@conference {932,
	title = {Mining the coherence of GNOME bug reports with statistical topic models},
	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 = {99 - 102},
	publisher = {IEEE},
	organization = {IEEE},
	address = {Vancouver, BC, Canada},
	abstract = {We adapt latent Dirichlet allocation to the problem of mining bug reports in order to define a new information-theoretic measure of coherence. We then apply our technique to a snapshot of the GNOME Bugzilla database consisting of 431,863 bug reports for multiple software projects. In addition to providing an unsupervised means for modeling report content, our results indicate substantial promise in applying statistical text mining algorithms for estimating bug report quality. Complete results are available from our supplementary materials Web site at http://sourcerer.ics.uci.edu/msr2009/gnome_coherence.html.},
	keywords = {bug reports, bugzilla, gnome, msr challenge, quality, sourcerer},
	isbn = {978-1-4244-3493-0},
	doi = {10.1109/MSR.2009.5069486},
	author = {Linstead, Erik and Baldi, Pierre}
}
@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 {1066,
	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)},
	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 re-use. 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, java, java.net, source code, sourceforge, sourcerer},
	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 {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}
}
