@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 {960,
	title = {A comparative exploration of FreeBSD bug lifetimes},
	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 = {106 - 109},
	publisher = {IEEE},
	organization = {IEEE},
	address = {Cape Town, South Africa},
	abstract = {In this paper, we explore the viability of mining the basic data provided in bug repositories to predict bug lifetimes. We follow the method of Lucas D. Panjer as described in his paper, Predicting Eclipse Bug Lifetimes. However, in place of Eclipse data, the FreeBSD bug repository is used. We compare the predictive accuracy of five different classification algorithms applied to the two data sets. In addition, we propose future work on whether there is a more informative way of classifying bugs than is considered by current bug tracking systems.},
	keywords = {bug reports, bug tracking, classification, eclipse, msr challenge, prediction},
	isbn = {978-1-4244-6802-7},
	doi = {10.1109/MSR.2010.5463291},
	attachments = {https://flosshub.org/sites/flosshub.org/files/106ChallengeGargi.pdf},
	author = {Bougie, Gargi and Treude, Christoph and Daniel M. German and Storey, Margaret-Anne}
}
@conference {965,
	title = {Identifying licensing of jar archives using a code-search approach},
	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 = {151 - 160},
	publisher = {IEEE},
	organization = {IEEE},
	address = {Cape Town, South Africa},
	abstract = {Free and open source software strongly promotes the reuse of source code. Some open source Java components/libraries are distributed as jar archives only containing the bytecode and some additional information. For whoever wanting to integrate this jar in her own project, it is important to determine the license(s) of the code from which the jar archive was produced, as this affects the way that such component can be used. This paper proposes an automatic approach to determine the license of jar archives, combining the use of a code-search engine with the automatic classification of licenses contained in textual flies enclosed in the jar. Results of an empirical study performed on 37 jars - from 17 different systems - indicate that this approach is able to successfully infer the jar licenses in over 95\% of the cases, but that in many cases the license in textual flies may differ from the one of the classes contained in the jar.},
	keywords = {apache, bytecode, classification, eclipse, google code, jar, java, licenses, source code},
	isbn = {978-1-4244-6802-7},
	doi = {10.1109/MSR.2010.5463282},
	attachments = {https://flosshub.org/sites/flosshub.org/files/151msr2010.pdf},
	author = {Di Penta, Massimiliano and Daniel M. German and Antoniol, Giuliano}
}
@conference {Alonso:2008:EIV:1370750.1370780,
	title = {Expertise identification and visualization from CVS},
	booktitle = {Proceedings of the 2008 international working conference on Mining software repositories},
	series = {MSR {\textquoteright}08},
	year = {2008},
	month = {05/2008},
	pages = {125{\textendash}128},
	publisher = {ACM},
	organization = {ACM},
	address = {New York, NY, USA},
	abstract = {As software evolves over time, the identification of expertise becomes an important problem. Component ownership and team awareness of such ownership are signals of solid project. Ownership and ownership awareness are also issues in open-source software (OSS) projects. Indeed, the membership in OSS projects is dynamic with team members arriving and leaving. In large open source projects, specialists who know the system very well are considered experts. How can one identify the experts in a project by mining a particular repository like the source code? Have they gotten help from other people?

