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TitlePredicting the Severity of a Reported Bug
Author(s)Ahmed Lamkanfi, Serge Demeyer, Emanuel Giger and Bart Goethals
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AbstractThe 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)
BibTeX
@inproceedings{LamkanfiMSR2010,
	author = {Ahmed Lamkanfi, Serge Demeyer, Emanuel Giger and Bart Goethals},
	title = {Predicting the Severity of a Reported Bug},
	booktitle = {Proceedings MSR'10 (7th IEEE Working Conference on Mining Software Repositories)},
	month = {May},
	publisher = {IEEE Press},
	year = {2010},
	note = {}
}
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 Lab On REengineering - Antwerpen, last modified 12:35:26 17 August 2010