@article {1802,
	title = {Candoia: A Platform and an Ecosystem for Building and Deploying Versatile Mining Software Repositories Tools},
	year = {2015},
	note = {" In terms of its focus,
the Candoia platform is closer to Bevan et al.{\textquoteright}s Kenyon [9],
Bajracharya et al.{\textquoteright}s Sourcerer [6], Gousios and Spinellis{\textquoteright}s Alitheia
Core [32, 31], Howison et al.{\textquoteright}s FLOSSMole [39] and different from
Boetticher et al.{\textquoteright}s PROMISE Repository [69], Gonz{\'a}lez-Barahona
and Robles{\textquoteright}s open-access data repositories [29], Black Duck OpenHub
(aka Ohloh) [13], GHTorrent [30, 33], Ossher et al.{\textquoteright}s SourcererDB
[64], the SourceForge Research Data Archive (SRDA) [28],
and Boa [25]. },
	month = {11/2015},
	institution = {Iowa State University},
	abstract = {Research on mining software repositories (MSR) has shown great
promise during the last decade in solving many challenging software
engineering problems. There exists, however, a {\textquoteleft}valley of death{\textquoteright}
between these significant innovations in the MSR research and their
deployment in practice. The significant cost of converting a prototype
to software; need to provide support for a wide variety of tools
and technologies e.g. CVS, SVN, Git, Bugzilla, Jira, Issues, etc,
to improve applicability; and the high cost of customizing tools to
practitioner-specific settings are some key hurdles in transition to
practice. We describe Candoia, a platform and an ecosystem that
is aimed at bridging this valley of death between innovations in
MSR research and their deployment in practice. We have implemented
Candoia and provide facilities to build and publish MSR
ideas as Candoia apps. Our evaluation demonstrates that Candoia
drastically reduces the cost of converting an idea to an app, thus
reducing the barrier to transitioning research findings into practice.
We also see versatility, in Candoia app{\textquoteright}s ability to work with a variety
of tools and technologies that the platform supports. Finally,
we find that customizing Candoia app to fit project-specific needs
is often well within the grasp of developers.},
	keywords = {Analysis of software and its evolution, Application specific development environments, flossmole cited, msr, research to practice, software evolution, software repositories},
	url = {http://lib.dr.iastate.edu/cgi/viewcontent.cgi?article=1378\&context=cs_techreports},
	attachments = {https://flosshub.org/sites/flosshub.org/files/Candoia-\%20A\%20Platform\%20and\%20an\%20Ecosystem\%20for\%20Building\%20and\%20Deploying\%20V.pdf},
	author = {Nitin M. Tiwari and Dalton D. Mills and Ganesha Upadhyaya and Eric Lin and Rajan, Hridesh}
}
@conference {1406,
	title = {Process Mining Software Repositories},
	booktitle = {15th European Conference on Software Maintenance and Reengineering (CSMR 2011) },
	year = {2011},
	pages = {5 - 14},
	publisher = {IEEE},
	organization = {IEEE},
	address = {Oldenburg, Germany},
	abstract = {Software developers{\textquoteright} activities are in general recorded in software repositories such as version control systems, bug trackers and mail archives. While abundant information is usually present in such repositories, successful information extraction is often challenged by the necessity to simultaneously analyze different repositories and to combine the information obtained.

We propose to apply process mining techniques, originally developed for business process analysis, to address this challenge. However, in order for process mining to become applicable, different software repositories should be combined, and {\textquotedblleft}related{\textquotedblright} software development events should be matched: e.g., mails sent about a file, modifications of the file and bug reports that can be traced back to it.