We provide an approach using classification of the source code tree as a path to derive the expertise of the committers. Because committers may get help from other people, we also retrieve their contributors. We also provide a visualization that helps to further explore the repository via committers and categories. We present a prototype implementation that describes our research using the Apache HTTP Web server project as a case study.},
	keywords = {apache, classification, committers, components, contributors, expertise, expertise identification, repository, scm, source code},
	isbn = {978-1-60558-024-1},
	doi = {http://doi.acm.org/10.1145/1370750.1370780},
	url = {http://doi.acm.org/10.1145/1370750.1370780},
	attachments = {https://flosshub.org/sites/flosshub.org/files/p125-alonso.pdf},
	author = {Alonso, Omar and Premkumar T. Devanbu and Gertz, Michael}
}
@conference {Herraiz:2008:TSB:1370750.1370786,
	title = {Towards a simplification of the bug report form in eclipse},
	booktitle = {Proceedings of the 2008 international working conference on Mining software repositories},
	series = {MSR {\textquoteright}08},
	year = {2008},
	pages = {145{\textendash}148},
	publisher = {ACM},
	organization = {ACM},
	address = {New York, NY, USA},
	abstract = {We believe that the bug report form of Eclipse contains too many fields, and that for some fields, there are too many options. In this MSR challenge report, we focus in the case of the severity field. That field contains seven different levels of severity. Some of them seem very similar, and it is hard to distinguish among them. Users assign severity, and developers give priority to the reports depending on their severity. However, if users can not distinguish well among the various severity options, they will probably assign different priorities to bugs that require the same priority. We study the mean time to close bugs reported in Eclipse, and how the severity assigned by users affects this time. The results shows that classifying by time to close, there are less clusters of bugs than levels of severity. We therefore conclude that there is a need to make a simpler bug report form.},
	keywords = {bug fixing, bug report, bug tracking system, classification, eclipse, msr challenge, severity},
	isbn = {978-1-60558-024-1},
	doi = {http://doi.acm.org/10.1145/1370750.1370786},
	url = {http://doi.acm.org/10.1145/1370750.1370786},
	author = {Herraiz, Israel and Daniel M. German and Jesus M. Gonzalez-Barahona and Gregorio Robles}
}
@conference {1014,
	title = {Predicting Eclipse Bug Lifetimes},
	booktitle = {Fourth International Workshop on Mining Software RepositoriesFourth International Workshop on Mining Software Repositories (MSR{\textquoteright}07:ICSE Workshops 2007)},
	year = {2007},
	pages = {29 - 29},
	publisher = {IEEE},
	organization = {IEEE},
	address = {Minneapolis, MN, USA},
	abstract = {In non-trivial software development projects planning and allocation of resources is an important and difficult task. Estimation of work time to fix a bug is commonly used to support this process. This research explores the viability of using data mining tools to predict the time to fix a bug given only the basic information known at the beginning of a bug{\textquoteright}s lifetime. To address this question, a historical portion of the Eclipse Bugzilla database is used for modeling and predicting bug lifetimes. A bug history transformation process is described and several data mining models are built and tested. Interesting behaviours derived from the models are documented. The models can correctly predict up to 34.9\% of the bugs into a discretized log scaled lifetime class.},
	keywords = {bug fixing, bugzilla, classification, eclipse, effort estimation, mining challenge, msr challenge, prediction, weka},
	isbn = {0-7695-2950-X},
	doi = {10.1109/MSR.2007.25},
	attachments = {https://flosshub.org/sites/flosshub.org/files/28300029.pdf},
	author = {Panjer, Lucas D.}
}
@conference {993,
	title = {Spam Filter Based Approach for Finding Fault-Prone Software Modules},
	booktitle = {Fourth International Workshop on Mining Software Repositories (MSR{\textquoteright}07:ICSE Workshops 2007)},
	year = {2007},
	pages = {4 - 4},
	publisher = {IEEE},
	organization = {IEEE},
	address = {Minneapolis, MN, USA},
	abstract = {Because of the increase of needs for spam e-mail detection, the spam filtering technique has been improved as a convenient and effective technique for text mining. We propose a novel approach to detect fault-prone modules in a way that the source code modules are considered as text files and are applied to the spam filter directly. In order to show the applicability of our approach, we conducted experimental applications using source code repositories of Java based open source developments. The result of experiments shows that our approach can classify more than 75\% of software modules correctly.},
	keywords = {argouml, bug reports, classification, eclipse, java, modules, scm, spam, text mining},
	isbn = {0-7695-2950-X},
	doi = {10.1109/MSR.2007.29},
	attachments = {https://flosshub.org/sites/flosshub.org/files/28300004.pdf},
	author = {Mizuno, Osamu and Ikami, Shiro and Nakaichi, Shuya and Kikuno, Tohru}
}
@article {1253,
	title = {The many meanings of open source},
	journal = {IEEE Software},
	volume = {21},
	year = {2004},
