@proceedings {1278,
	title = {Building Knowledge in Open Source Software Research in Six Years of Conferences},
	year = {2011},
	note = {RQ1. Is there any social network underlying the research production at the OSS conference series?
RQ2. What are the major streams of research proposed at the OSS conference series?},
	month = {10/2011},
	pages = {123-141},
	publisher = {Springer},
	abstract = {Since its origins, the diffusion of the OSS phenomenon and the information about it has been entrusted to the Internet and its virtual communities of developers. This public mass of data has attracted the interest of researchers and practitioners aiming at formalizing it into a body of knowledge. To this aim, in 2005, a new series of conferences on OSS started to collect and convey OSS knowledge to the research and industrial community. Our work mines articles of the OSS conference series to understand the process of knowledge grounding and the community surrounding it. As such, we propose a semi-automated approach for a systematic mapping study on these articles. We automatically build a map of cross-citations among all the papers of the conferences and then we manually inspect the resulting clusters to identify knowledge building blocks and their mutual relationships. We found that industry-related, quality assurance, and empirical studies often originate or maintain new streams of research.},
	keywords = {Cross-citations, flossmole cited, graph, literature review, network, research, Systematic Mapping Study},
	author = {Mulazzini, Fabio and Rossi, Bruno and Russo, Barbara and Steff, Maximilian}
}
@inbook {springerlink:10.1007/978-3-642-13244-5_20,
	title = {Download Patterns and Releases in Open Source Software Projects: A Perfect Symbiosis?},
	booktitle = {Open Source Software: New Horizons},
	series = {IFIP Advances in Information and Communication Technology},
	volume = {319},
	year = {2010},
	note = {"We apply experimentally our method to the most downloaded projects of SourceForge{\textquoteright}s history crawled through the FLOSSMole repository."},
	pages = {252-267},
	publisher = {Springer Boston},
	organization = {Springer Boston},
	abstract = {Software usage by end-users is one of the factors used to evaluate the success of software projects. In the context of open source software, there is no single and non-controversial measure of usage, though. Still, one of the most used and readily available measure is data about projects downloads. Nevertheless, download counts and averages do not convey as much information as the patterns in the original downloads time series. In this research, we propose a method to increase the expressiveness of mere download rates by considering download patterns against software releases. We apply experimentally our method to the most downloaded projects of SourceForge{\textquoteright}s history crawled through the FLOSSMole repository. Findings show that projects with similar usage can have indeed different levels of sensitivity to releases, revealing different behaviors of users. Future research will develop further the pattern recognition approach to automatically categorize open source projects according to their download patterns.},
	keywords = {flossmole, oss2010, sourceforge},
	url = {http://dx.doi.org/10.1007/978-3-642-13244-5_20},
	author = {Rossi, Bruno and Russo, Barbara and Succi, Giancarlo},
	editor = {{\r A}gerfalk, P{\"a}r and Boldyreff, Cornelia and Gonz{\'a}lez-Barahona, Jes{\'u}s and Madey, Gregory and Noll, John}
}
