@conference {1305,
	title = {Visualizing collaboration and influence in the open-source software community},
	booktitle = {Proceedings of the 8th working conference on Mining software repositories - MSR {\textquoteright}11},
	year = {2011},
	note = {"This data set includes the complete social graph of 500,000 follow links as well as over 1,000,000 commits and 50,000 users."

"...a large fraction of [GitHub] users provide a location in their profile, which we can turn into geographic coordinates using a geocoding API like PlaceFinder...

"For each repository, we extract the owner, collaborator, and contributor usernames, plus branch names. New user- names help to find new repositories, while branch names are used to fetch commit metadata. Using this method, the crawler uncovered 40,860 code repositories, representing 33,388 unique project names and 1,219,872 individual commits."

"In addition to crawled data, we use the complete GitHub user follower graph from Jan 19, 2011. This graph includes 452,248 links connecting 106,247 unique users, 47\% (49,500) of which could be geocoded with the PlaceFinder API"},
	month = {05/2011},
	pages = {223-226},
	publisher = {ACM Press},
	organization = {ACM Press},
	address = {New York, New York, USA},
	abstract = {We apply visualization techniques to user profiles and repository metadata from the GitHub source code hosting service. Our motivation is to identify patterns within this development community that might otherwise remain obscured. Such patterns include the effect of geographic distance on developer relationships, social connectivity and influence among cities, and variation in project-specific contribution styles (e.g., centralized vs. distributed). Our analysis examines directed graphs in which nodes represent users{\textquoteright} geographic locations and edges represent (a) follower relationships, (b) successive commits, or (c) contributions to the same project. We inspect this data using a set of visualization techniques: geo-scatter maps, small multiple displays, and matrix diagrams. Using these representations, and tools based on them, we develop hypotheses about the larger GitHub community that would be difficult to discern using traditional lists, tables, or descriptive statistics. These methods are not intended to provide conclusive answers; instead, they provide a way for researchers to explore the question space and communicate initial insights.},
	keywords = {COLLABORATION, data exploration, geography, geoscatter, github, graph, mapping, metadata, open source, social graph, user profiles, visualization},
	isbn = {9781450305747},
	doi = {10.1145/1985441.1985476},
	url = {http://vis.stanford.edu/files/2011-GotHub-MSR.pdf},
	author = {Marschner, Eli and Rosenfeld, Evan and Heer, Jeffrey and Heller, Brandon}
}
@conference {957,
	title = {Assessment of issue handling efficiency},
	booktitle = {2010 7th IEEE Working Conference on Mining Software Repositories (MSR 2010)2010 7th IEEE Working Conference on Mining Software Repositories (MSR 2010)},
	year = {2010},
	pages = {94 - 97},
	publisher = {IEEE},
	organization = {IEEE},
	address = {Cape Town, South Africa},
	abstract = {We mined the issue database of GNOME to assess how issues are handled. How many issues are submitted and resolved? Does the backlog grow or decrease? How fast are issues resolved? Does issue resolution speed increase or decrease over time? In which subproject are issues handled most efficiently? To answer such questions, we apply several visualization and quantification instruments to the raw issue data. In particular, we aggregate issues into four risk categories, based on their resolution time. These categories are the basis both for visualizing and ranking, which are used in concert for issue database exploration.},
	keywords = {bug reports, bug tracking, classification, gnome, msr challenge, visualization},
	isbn = {978-1-4244-6802-7},
	doi = {10.1109/MSR.2010.5463292},
	attachments = {https://flosshub.org/sites/flosshub.org/files/94bluijtenMSR2010.pdf},
	author = {Luijten, Bart and Visser, Joost and Zaidman, Andy}
}
@conference {933,
	title = {Visualizing Gnome with the Small Project Observatory},
	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 = {103 - 106},
	publisher = {IEEE},
	organization = {IEEE},
	address = {Vancouver, BC, Canada},
	abstract = {We analyzed the gnome family of systems with the small project observatory, our online ecosystem visualization platform. We begin by briefly introducing the model of SPO. We then observe and discuss several phases in the activity of the gnome ecosystem. We follow and look at how the contributors are distributed between writing source code and doing other activities such as internationalization. We end with a visual overview of the activity of more than 900 contributors in the 10 years of existence of gnome.},
	keywords = {bugzilla, contributions, gnome, msr challenge, spo, visualization},
	isbn = {978-1-4244-3493-0},
	doi = {10.1109/MSR.2009.5069487},
	attachments = {https://flosshub.org/sites/flosshub.org/files/103Lung2009a.pdf},
	author = {Lungu, Mircea and Malnati, Jacopo and Lanza, Michele}
}
@conference {998,
	title = {Visual Data Mining in Software Archives to Detect How Developers Work Together},
	booktitle = {Fourth International Workshop on Mining Software RepositoriesFourth International Workshop on Mining Software Repositories (MSR{\textquoteright}07:ICSE Workshops 2007)},
	year = {2007},
	pages = {9 - 9},
	publisher = {IEEE},
	organization = {IEEE},
	address = {Minneapolis, MN, USA},
	abstract = {Analyzing the check-in information of open source software projects which use a version control system such as CVS or SUBVERSION can yield interesting and important insights into the programming behavior of developers. As in every major project tasks are assigned to many developers, the development must be coordinated between these programmers.

This paper describes three visualization techniques that help to examine how programmers work together, e.g. if they work as a team or if they develop their part of the software separate from each other. Furthermore, phases of stagnation in the lifetime of a project can be uncovered and thus, possible problems are revealed.

