Applying Social Network Analysis to the Information in CVS Repositories :: essays research papers

Applying Social Network Analysis to the Information in CVS Repositories annulThe huge quantities of data available in the CVS repositoriesof large, long-lived libre (free, open reference book) softwareprojects, and the many interrelationships among those dataoffer opportunities for extracting large amounts of valuableinformation about their structure, ontogeny and internalprocesses. Unfortunately, the sheer volume of that informationrenders it almost unusable without gifting methodologieswhich highlight the relevant information for a givenaspect of the project. In this paper, we propose the use of goods and services ofa well known set of methodologies (social network analysis)for characterizing libre software projects, their evolutionover time and their internal structure. In addition,we show how we have applied such(prenominal) methodologies to realcases, and extract some preliminary conclusions from thatexperience.Keywords source code repositories, visualization techniques, in volved net kit and boodle, libre software engineering1 IntroductionThe study and characterization of complex systems is anactive research area, with many interesting open problems.Special attention has been paid recently to techniques basedon network analysis, thanks to their power to trance someimportant characteristics and relationships. Network characterizationis widely used in many scientific and technologicaldisciplines, ranging from neurobiology 14 to computernetworks 1 3 or linguistics 9 (to mention uprightsome examples). In this paper we apply this kind of analysisto software projects, using as a base the data available intheir source code versioning repository (usually CVS). Fortunately,most large (both in code size and number of developers)libre (free, open source) software projects maintainsuch repositories, and grant public advance to them.The information in the CVS repositories of libre softwareprojects has been gathered and analyzed using severalmethodologies 12 5, but still many other approaches arepossible. Among them, we explore here how to apply sometechniques already common in the traditional (social) networkanalysis. The proposed approach is based on consideringeither modules (usually CVS directories) or developers(commiters to the CVS) as vertices, and the number of commoncommits as the weight of the link between any two vertices(see section 3 for a more detailed definition). This way,we end up with a weighted graphical record which captures some relationshipsbetween developers or modules, in which characteristicsas information flow or communities can be studied.There have been some other works analyzing social networksin the libre software world. 7 hypothesizes that theorganization of libre software projects can be modeled asself-organizing social networks and shows that this seemsto be true at least when poring over SourceForge projects.6 proposes also a sort of network analysis for libre softwareprojects, but considering source depe ndencies betweenmodules. Our approach explores how to apply thosenetwork analysis techniques in a more comprehensive and