@inbook {Kerzazi2017,
	title = {Knowledge Flows Within Open Source Software Projects: A Social Network Perspective},
	booktitle = {Advances in Ubiquitous Networking 2: Proceedings of the UNet{\textquoteright}16},
	year = {2017},
	pages = {247{\textendash}258},
	publisher = {Springer Singapore},
	organization = {Springer Singapore},
	address = {Singapore},
	abstract = {Developing software is knowledge-intensive activity, requiring extensive technical knowledge and awareness. The abstract part of development is the social interactions that drive knowledge flows between contributors, especially for Open Source Software (OSS). This study investigated knowledge sharing and propagation from social perspective using social network analysis (SNA). We mined and analyzed the issue and review histories of three OSS from GitHub. Particular attention has been paid to the socio-interactions through comments from contributors on reviews. We aim at explaining the propagation and density of knowledge flows within contributor networks. The results show that review requests flow from the core contributors toward peripheral contributors and comments on reviews are in a continuous loop from the core teams to the peripherals and back; and the core contributors leverage on their awareness and technical knowledge to increase their notoriety by playing the role of communication brokers supported by comments on work items.},
	keywords = {expertise, Knowledge flows, open source, SNA},
	isbn = {978-981-10-1627-1},
	doi = {10.1007/978-981-10-1627-1_19},
	url = {http://dx.doi.org/10.1007/978-981-10-1627-1_19},
	author = {Kerzazi, Noureddine and El Asri, Ikram},
	editor = {El-Azouzi, Rachid and Menasche, Daniel Sadoc and Sabir, Essa{\"\i}d and De Pellegrini, Francesco and Benjillali, Mustapha}
}
@conference {937,
	title = {Assigning bug reports using a vocabulary-based expertise model of developers},
	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 = {131 - 140},
	publisher = {IEEE},
	organization = {IEEE},
	address = {Vancouver, BC, Canada},
	abstract = {For popular software systems, the number of daily submitted bug reports is high. Triaging these incoming reports is a time consuming task. Part of the bug triage is the assignment of a report to a developer with the appropriate expertise. In this paper, we present an approach to automatically suggest developers who have the appropriate expertise for handling a bug report. We model developer expertise using the vocabulary found in their source code contributions and compare this vocabulary to the vocabulary of bug reports. We evaluate our approach by comparing the suggested experts to the persons who eventually worked on the bug. Using eight years of Eclipse development as a case study, we achieve 33.6\% top-1 precision and 71.0\% top-10 recall.},
	keywords = {bug reports, bugzilla, develect, developers, eclipse, expertise, scm},
	isbn = {978-1-4244-3493-0},
	doi = {10.1109/MSR.2009.5069491},
	attachments = {https://flosshub.org/sites/flosshub.org/files/131AssigningBugReports.pdf},
	author = {Matter, Dominique and Kuhn, Adrian and Nierstrasz, Oscar}
}
@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 {Schuler:2008:MUE:1370750.1370779,
	title = {Mining usage expertise from version archives},
	booktitle = {Proceedings of the 2008 international working conference on Mining software repositories},
	series = {MSR {\textquoteright}08},
	year = {2008},
	month = {05/2008},
	pages = {121{\textendash}124},
	publisher = {ACM},
	organization = {ACM},
	address = {New York, NY, USA},
	abstract = {In software development, there is an increasing need to find and connect developers with relevant expertise. Existing expertise recommendation systems are mostly based on variations of the Line 10 Rule: developers who changed a file most often have the most implementation expertise. In this paper, we introduce the concept of usage expertise, which manifests itself whenever developers are using functionality, e.g., by calling API methods. We present preliminary results for the ECLIPSE project that demonstrate that our technique allows to recommend experts for files with no or little history, identify developers with similar expertise, and measure the usage of API methods.},
	keywords = {api, computer-supported cooperative work, eclipse, expertise, recommendation, scm, software repository, source code},
	isbn = {978-1-60558-024-1},
	doi = {http://doi.acm.org/10.1145/1370750.1370779},
	url = {http://doi.acm.org/10.1145/1370750.1370779},
	attachments = {https://flosshub.org/sites/flosshub.org/files/p121-schuler.pdf},
