@proceedings {1522,
	title = {Boa: A Language and Infrastructure for Analyzing Ultra-Large-Scale Software Repositories},
	year = {2013},
	month = {05/2013},
	pages = {422-431},
	abstract = {In today{\textquoteright}s software-centric world, ultra-large-scale software repositories, e.g. SourceForge (350,000+ projects), GitHub (250,000+ projects), and Google Code (250,000+ projects) are the new library of Alexandria. They contain an enormous corpus of software and information about software. Scientists and engineers alike are interested in analyzing this wealth of information both for curiosity as well as for testing important hypotheses. However, systematic extraction of relevant data from these repositories and analysis of such data for testing hypotheses is hard, and best left for mining software repository (MSR) experts! The goal of Boa, a domain-specific language and infrastructure described here, is to ease testing MSR-related hypotheses. We have implemented Boa and provide a web-based interface to Boa{\textquoteright}s infrastructure. Our evaluation demonstrates that Boa substantially reduces programming efforts, thus lowering the barrier to entry. We also see drastic improvements in scalability. Last but not least, reproducing an experiment conducted using Boa is just a matter of re-running small Boa programs provided by previous researchers.},
	keywords = {ease of use, forge, github, google code, lower barrier to entry, mining, repository, reproducible, scalable, Software, sourceforge},
	author = {Dyer, Robert and Nguyen, Hoan Anh and Rajan, Hridesh and Nguyen, Tien N.}
}
@article {Ampatzoglou2013131,
	title = {Building and mining a repository of design pattern instances: Practical and research benefits},
	journal = {Entertainment Computing},
	volume = {4},
	number = {2},
	year = {2013},
	note = {flossmole cited},
	pages = {131 - 142},
	abstract = {Design patterns are well-known design solutions that are reported to produce substantial benefits with respect to software quality. However, to our knowledge there are no scientific efforts on gathering information on software projects that use design patterns. This paper introduces a web repository of design patterns instances that have been used in open source projects. The usefulness of such a repository lies in the provision of a base of knowledge, where developers can identify reusable components and researchers can find a mined data set. Currently, 141 open source projects have been considered and more than 4500 pattern instances have been found and recorded in the database of the repository. The evaluation of the repository has been performed from an academic and a practical point of view. The results suggest that the repository can be useful for both experienced and inexperienced users. However, the benefits of using the repository are more significant for inexperienced users. },
	keywords = {flossmole cited, repository},
	issn = {1875-9521},
	doi = {10.1016/j.entcom.2012.10.002},
	url = {http://www.sciencedirect.com/science/article/pii/S1875952112000195},
	author = {Apostolos Ampatzoglou and Olia Michou and Ioannis Stamelos}
}
@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}
}
@conference {945,
	title = {SourcererDB: An aggregated repository of statically analyzed and cross-linked open source Java projects},
	booktitle = {2009 6th IEEE International Working Conference on Mining Software Repositories (MSR)2009 6th IEEE International Working Conference on Mining Software Repositories},
	year = {2009},
	pages = {183 - 186},
	publisher = {IEEE},
	organization = {IEEE},
	address = {Vancouver, BC, Canada},
	abstract = {The open source movement has made vast quantities of source code available online for free, providing an extremely large dataset for empirical study and potential resuse. A major difficulty in exploiting this potential fully is that the data are currently scattered between competing source code repositories, none of which are structured for empirical analysis and cross-project comparison. As a result, software researchers and developers are left to compile their own datasets, resulting in duplicated effort and limited results. To address this challenge, we built SourcererDB, an aggregated repository of statically analyzed and cross-linked open source Java projects. SourcererDB contains local snapshots of 2,852 Java projects taken from Sourceforge, Apache and Java.net. These projects are statically analyzed to extract rich structural information, which is then stored in a relational database. References to entities in the 16,058 external jars are resolved and grouped, allowing for cross-project usage information to be accessed easily. This paper describes: (a) the mechanism for resolving and grouping these cross-project references, (b) the structure of and the metamodel for the SourcererDB repository, and (d) end-user dataset access mechanisms. Our goal in building SourcererDB is to provide a rich dataset of source code to facilitate the sharing of extracted data and to encourage reuse and repeatability of experiments.},
