@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}
}
@book {1249,
	title = {Open Source Software Developer and Project Networks},
	series = {IFIP Advances in Information and Communication TechnologyOpen Source Software: New Horizons},
	volume = {319},
	year = {2010},
	note = {no information on data gathering procedures},
	pages = {407 - 412},
	publisher = {Springer Berlin Heidelberg},
	organization = {Springer Berlin Heidelberg},
	address = {Berlin, Heidelberg},
	abstract = {This paper outlines complex network concepts and how social networks are built from Open Source Software (OSS) data. We present an initial study of the social networks of three different OSS forges, BerliOS Developer, GNU Savannah, and SourceForge. Much research has been done on snapshot or conflated views of these networks, especially SourceForge, due to the size of the SourceForge community. The degree distribution, connectedness, centrality, and scale-free nature of SourceForge has been presented for the network at particular points in time. However, very little research has been done on how the network grows, how connections were made, especially during its infancy, and how these metrics evolve over time. },
	keywords = {berlios, savannah, sourceforge},
	isbn = {978-3-642-13244-5},
	issn = {1861-2288},
	doi = {10.1007/978-3-642-13244-5_39},
	author = {Madey, G. and van Antwerp, M.},
	editor = {{\r A}gerfalk, P{\"a}r and Boldyreff, Cornelia and Gonz{\'a}lez-Barahona, Jes{\'u}s M. and Madey, Gregory R. and Noll, John}
}
@book {1250,
	title = {Warehousing and Studying Open Source Versioning Metadata},
	series = {IFIP Advances in Information and Communication Technology Open Source Software: New Horizons (OSS 2010)},
	volume = {319},
	year = {2010},
	pages = {413 - 418},
	publisher = {Springer Berlin Heidelberg},
	organization = {Springer Berlin Heidelberg},
	address = {Berlin, Heidelberg},
	abstract = {In this paper, we describe the downloading and warehousing of Open Source Software (OSS) versioning metadata from SourceForge, BerliOS Developer, and GNU Savannah. This data enables and supports research in areas such as software engineering, open source phenomena, social network analysis, data mining, and project management. This newly-formed database containing Concurrent Versions System (CVS) and Subversion (SVN) metadata offers new research opportunities for large-scale OSS development analysis. The CVS and SVN data is juxtaposed with the SourceForge.net Research Data Archive [5] for the purpose of performing more powerful and interesting queries. We also present an initial statistical analysis of some of the most active projects. },
	keywords = {berlios, cvs, savannah, scm, sourceforge, srda, subversion, svn},
	isbn = {978-3-642-13244-5},
	issn = {1861-2288},
	doi = {10.1007/978-3-642-13244-5_40},
	author = {van Antwerp, M. and Madey, G.},
	editor = {{\r A}gerfalk, P{\"a}r and Boldyreff, Cornelia and Gonz{\'a}lez-Barahona, Jes{\'u}s M. and Madey, Gregory R. and Noll, John}
}
@article {Beecher2009739,
	title = {Identifying exogenous drivers and evolutionary stages in FLOSS projects},
	journal = {Journal of Systems and Software},
	volume = {82},
	number = {5},
	year = {2009},
	pages = {739 - 750},
	abstract = {The success of a Free/Libre/Open Source Software (FLOSS) project has been evaluated in the past through the number of commits made to its configuration management system, number of developers and number of users. Most studies, based on a popular FLOSS repository (SourceForge), have concluded that the vast majority of projects are failures. This study{\textquoteright}s empirical results confirm and expand conclusions from an earlier and more limited work. Not only do projects from different repositories display different process and product characteristics, but a more general pattern can be observed. Projects may be considered as early inceptors in highly visible repositories, or as established projects within desktop-wide projects, or finally as structured parts of FLOSS distributions. These three possibilities are formalized into a framework of transitions between repositories. The framework developed here provides a wider context in which results from FLOSS repository mining can be more effectively presented. Researchers can draw different conclusions based on the overall characteristics studied about an Open Source software project{\textquoteright}s potential for success, depending on the repository that they mine. These results also provide guidance to OSS developers when choosing where to host their project and how to distribute it to maximize its evolutionary success.},
	keywords = {developers, forge, forges, repositories, repository, scm, software repositories, sourceforge, success, users},
	issn = {0164-1212},
	doi = {DOI: 10.1016/j.jss.2008.10.026},
	url = {http://www.sciencedirect.com/science/article/B6V0N-4TVTJFS-1/2/e32ecee1bcb54bd4a5dff6d5e3daca8d},
	author = {Karl Beecher and Capiluppi, Andrea and Boldyreff, Cornelia}
}
@article {Capiluppi200989,
	title = {Quality Factors and Coding Standards - a Comparison Between Open Source Forges},
	journal = {Electronic Notes in Theoretical Computer Science},
	volume = {233},
	year = {2009},
	note = {Proceedings of the International Workshop on Software Quality and Maintainability (SQM 2008)},
	pages = {89 - 103},
	abstract = {Enforcing adherence to standards in software development in order to produce high quality software artefacts has long been recognised as best practice in traditional software engineering. In a distributed heterogeneous development environment such those found within the Open Source paradigm, coding standards are informally shared and adhered to by communities of loosely coupled developers. Following these standards could potentially lead to higher quality software. This paper reports on the empirical analysis of two major forges where OSS projects are hosted. The first one, the KDE forge, provides a set of guidelines and coding standards in the form of a coding style that developers may conform to when producing the code source artefacts. The second studied forge, SourceForge, imposes no formal coding standards on developers. A sample of projects from these two forges has been analysed to detect whether the SourceForge sample, where no coding standards are reinforced, has a lower quality than the sample from KDE. Results from this analysis form a complex picture; visually, all the selected metrics show a clear divide between the two forges, but from the statistical standpoint, clear distinctions cannot be drawn amongst these quality related measures in the two forge samples.},
	keywords = {artefacts, artifacts, coding standards, coding style, complexity, forge, forges, kde, metrics, quality, source code, sourceforge},
	issn = {1571-0661},
	doi = {DOI: 10.1016/j.entcs.2009.02.063},
	url = {http://www.sciencedirect.com/science/article/B75H1-4VXDKRV-7/2/abcc2be2c4c3998e4bc9b53473ca2d81},
	author = {Capiluppi, Andrea and Boldyreff, Cornelia and Karl Beecher and Paul J. Adams}
}
