@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.}
}
