The FLOSS understood as a development model provides a well-defined or at least can be characterized through social organization established patterns.
A good example of this is shown by "Crowston & Howison" who examined 120 projects from SourceForge and inquired about their social organization, discovering that there are patterns around each project and its members, in fact they found a pattern of stratification baptized as "The Onion Model".
There are specific tools to perform this type of analysis, here we mention two of them based on FLOSS: "CVSAnalY" (https://github.com/MetricsGrimoire/CVSAnalY) y "R Project" (http://www.r-project.org).
CVSAnalY is based on Python under GNU GPL license, and extracts information out of source code repository logs and stores it into a database. This provides the potential to analyze in detail the data contained in the log of a project, doing custom queries and limiting the results to what is really needed. For instance, the database could be MySQL and the repository source could be Git.
The R Project also based on GNU GPL license, provides set of software facilities for data manipulation, calculation and graphical display, based on the R language which is oriented to statistical computing and graphics. With this tool we could generate bar graphs showing the distribution of the bug-threads for certain project, or the top commiters by specific dates for instance.
Obtaining metric statistics and graphical visualization for the activity of developers around free software projects, allow us to identify among many other things: orders of magnitude between the Onion Model layers, determine the existence of "generational relay", do "social network analisys" or identify "developers territoriality" and thereby make analysis regarding the evolution of the project.
- Ortega F., Amor J. and Robles G. "The Onion Model in FLOSS". GSyC-Libresoft, MSWL URJC, Madrid, November 2011.
- Crowston K and Howison J. "The social structure of Free and Open Source software development". School of Information Studies, Syracuse University. November 2004.