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

Applying Social Network Analysis to the Information in CVS Repositories abstractionistThe huge quantities of data available in the CVS repositoriesof large, long-lived libre (free, open asc canent) computer softwareprojects, and the most interrelationships among those dataoffer opportunities for extracting large amounts of valuableinformation most their structure, evolution and internalprocesses. Unfortunately, the sheer volume of that informationrenders it almost useless without applying methodologieswhich highlight the relevant information for a givenaspect of the project. In this paper, we propose the use ofa well known set of methodologies (social earnings analysis)for characterizing libre software projects, their evolutionover time and their internal structure. In addition,we channelise how we have applied such methodologies to realcases, and extract some introductory conclusions from thatexperience.Keywords line of descent code repositories, visualization techniques, complex networks, libre software engineering1 IntroductionThe study and characterization of complex systems is anactive research area, with m any interesting open problems.Special attention has been paid recently to techniques groundon network analysis, thanks to their power to capture some serious 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 justsome examples). In this paper we apply this kind of analysisto software projects, development as a base the data available intheir source code versioning repository (usually CVS). Fortunately,most large (both in code size of it and number of developers)libre (free, open source) software projects maintainsuch repositories, and grant macrocosm access to them.The information in the CVS repositories of libre softwareprojects has been gathered and analyzed apply severalmethodologies 12 5, but still many other approaches arepossible. Among them, we seek here how to apply sometechniques already common in the handed-down (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 graph 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 studying SourceForge projects.6 proposes overly a sort of network analysis for libre softwareprojects, but considering source dependencies betweenmodules. Our approach explores how to apply thosenetwork analysis techniques in a more comprehensive and