of Data Analysis Techniques and Strategies
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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.