	keywords = {apache, integration, java, java.net, project, repository, sourceforge, SourcererDB},
	isbn = {978-1-4244-3493-0},
	doi = {10.1109/MSR.2009.5069501},
	author = {Ossher, Joel and Bajracharya, Sushil and Linstead, Erik and Baldi, Pierre and Lopes, Cristina}
}
@conference {940,
	title = {Using Latent Dirichlet Allocation for automatic categorization of software},
	booktitle = {2009 6th IEEE International Working Conference on Mining Software Repositories (MSR)2009 6th IEEE International Working Conference on Mining Software Repositories},
	year = {2009},
	pages = {163 - 166},
	publisher = {IEEE},
	organization = {IEEE},
	address = {Vancouver, BC, Canada},
	abstract = {In this paper, we propose a technique called LACT for automatically categorizing software systems in open-source repositories. LACT is based on latent Dirichlet Allocation, an information retrieval method which is used to index and analyze source code documents as mixtures of probabilistic topics. For an initial evaluation, we performed two studies. In the first study, LACT was compared against an existing tool, MUDABlue, for classifying 41 software systems written in C into problem domain categories. The results indicate that LACT can automatically produce meaningful category names and yield classification results comparable to MUDABlue. In the second study, we applied LACT to 43 software systems written in different programming languages such as C/C++, Java, C$\#$, PHP, and Perl. The results indicate that LACT can be used effectively for the automatic categorization of software systems regardless of the underlying programming language or paradigm. Moreover, both studies indicate that LACT can identify several new categories that are based on libraries, architectures, or programming languages, which is a promising improvement as compared to manual categorization and existing techniques.},
	keywords = {categorization, category mining, lact, mudablue, multiple languages, repository},
	isbn = {978-1-4244-3493-0},
	doi = {10.1109/MSR.2009.5069496},
	attachments = {https://flosshub.org/sites/flosshub.org/files/163MSR2009_TianPos.pdf},
	author = {Tian, Kai and Revelle, Meghan and Poshyvanyk, Denys}
}
@conference {1208,
	title = {Advances in the Sourceforge Research Data Archive},
	booktitle = {3rd Workshop on Public Data about Software Development (WoPDaSD 2008)},
	year = {2008},
	month = {2009},
	pages = {25-29},
	abstract = {The SourceForge Research Data Archive (SRDA), located at http://zerlot.cse.nd.edu, is a collection of Open Source Software (OSS) data and resources [6]. Over 100 researchers worldwide use the archive for research in many fields. In this paper, we describe the recent changes, the work in progress, and future plans for making the archive easier to use and for allowing more advanced research to be done with the data available.},
	keywords = {forge, forges, repositories, repository, sourceforge, srda},
	attachments = {https://flosshub.org/sites/flosshub.org/files/srda2008.pdf},
	author = {Matthew Van Antwerp and Madey, Greg}
}
@conference {Alonso:2008:EIV:1370750.1370780,
	title = {Expertise identification and visualization from CVS},
	booktitle = {Proceedings of the 2008 international working conference on Mining software repositories},
	series = {MSR {\textquoteright}08},
	year = {2008},
	month = {05/2008},
	pages = {125{\textendash}128},
	publisher = {ACM},
	organization = {ACM},
	address = {New York, NY, USA},
	abstract = {As software evolves over time, the identification of expertise becomes an important problem. Component ownership and team awareness of such ownership are signals of solid project. Ownership and ownership awareness are also issues in open-source software (OSS) projects. Indeed, the membership in OSS projects is dynamic with team members arriving and leaving. In large open source projects, specialists who know the system very well are considered experts. How can one identify the experts in a project by mining a particular repository like the source code? Have they gotten help from other people?

