The tech world frequently talks about open source software as a collaborative endeavor, but it is less apt to use the word “commons,” let alone engage in rigorous empirical analysis for understanding how software commons actually work. The arrival of Internet Success: A Study of Open-Source Software Commons (MIT Press) is therefore a welcome event. This book is the first large-scale empirical study to look at the social, technical and institutional aspects of free, libre and open source software (often known as “FLOSS”). It uses extensive firsthand survey research, statistical analysis and commons frameworks for studying this under-theorized realm.
While most people may associate open source software with Linux, there are in fact tens of thousands of open source projects in existence. Many consist of no more than two or three participants, and may have only an irregular existence. However, many thousands of others attract a small but spirited team, and still others are huge, robust social ecosystems in their own right.
The authors of Internet Success, UMass Professor Charles M. Schweik and consultant Robert C. English, looked at the large universe of FLOSS projects hosted on SourceForge.net, a website that functions as a kind of clearinghouse for over 260,000 FLOSS projects (as of February 2011) and 2.7 registered software developers. The site provides most of the tools that developers need to find colleagues and build a new FLOSS program – a Web repository of code, bug-tracking utilities, online forums, email mailing lists, a wiki, file downloading services, etc.
While SourceForge is not the only such site for FLOSS projects, it is the largest and arguably representative of the universe of such projects. With support from the National Science Foundation, Schweik and English set out to study the pool of software development projects on SourceForge to try to determine why some succeed, why others fail and why others simply languish. They explain in excruciating technical, social science detail how they assembled and analyzed their datasets, which originate in a vast collection of SourceForge data on more than 130,000 projects as well as their own survey questionnaire of programmers.