@conference {949,
	title = {Predicting the severity of a reported bug},
	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 = {1 - 10},
	publisher = {IEEE},
	organization = {IEEE},
	address = {Cape Town, South Africa},
	abstract = {The severity of a reported bug is a critical factor in deciding how soon it needs to be fixed. Unfortunately, while clear guidelines exist on how to assign the severity of a bug, it remains an inherent manual process left to the person reporting the bug. In this paper we investigate whether we can accurately predict the severity of a reported bug by analyzing its textual description using text mining algorithms. Based on three cases drawn from the open-source community (Mozilla, Eclipse and GNOME), we conclude that given a training set of sufficient size (approximately 500 reports per severity), it is possible to predict the severity with a reasonable accuracy (both precision and recall vary between 0.65-0.75 with Mozilla and Eclipse; 0.70-0.85 in the case of GNOME).},
	keywords = {bug reports, eclipse, gnome, mozilla, severity, text mining},
	isbn = {978-1-4244-6802-7},
	doi = {10.1109/MSR.2010.5463284},
	attachments = {https://flosshub.org/sites/flosshub.org/files/1lamkanfiDemeyer1.pdf},
	author = {Lamkanfi, Ahmed and Demeyer, Serge and Giger, Emanuel and Goethals, Bart}
}