The combination and matching of events has been implemented in FRASR (FRamework for Analyzing Software Repositories), augmenting the process mining framework ProM. FRASR has been successfully applied in a series of case studies addressing such aspects of the development process as roles of different developers and the way bug reports are handled.},
	keywords = {amsn, email, email archives, gcc, mailing list, Process mining, software repositories},
	isbn = {978-1-61284-259-2},
	doi = {10.1109/CSMR.2011.5},
	attachments = {https://flosshub.org/sites/flosshub.org/files/2011-03_CSMR.pdf},
	author = {Poncin, Wouter and Serebrenik, Alexander and Brand, Mark van den}
}
@article {Beecher2009739,
	title = {Identifying exogenous drivers and evolutionary stages in FLOSS projects},
	journal = {Journal of Systems and Software},
	volume = {82},
	number = {5},
	year = {2009},
	pages = {739 - 750},
	abstract = {The success of a Free/Libre/Open Source Software (FLOSS) project has been evaluated in the past through the number of commits made to its configuration management system, number of developers and number of users. Most studies, based on a popular FLOSS repository (SourceForge), have concluded that the vast majority of projects are failures. This study{\textquoteright}s empirical results confirm and expand conclusions from an earlier and more limited work. Not only do projects from different repositories display different process and product characteristics, but a more general pattern can be observed. Projects may be considered as early inceptors in highly visible repositories, or as established projects within desktop-wide projects, or finally as structured parts of FLOSS distributions. These three possibilities are formalized into a framework of transitions between repositories. The framework developed here provides a wider context in which results from FLOSS repository mining can be more effectively presented. Researchers can draw different conclusions based on the overall characteristics studied about an Open Source software project{\textquoteright}s potential for success, depending on the repository that they mine. These results also provide guidance to OSS developers when choosing where to host their project and how to distribute it to maximize its evolutionary success.},
	keywords = {developers, forge, forges, repositories, repository, scm, software repositories, sourceforge, success, users},
	issn = {0164-1212},
	doi = {DOI: 10.1016/j.jss.2008.10.026},
	url = {http://www.sciencedirect.com/science/article/B6V0N-4TVTJFS-1/2/e32ecee1bcb54bd4a5dff6d5e3daca8d},
	author = {Karl Beecher and Capiluppi, Andrea and Boldyreff, Cornelia}
}
@conference {Sager:2006:DSJ:1137983.1138000,
	title = {Detecting similar Java classes using tree algorithms},
	booktitle = {Proceedings of the 2006 international workshop on Mining software repositories},
	series = {MSR {\textquoteright}06},
	year = {2006},
	pages = {65{\textendash}71},
	publisher = {ACM},
	organization = {ACM},
	address = {New York, NY, USA},
	abstract = {Similarity analysis of source code is helpful during development to provide, for instance, better support for code reuse. Consider a development environment that analyzes code while typing and that suggests similar code examples or existing implementations from a source code repository. Mining software repositories by means of similarity measures enables and enforces reusing existing code and reduces the developing effort needed by creating a shared knowledge base of code fragments. In information retrieval similarity measures are often used to find documents similar to a given query document. This paper extends this idea to source code repositories. It introduces our approach to detect similar Java classes in software projects using tree similarity algorithms. We show how our approach allows to find similar Java classes based on an evaluation of three tree-based similarity measures in the context of five user-defined test cases as well as a preliminary software evolution analysis of a medium-sized Java project. Initial results of our technique indicate that it (1) is indeed useful to identify similar Java classes, (2)successfully identifies the ex ante and ex post versions of refactored classes, and (3) provides some interesting insights into within-version and between-version dependencies of classes within a Java project.},
	keywords = {change analysis, clones, coogle, eclipse, famix, java, similarity, software evolution, software repositories, source code, tree similarity measures},
	isbn = {1-59593-397-2},
	doi = {http://doi.acm.org/10.1145/1137983.1138000},
	url = {http://doi.acm.org/10.1145/1137983.1138000},
	attachments = {https://flosshub.org/sites/flosshub.org/files/65Detecting.pdf},
	author = {Sager, Tobias and Bernstein, Abraham and Pinzger, Martin and Kiefer, Christoph}
}
