@conference {Rastkar:2010:SSA:1806799.1806872,
	title = {Summarizing software artifacts: a case study of bug reports},
	booktitle = {Proceedings of the 32nd ACM/IEEE International Conference on Software Engineering - Volume 1},
	series = {ICSE {\textquoteright}10},
	year = {2010},
	pages = {505{\textendash}514},
	publisher = {ACM},
	organization = {ACM},
	address = {New York, NY, USA},
	abstract = {Many software artifacts are created, maintained and evolved as part of a software development project. As software developers work on a project, they interact with existing project artifacts, performing such activities as reading previously filed bug reports in search of duplicate reports. These activities often require a developer to peruse a substantial amount of text. In this paper, we investigate whether it is possible to summarize software artifacts automatically and effectively so that developers could consult smaller summaries instead of entire artifacts. To provide focus to our investigation, we consider the generation of summaries for bug reports. We found that existing conversation-based generators can produce better results than random generators and that a generator trained specifically on bug reports can perform statistically better than existing conversation-based generators. We demonstrate that humans also find these generated summaries reasonable indicating that summaries might be used effectively for many tasks.},
	keywords = {bug reports, eclipse, gnome, human-centric software engineering, kde, machine learning, mozilla},
	isbn = {978-1-60558-719-6},
	doi = {10.1145/1806799.1806872},
	url = {http://doi.acm.org/10.1145/1806799.1806872},
	author = {Rastkar, Sarah and Murphy, Gail C. and Murray, Gabriel}
}
@conference {939,
	title = {On what basis to recommend: Changesets or interactions?},
	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 = {155 - 158},
	publisher = {IEEE},
	organization = {IEEE},
	address = {Vancouver, BC, Canada},
	abstract = {Different flavours of recommendation systems have been proposed to help software developers perform software evolution tasks. A number of these recommendation systems are based on changesets. When changeset information is used, recommendations are based on only the end result of the activity undertaken to complete a task. In this paper, we report on an investigation that compared how recommendations based on changesets compare to recommendations based on interactions collected as a programmer performed the task that resulted in a changeset. To provide a common basis for the comparison, our investigation considered how bug reports considered similar based on changeset information compare to bug reports considered similar based on interaction information. We found that there is no direct relationship between the bug reports found similar with the different methods, suggesting that each comparison methods captures a different aspect of the problem.},
	keywords = {bug reports, changeset, eclipse, mylyn},
	isbn = {978-1-4244-3493-0},
	doi = {10.1109/MSR.2009.5069494},
	author = {Rastkar, Sarah and Murphy, Gail C.}
}
