@conference {1823,
	title = {"May the fork be with you": novel metrics to analyze collaboration on GitHub},
	booktitle = {Proceedings of the 5th International Workshop on Emerging Trends in Software Metrics - WETSoM 2014},
	year = {2014},
	note = {"According to FLOSSmole [8] (Free Libre OpenSource Software)
statistics, GitHub had 191765 repositories publicly
available at May 2012."},
	pages = {37 - 43},
	publisher = {ACM Press},
	organization = {ACM Press},
	address = {New York, New York, USA},
	abstract = {Multi{\textendash}repository software projects are becoming more and
more popular, thanks to web{\textendash}based facilities such as GitHub.
Code and process metrics generally assume a single repository
must be analyzed, in order to measure the characteristics
of a codebase. Thus they are not apt to measure how
much relevant information is hosted in multiple repositories
contributing to the same codebase. Nor can they feature
the characteristics of such a distributed development process.
We present a set of novel metrics, based on an original
classification of commits, conceived to capture some interesting
aspects of a multi{\textendash}repository development process. We
also describe an efficient way to build a data structure that
allows to compute these metrics on a set of Git repositories.
Interesting outcomes, obtained by applying our metrics
on a large sample of projects hosted on GitHub, show the
usefulness of our contribution.},
	keywords = {flossmole, github},
	isbn = {9781450328548},
	doi = {10.1145/2593868.2593875},
	url = {http://marbiaz.github.io/docs/Biazzini14b.pdf},
	author = {Marco Biazzini and Benoit Baudry}
}
@conference {Zhang:2008:ISG:1370750.1370785,
	title = {An initial study of the growth of eclipse defects},
	booktitle = {Proceedings of the 2008 international working conference on Mining software repositories},
	series = {MSR {\textquoteright}08},
	year = {2008},
	pages = {141{\textendash}144},
	publisher = {ACM},
	organization = {ACM},
	address = {New York, NY, USA},
	abstract = {We analyze the Eclipse defect data from June 2004 to November 2007, and find that the growth of the number of defects can be well modeled by polynomial functions. Furthermore, we can predict the number of future Eclipse defects based on the nature of defect growth.},
	keywords = {bug reports, defect growth model, defect prediction, eclipse, msr challenge, polynomial regression},
	isbn = {978-1-60558-024-1},
	doi = {http://doi.acm.org/10.1145/1370750.1370785},
	url = {http://doi.acm.org/10.1145/1370750.1370785},
	author = {Zhang, Hongyu}
}
