@conference {1212,
	title = {Studying Production Phase SourceForge Projects: An Exploratory Analysis Using cvs2mysql and SFRA},
	booktitle = {2nd Workshop on Public Data about Software Development (WoPDaSD 2007)},
	year = {2007},
	month = {2007},
	abstract = {A wealth of data can be extracted from the natural by-products of software development processes and used in empirical studies of software engineering. However, the size and accuracy of such studies depend in large part on the availability of tools that facilitate the collection of data from individual projects and the combination of data from multiple projects. To demonstrate this point, we present our experience gathering and analyzing data from nearly 10,000 open source projects hosted on SourceForge. We describe the tools we developed to collect the data and the ways in which these tools and data may be used by other researchers. We also provide examples of statistics that we have calculated from these data to describe interesting author- and project-level behaviors of the SourceForge community.},
	keywords = {Data Collection, forge, repositories, sourceforge},
	attachments = {https://flosshub.org/sites/flosshub.org/files/Delorey2007c.pdf},
	author = {Delorey, Daniel P. and Knutson, Charles D. and MacLean, Alexander C.}
}
@conference {1213,
	title = {Working with Open Source Development Data: Considerations triggered by a study of bug scenarios},
	booktitle = {2nd Workshop on Public Data about Software Development (WoPDaSD 2007)},
	year = {2007},
	month = {2007},
	abstract = {The retrieval and preparation of public data on software development calls for more than just technical skills. In 
addition, care and judgement are needed to avoid disproportionate costs to the providers of data or unnecessary embarrassment to the participants tracked in the data. Taking the extraction of bug scenarios as a use case, we illustrate these concerns and discuss how they could be translated into social requirements that would help to make retrieval and preparation a sustainable exercise. In particular, we call for more efforts to establish institutional repositories of public data on software development and, besides, we suggest that reviewers could play a role in making sure that empirical research is performed in a way that does not bring the long-term relationship between software developers and researchers in jeopardy. },
	keywords = {bug reports, bug scenarios, Data Collection},
	attachments = {https://flosshub.org/sites/flosshub.org/files/denBesten-wopdasd.pdf},
	author = {den Besten, Matthijs and Masmoudi, H{\'e}la and Jean-Michel Dalle}
}
@proceedings {flosswp181,
	title = {The perils and pitfalls of mining SourceForge},
	year = {2004},
	month = {05/2004},
	pages = {7-11},
	abstract = {SourceForge provides abundant accessible data from Open Source Software development projects, making it an attractive data source for software engineering research. However it is not without theoretical peril and practical pitfalls. In this paper, we outline practical lessons gained from our spidering, parsing and analysis of SourceForge data. SourceForge can be practically difficult: projects are defunct, data from earlier systems has been dumped in and crucial data is hosted outside SourceForge, dirtying the retrieved data. These practical issues play directly into analysis: decisions made in screening projects can reduce the range of variables, skewing data and biasing correlations. SourceForge is theoretically perilous: because it provides easily accessible data items for each project, tempting researchers to fit their theories to these limited data. Worse, few are plausible dependent variables. Studies are thus likely to test the same hypotheses even if they start from different theoretical bases. To avoid these problems, analyses of SourceForge projects should go beyond project level variables and carefully consider which variables are used for screening projects and which for testing hypotheses.},
	keywords = {Data Collection, sourceforge},
	attachments = {https://flosshub.org/sites/flosshub.org/files/howison04msr.pdf},
	author = {Howison, James and Kevin Crowston}
}
@conference {Gasser04researchinfrastructure,
	title = {Research Infrastructure for Empirical Science of F/OSS},
	booktitle = {Proc. Intern. Workshop on Mining Software Repositories},
	year = {2004},
	pages = {12-16},
	abstract = {F/OSS research faces a new and unusual situation: the traditional difficulties of gathering enough empirical data have been replaced by issues of dealing with enormous amounts of freely available data from many disparate sources (forums, code, bug reports, etc.) At present no means exist for assembling these data under common access points and frameworks for comparative, longitudinal, and collaborative research. Gathering and maintaining large F/OSS data collections reliably and making them usable present several research challenges. For example, current projects usually rely on {\textquotedblleft}web scraping{\textquotedblright} or on direct access to raw data from groups that generate it, and both of these methods require unique effort for each new corpus, or even for updating existing corpora. In this paper we identify several common needs and critical factors in F/OSS empirical research, and suggest orientations and recommendations for the design of a shared research infrastructure.},
	keywords = {data, Data Collection, empirical, infrastructure},
	attachments = {https://flosshub.org/sites/flosshub.org/files/12ResearchInfrastructure.pdf},
	author = {Gasser, Les and Gabriel Ripoche and Sandusky, Robert J.}
}
