@conference {LamkanfiMSR2010,
	title = {Predicting the Severity of a Reported Bug},
	booktitle = {Proceedings {MSR}{\textquoteright}10 (7th IEEE Working Conference on Mining Software Repositories)},
	year = {2010},
	note = {[Acceptance ratio: 16/51 = 31.4\%]},
	publisher = {IEEE Press},
	organization = {IEEE Press},
	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).},
	author = {Lamkanfi, Ahmed and Serge Demeyer and Emanuel Giger and Bart Goethals}
}
