Predicting the severity of a reported bug

Submitted by msquire on Wed, 2011-04-13 09:50

Title	Predicting the severity of a reported bug
Publication Type	Conference Paper
Year of Publication	2010
Authors	Lamkanfi, A, Demeyer, S, Giger, E, Goethals, B
Secondary Title	2010 7th IEEE Working Conference on Mining Software Repositories (MSR 2010)2010 7th IEEE Working Conference on Mining Software Repositories (MSR 2010)
Pagination	1 - 10
Publisher	IEEE
Place Published	Cape Town, South Africa
ISBN Number	978-1-4244-6802-7
Keywords	bug reports, eclipse, gnome, mozilla, severity, text mining
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).
DOI	10.1109/MSR.2010.5463284
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