@proceedings {1902,
	title = {Assessing Code Authorship: The Case of the Linux Kernel},
	volume = {496},
	year = {2017},
	month = {05/2017},
	pages = {151-163},
	publisher = {Springer},
	abstract = {Code authorship is a key information in large-scale open-source systems. Among others, it allows maintainers to assess division of work and identify key collaborators. Interestingly, open-source communities lack guidelines on how to manage authorship. This could be mitigated by setting to build an empirical body of knowledge on how authorship-related measures evolve in successful open-source communities. Towards that direction, we perform a case study on the Linux kernel. Our results show that: (a) only a small portion of developers (26\%) makes significant contributions to the code base; (b) the distribution of the number of files per author is highly skewed{\textemdash}a small group of top-authors (3\%) is responsible for hundreds of files, while most authors (75\%) are responsible for at most 11 files; (c) most authors (62\%) have a specialist profile; (d) authors with a high number of co-authorship connections tend to collaborate with others with less connections.},
	keywords = {code authorship, developer network, linux kernel},
	doi = {10.1007/978-3-319-57735-7_15},
	url = {https://link.springer.com/chapter/10.1007/978-3-319-57735-7_15},
	author = {Guilherme Avelino and Passos, Leonardo and Andre Hora and Marco Tulio Valente}
}
@proceedings {1573,
	title = {"A bit of code": How the Stack Overflow Community Creates Quality Postings},
	year = {2014},
	month = {01/2014},
	pages = {1425-1434},
	publisher = {IEEE Computer Society},
	abstract = {The Stack Overflow web site is an online community where programmers can ask and answer one another{\textquoteright}s questions, earning points and badges. The site offers guidance in the form of a Frequently Asked Questions (FAQ), beginning with "What kind of questions can I ask here?" The answer explains that "the best Stack Overflow questions have a bit of source code in them". This paper explores the role of source code and non-source code text on Stack Overflow in both questions and answers. The primary contribution of this paper is to provide a more detailed understanding of whether the presence of source code (and how much) actually will produce the "best" Stack Overflow questions or answers. A second contribution of this paper is to determine how the non-code portions of the text might also contribute the "best" Stack Overflow postings.  },
	keywords = {COLLABORATION, collaborative development, data mining, developer network, knowledge collaboration, open content, text mining},
	doi = {http://dx.doi.org/10.1109/HICSS.2014.185},
	attachments = {https://flosshub.org/sites/flosshub.org/files/hicssSMFinalWatermark.pdf},
	author = {Squire, Megan and Funkhouser, Christian}
}
@conference {Meneely:2011:SDN:1985793.1985832,
	title = {Socio-technical developer networks: should we trust our measurements?},
	booktitle = {Proceedings of the 33rd International Conference on Software Engineering},
	series = {ICSE {\textquoteright}11},
	year = {2011},
	pages = {281{\textendash}290},
	publisher = {ACM},
	organization = {ACM},
	address = {New York, NY, USA},
	abstract = {Software development teams must be properly structured to provide effectiv collaboration to produce quality software. Over the last several years, social network analysis (SNA) has emerged as a popular method for studying the collaboration and organization of people working in large software development teams. Researchers have been modeling networks of developers based on socio-technical connections found in software development artifacts. Using these developer networks, researchers have proposed several SNA metrics that can predict software quality factors and describe the team structure. But do SNA metrics measure what they purport to measure? The objective of this research is to investigate if SNA metrics represent socio-technical relationships by examining if developer networks can be corroborated with developer perceptions. To measure developer perceptions, we developed an online survey that is personalized to each developer of a development team based on that developer{\textquoteright}s SNA metrics. Developers answered questions about other members of the team, such as identifying their collaborators and the project experts. A total of 124 developers responded to our survey from three popular open source projects: the Linux kernel, the PHP programming language, and the Wireshark network protocol analyzer. Our results indicate that connections in the developer network are statistically associated with the collaborators whom the developers named. Our results substantiate that SNA metrics represent socio-technical relationships in open source development projects, while also clarifying how the developer network can be interpreted by researchers and practitioners.},
	keywords = {developer network, developers, linux, linux kernel, PHP, social network analysis, Survey, wireshark},
	isbn = {978-1-4503-0445-0},
	doi = {10.1145/1985793.1985832},
	url = {http://doi.acm.org/10.1145/1985793.1985832},
	author = {Meneely, Andrew and Williams, Laurie}
}