	author = {Schuler, David and Zimmermann, Thomas}
}
@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 {1015,
	title = {Mining Eclipse Developer Contributions via Author-Topic Models},
	booktitle = {Fourth International Workshop on Mining Software Repositories (MSR{\textquoteright}07:ICSE Workshops 2007)},
	year = {2007},
	pages = {30 - 30},
	publisher = {IEEE},
	organization = {IEEE},
	address = {Minneapolis, MN, USA},
	abstract = {We present the results of applying statistical author-topic models to a subset of the Eclipse 3.0 source code consisting of 2,119 source files and 700,000 lines of code from 59 developers. This technique provides an intuitive and automated framework with which to mine developer contributions and competencies from a given code base while simultaneously extracting software function in the form of topics. In addition to serving as a convenient summary for program function and developer activities, our study shows that topic models provide a meaningful, effective, and statistical basis for developer similarity analysis.},
	keywords = {contributions, developers, eclipse, expertise, mining challenge, msr challenge, source code, topics},
	isbn = {0-7695-2950-X},
	doi = {10.1109/MSR.2007.20},
	attachments = {https://flosshub.org/sites/flosshub.org/files/28300030.pdf},
	author = {Linstead, Erik and Rigor, Paul and Bajracharya, Sushil and Lopes, Cristina and Baldi, Pierre}
}
@conference {994,
	title = {Recommending Emergent Teams},
	booktitle = {Fourth International Workshop on Mining Software Repositories (MSR{\textquoteright}07:ICSE Workshops 2007)},
	year = {2007},
	pages = {5 - 5},
	publisher = {IEEE},
	organization = {IEEE},
	address = {Minneapolis, MN, USA},
	abstract = {To build successful complex software systems, developers must collaborate with each other to solve issues. To facilitate this collaboration, specialized tools, such as chat and screen sharing, are being integrated into development environments. Currently, these tools require a developer to maintain a list of other developers with whom they may wish to communicate and to determine who within this list has expertise for a specific situation. For large, dynamic projects, like several successful open-source projects, these requirements place an unreasonable burden on the developer. In this paper, we show how the structure of a team emerges from how developers change software artifacts. We introduce the Emergent Expertise Locator (EEL) that uses emergent team information to propose experts to a developer within their development environment as the developer works. We found that EEL produces, on average, results with higher precision and higher recall than an existing heuristic for expertise recommendation.},
	keywords = {bugzilla, developers, eclipse, evolution, expertise, Firefox, teams},
	isbn = {0-7695-2950-X},
	doi = {10.1109/MSR.2007.27},
	attachments = {https://flosshub.org/sites/flosshub.org/files/28300005.pdf},
	author = {Minto, Shawn and Murphy, Gail C.}
}
@article {flosswp325,
	title = {Identifying Knowledge Brokers that Yield Software Engineering Knowledge in OSS Projects},
	journal = {Information and Software Technology},
	volume = {46},
	year = {2006},
	note = {Uses the Debian mailing lists "kde", "mentor", and "user". 
the collection period was from January 2001 to September 2004},
	month = {11/2006},
	pages = {1025-1033},
	abstract = {Much research on open source software development concentrates on developer lists and other software repositories to investigate what motivates professional software developers to participate in open source software projects. Little attention has been paid to individuals who spend valuable time in lists helping participants on some mundane yet vital project activities. Using three Debian lists as a case study we investigate the impact of knowledge brokers and their associated activities in open source projects. Social network analysis was used to visualize how participants are affiliated with the lists. The network topology reveals substantial community participation. The consequence of collaborating in mundane activities for the success of open source software projects is discussed. The direct beneficiaries of this research are in the identification of knowledge experts in open source software projects.},
	keywords = {debian, email, email archives, expertise, knowledge sharing, mailing list, project success, social network analysis},
	doi = {10.1016/j.infsof.2005.12.019},
	attachments = {https://flosshub.org/sites/flosshub.org/files/IST-Vol-48-11-2006.pdf},
	author = {Sowe, Sulayman K. and Ioannis Stamelos and Lefteris Angelis}
}