We provide an approach using classification of the source code tree as a path to derive the expertise of the committers. Because committers may get help from other people, we also retrieve their contributors. We also provide a visualization that helps to further explore the repository via committers and categories. We present a prototype implementation that describes our research using the Apache HTTP Web server project as a case study.},
	keywords = {apache, classification, committers, components, contributors, expertise, expertise identification, repository, scm, source code},
	isbn = {978-1-60558-024-1},
	doi = {http://doi.acm.org/10.1145/1370750.1370780},
	url = {http://doi.acm.org/10.1145/1370750.1370780},
	attachments = {https://flosshub.org/sites/flosshub.org/files/p125-alonso.pdf},
	author = {Alonso, Omar and Premkumar T. Devanbu and Gertz, Michael}
}
@conference {992,
	title = {Determining Implementation Expertise from Bug Reports},
	booktitle = {Fourth International Workshop on Mining Software Repositories (MSR{\textquoteright}07:ICSE Workshops 2007)},
	year = {2007},
	pages = {2 - 2},
	publisher = {IEEE},
	organization = {IEEE},
	address = {Minneapolis, MN, USA},
	abstract = {As developers work on a software product they accumulate expertise, including expertise about the code base of the software product. We call this type of expertise "implementation expertise". Knowing the set of developers who have implementation expertise for a software product has many important uses. This paper presents an empirical evaluation of two approaches to determining implementation expertise from the data in source and bug repositories. The expertise sets created by the approaches are compared to those provided by experts and evaluated using the measures of precision and recall. We found that both approaches are good at finding all of the appropriate developers, although they vary in how many false positives are returned.},
	keywords = {bug reports, developers, eclipse, expertise, repository, scm, source code},
	isbn = {0-7695-2950-X},
	doi = {10.1109/MSR.2007.7},
	attachments = {https://flosshub.org/sites/flosshub.org/files/28300002.pdf},
	author = {Anvik, John and Murphy, Gail C.}
}
@conference {DBLP:conf/csmr/CapiluppiLM03,
	title = {Characteristics of Open Source Projects},
	booktitle = {7th European Conference on Software Maintenance and Reengineering (CSMR{\textquoteright}03)},
	year = {2003},
	note = {"We analyze a sample of around 400 projects from a popular OS project repository. "
no pdf to confirm what projects these are or what the repository is.[ms]},
	pages = {317-},
	abstract = {Most empirical studies about Open Source (OS)projects or products are vertical and usually deal with the flagship, successful projects. There is a substantial lack of horizontal studies to shed light on the whole population of projects, including failures. This paper presents a horizontal study aimed at characterizing OS projects. We analyze a sample of around 400 projects from a popular OS project repository. Each project is characterized by a number of attributes. We analyze these attributes statically and over time. The main results show that few projects are capable of attracting a meaningful community of developers. The majority of projects is made by few (in many cases one) person with a very slow pace of evolution.},
	keywords = {evolution, project success, repository},
	author = {Capiluppi, Andrea and Patricia Lago and Maurizio Morisio}
}
@article {1099,
	title = {Evidences in the evolution of OS projects through Changelog Analyses},
	journal = {Proceedings of the 3rd ICSE Workshop on Open Source},
	year = {2003},
	note = {"In this study we concentrate on a very large sample (406 projects) selected randomly from an OS portal[20]" (freshmeat)

"We define three clusters of projects: {\textquoteright}large{\textquoteright} projects as long as they are based on more than 1000KB(40KLOC)..."},
	pages = {19-24},
	abstract = {Most empirical studies about Open Source (OS) projects or products are vertical and usually deal with the flagship, successful projects. There is a substantial lack of horizontal studies to shed light on the whole population of projects, including failures. This paper presents a horizontal study aimed at characterizing OS projects. We analyze a sample of around 400 projects from a popular OS project repository. Each project is characterized by a number of attributes. We analyze these attributes statically and over time. The main results show that few projects are capable of attracting a meaningful community of developers. The majority of projects is made by few (in many cases one) person with a very slow pace of evolution. We then try to observe how many projects count on a substantial number of developers, and analyze those projects more deeply. The goal is to achieve a better insight in the dynamics of open source development. The initial results of this analysis, especially growth in code size and tendency to stability in modularity, seem to be in line with traditional close source development.},
	keywords = {classification, freshmeat, loc, modularity, repository, size, sloc, source code},
	url = {http://hdl.handle.net/10552/1037},
	attachments = {https://flosshub.org/sites/flosshub.org/files/capiluppi2003.pdf},
	author = {Capiluppi, Andrea}
}