	note = {"We determined a set of characteristics that are almost always present and others that vary among open source projects, and this serves as the core of this work"
"Section 3 describes some open source characteristics that can be used in determining whether a project is or not open source"},
	month = {01/2004},
	pages = {34 - 40},
	abstract = {The term Open Source is widely applied to describe some software development methodologies. This paper does not provide a judgment on the open source approach, but exposes the fact that simply stating that a project is open source does not provide a precise description of the approach used to support the project. By taking a multi- disciplinary point of view, we propose a collection of characteristics that are common, as well as some that vary among open source projects. The set of open source characteristics we found can be used as a tick-list both for analysing and for setting up open source projects. Our tick-list also provides a starting point for understanding the many meanings of the term open source.},
	keywords = {classification, projects, taxonomy},
	issn = {0740-7459},
	doi = {10.1109/MS.2004.1259206},
	attachments = {https://flosshub.org/sites/flosshub.org/files/gacek.pdf},
	author = {Gacek, C. and Arief, B.}
}
@article {1099,
	title = {Evidences in the evolution of OS projects through Changelog Analyses},
	journal = {Proceedings of the 3rd ICSE Workshop on Open Source},
	year = {2003},
	note = {"In this study we concentrate on a very large sample (406 projects) selected randomly from an OS portal[20]" (freshmeat)

"We define three clusters of projects: {\textquoteright}large{\textquoteright} projects as long as they are based on more than 1000KB(40KLOC)..."},
	pages = {19-24},
	abstract = {Most empirical studies about Open Source (OS) projects or products are vertical and usually deal with the flagship, successful projects. There is a substantial lack of horizontal studies to shed light on the whole population of projects, including failures. This paper presents a horizontal study aimed at characterizing OS projects. We analyze a sample of around 400 projects from a popular OS project repository. Each project is characterized by a number of attributes. We analyze these attributes statically and over time. The main results show that few projects are capable of attracting a meaningful community of developers. The majority of projects is made by few (in many cases one) person with a very slow pace of evolution. We then try to observe how many projects count on a substantial number of developers, and analyze those projects more deeply. The goal is to achieve a better insight in the dynamics of open source development. The initial results of this analysis, especially growth in code size and tendency to stability in modularity, seem to be in line with traditional close source development.},
	keywords = {classification, freshmeat, loc, modularity, repository, size, sloc, source code},
	url = {http://hdl.handle.net/10552/1037},
	attachments = {https://flosshub.org/sites/flosshub.org/files/capiluppi2003.pdf},
	author = {Capiluppi, Andrea}
}
@conference {1153,
	title = {Characterizing the OSS process},
	booktitle = {Proceedings of the 2nd ICSE Workshop on Open Source},
	year = {2002},
	note = {"We have considered two well-known Open Source portals (FreshMeat [1] and SourceForge [2] )."
"Using pseudo-random sampling we have selected a sample of 400 projects (mostly from FreshMeat). Each project is described by several variables (programming language, type of license, size of source code, type of documentation available and others). By indirect means (analysis of the Changelog file, or CVS) it is also possible to compute the number of people working on the project, and the number of external contributors. From FreshMeat we get both a vitality index, that considers the number of releases per time period, and a popularity index, which is a first measure of the interest of users to the project (project URL hits, mixed with subscriptions to it)."},
	abstract = {The Open Source model of software development has gained the attention of both the business, the practitioners{\textquoteright} and the research communities. The Open Source process has been described by the seminal paper by Eric Raymond [4] and [5]. However, sound empirical studies are still very limited [3], [6].
Our goal is to investigate the OS process by empirical means, to analyze, characterize it, and possibly model it with quantitative models. It should be noted that the Open Source process provides open process and product data, and therefore is a rare opportunity for empirical research.
Our initial research focus is on the characterization of the process, starting from the evolution of OS projects. In traditional projects, a significant number of releases in a short time is usually considered an instability factor [7] and [8], while in the OSS community, it is an evidence of vitality, shows the commitment of the authors and the power of attraction of other programmers [9]. Is it possible to characterize the vitality of projects? And, can vitality be traced to some other characteristics of a project?},
	keywords = {bugs, change log, classification, cvs, downloads, freshmeat, metadata, patches, popularity, project success, release history, sourceforge, vitality},
	attachments = {https://flosshub.org/sites/flosshub.org/files/CapiluppiLagoMorisio.pdf},
	author = {Capiluppi, Andrea and Patricia Lago and Maurizio Morisio}
}
