@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 {943,
	title = {Automatic labeling of software components and their evolution using log-likelihood ratio of word frequencies in source code},
	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 = {175 - 178},
	publisher = {IEEE},
	organization = {IEEE},
	address = {Vancouver, BC, Canada},
	abstract = {As more and more open-source software components become available on the Internet we need automatic ways to label and compare them. For example, a developer who searches for reusable software must be able to quickly gain an understanding of retrieved components. This understanding cannot be gained at the level of source code due to the semantic gap between source code and the domain model. In this paper we present a lexical approach that uses the log-likelihood ratios of word frequencies to automatically provide labels for software components. We present a prototype implementation of our labeling/comparison algorithm and provide examples of its application. In particular, we apply the approach to detect trends in the evolution of a software system.},
	keywords = {frequency, hapax, information retrieval, java, junit, keywords, labeling, source code},
	isbn = {978-1-4244-3493-0},
	doi = {10.1109/MSR.2009.5069499},
	attachments = {https://flosshub.org/sites/flosshub.org/files/175AutomaticLabeling.pdf},
	author = {Kuhn, Adrian}
}
