@proceedings {1758,
	title = {A Dataset of the Activity of the git Super-repository of Linux in 2012},
	year = {2015},
	month = {05/2015},
	publisher = {IEEE},
	abstract = {This dataset documents the activity in the public
portion of the git Super-repository of the Linux kernel during
2012. In a distributed version control system, such as git, the
Super-repository is the collection of all the repositories (repos)
used for development. In such a Super-repository, some repos
will be accessible only by their owners (they are private, and
are located in places that are unreachable to other users) while
others are available to other members of the team. The latter
public repositories are used as avenues through which commits
flow from one developer to another. During the last six weeks of
2011, we proceeded to automatically discover the public portion
of the Super-repository of Linux. Then, in 2012, every 3 hrs,
each of these public repositories was queried to see what new
commits it had and what commits had disappeared from it
using a process we call continuous mining. This resulted in the
identification of 533,513 different commits across 451 different
public repositories and how they propagated through the Linux
Super-repository, including the repository of Linus Torvalds (i.e.,
the main repository of the Linux kernel). This information could
help us understand how kernel contributors use git, how they
collaborate and how commits are integrated into the Linux kernel
and into the repositories of organizations that distribute the
kernel.
This dataset is at http://turingmachine.org/2015/linuxGit},
	url = {http://turingmachine.org/2015/linuxGit/msr-data-git-linux.pdf},
	attachments = {https://flosshub.org/sites/flosshub.org/files/msr-data-git-linux.pdf},
	author = {Daniel M. German and Adams, Bram and Hassan, Ahmed E.}
}
@conference {Murgia:2014:DFE:2597073.2597086,
	title = {Do Developers Feel Emotions? An Exploratory Analysis of Emotions in Software Artifacts},
	booktitle = {Proceedings of the 11th Working Conference on Mining Software Repositories},
	series = {MSR 2014},
	year = {2014},
	pages = {262{\textendash}271},
	publisher = {ACM},
	organization = {ACM},
	address = {New York, NY, USA},
	abstract = {Software development is a collaborative activity in which developers interact to create and maintain a complex software system. Human collaboration inevitably evokes emotions like joy or sadness, which can affect the collaboration either positively or negatively, yet not much is known about the individual emotions and their role for software development stakeholders. In this study, we analyze whether development artifacts like issue reports carry any emotional information about software development. This is a first step towards verifying the feasibility of an automatic tool for emotion mining in software development artifacts: if humans cannot determine any emotion from a software artifact, neither can a tool. Analysis of the Apache Software Foundation issue tracking system shows that developers do express emotions (in particular gratitude, joy and sadness). However, the more context is provided about an issue report, the more human raters start to doubt and nuance their interpretation of emotions. More investigation is needed before building a fully automatic emotion mining tool.
},
	keywords = {Emotion Mining, Empirical Software Engineer- ing, Issue Report},
	isbn = {978-1-4503-2863-0},
	doi = {10.1145/2597073.2597086},
	url = {http://doi.acm.org/10.1145/2597073.2597086},
	attachments = {https://flosshub.org/sites/flosshub.org/files/murgia.pdf},
	author = {Murgia, Alessandro and Tourani, Parastou and Adams, Bram and Ortu, Marco}
}