To demonstrate the usefulness of these visualization techniques we performed case studies on two open source projects. In these studies interesting patterns of developers? behavior, e.g. the specialization on a certain module can be observed. Moreover, modules that have been changed by many developers can be identified as well as such ones that have been altered by only one programmer.},
	keywords = {change, coordination, cvs, developers, junit, modules, scm, source code, svn, teams, tomcat, visualization},
	isbn = {0-7695-2950-X},
	doi = {10.1109/MSR.2007.34},
	attachments = {https://flosshub.org/sites/flosshub.org/files/28300009.pdf},
	author = {Weissgerber, Peter and Pohl, Mathias and Burch, Michael}
}
@conference {D{\textquoteright}Ambros:2006:AER:1137983.1138029,
	title = {Applying the evolution radar to PostgreSQL},
	booktitle = {Proceedings of the 2006 international workshop on Mining software repositories},
	series = {MSR {\textquoteright}06},
	year = {2006},
	pages = {177{\textendash}178},
	publisher = {ACM},
	organization = {ACM},
	address = {New York, NY, USA},
	keywords = {cvs, documentation, evolution, evolution radar, logical coupling, makefile, mining challenge, msr challenge, postgresql, re-engineering, refactoring, release history, rhdb, source code, version control, visualization},
	isbn = {1-59593-397-2},
	doi = {http://doi.acm.org/10.1145/1137983.1138029},
	url = {http://doi.acm.org/10.1145/1137983.1138029},
	attachments = {https://flosshub.org/sites/flosshub.org/files/177ApplyingEvolution.pdf},
	author = {D{\textquoteright}Ambros, Marco and Lanza, Michele}
}
@conference {Beyer:2006:CVA:1137983.1138023,
	title = {Co-change visualization applied to PostgreSQL and ArgoUML: (MSR challenge report)},
	booktitle = {Proceedings of the 2006 international workshop on Mining software repositories},
	series = {MSR {\textquoteright}06},
	year = {2006},
	pages = {165{\textendash}166},
	publisher = {ACM},
	organization = {ACM},
	address = {New York, NY, USA},
	abstract = {Co-change visualization is a method to recover the subsystem structure of a software system from the version history, based on common changes and visual clustering. This paper presents the results of applying the tool CCVisu which implements co-change visualization, to the two open-source software systems PostgreSQL and ArgoUML The input of the method is the co-change graph, which can be easily extracted by CCVisu from a Cvs version repository. The output is a graph layout that places software artifacts that were often commonly changed at close positions, and artifacts that were rarely co-changed at distant positions. This property of the layout is due to the clustering property of the underlying energy model,which evaluates the quality of a produced layout. The layout can be displayed on the screen, or saved to a file in SVG or VRML format.},
	keywords = {argouml, ccvisu, cvs, force-directed graph layout, graph, mining challenge, msr challenge, postgresql, software clustering, software structure analysis, software visualization, version control, visualization},
	isbn = {1-59593-397-2},
	doi = {http://doi.acm.org/10.1145/1137983.1138023},
	url = {http://doi.acm.org/10.1145/1137983.1138023},
	attachments = {https://flosshub.org/sites/flosshub.org/files/165Co-Change.pdf},
	author = {Beyer, Dirk}
}
@conference {D{\textquoteright}Ambros:2006:ERV:1137983.1137992,
	title = {The evolution radar: visualizing integrated logical coupling information},
	booktitle = {Proceedings of the 2006 international workshop on Mining software repositories},
	series = {MSR {\textquoteright}06},
	year = {2006},
	pages = {26{\textendash}32},
	publisher = {ACM},
	organization = {ACM},
	address = {New York, NY, USA},
	abstract = {In software evolution research logical coupling has extensively been used to recover the hidden dependencies between source code artifacts. They would otherwise go lost because of the file-based nature of current versioning systems. Previous research has dealt with low-level couplings between files, leading to an explosion of data to be analyzed, or has abstracted the logical couplings to module level, leading to a loss of detailed information. In this paper we propose a visualization-based approach which integrates both file-level and module-level logical coupling information. This not only facilitates an in-depth analysis of the logical couplings at all granularity levels, it also leads to a precise characterization of the system modules in terms of their logical coupling dependencies.},
	keywords = {change management, cvs, evolution, logical coupling, mozilla, scm, source code, thunderbird, tinderbox, visualization},
	isbn = {1-59593-397-2},
	doi = {http://doi.acm.org/10.1145/1137983.1137992},
	url = {http://doi.acm.org/10.1145/1137983.1137992},
	attachments = {https://flosshub.org/sites/flosshub.org/files/26TheEvolutionRadar.pdf},
	author = {D{\textquoteright}Ambros, Marco and Lanza, Michele and Lungu, Mircea}
}
@conference {Voinea:2006:MSR:1137983.1138024,
	title = {Mining software repositories with CVSgrab},
	booktitle = {Proceedings of the 2006 international workshop on Mining software repositories},
	series = {MSR {\textquoteright}06},
	year = {2006},
	pages = {167{\textendash}168},
	publisher = {ACM},
	organization = {ACM},
	address = {New York, NY, USA},
	keywords = {argouml, cvs, cvsgrab, evolution, mining challenge, msr challenge, postgresql, software visualization, source code, team, visualization},
	isbn = {1-59593-397-2},
	doi = {http://doi.acm.org/10.1145/1137983.1138024},
	url = {http://doi.acm.org/10.1145/1137983.1138024},
	attachments = {https://flosshub.org/sites/flosshub.org/files/167MiningSoftware.pdf},
	author = {Voinea, Lucian and Telea, Alexandru}
}
