Last updated on Monday, October 06, 2025
@inproceedings{LamkanfiMSR2010,
author = {Ahmed Lamkanfi and Serge Demeyer and Emanuel Giger and
Bart Goethals},
booktitle = {Proceedings {MSR}'10 (7th {IEEE} Working Conference
on Mining Software Repositories)},
month = may,
note = {Acceptance ratio: 16/51 = 31.4\%},
publisher = {{IEEE} Press},
title = {Predicting the Severity of a Reported Bug},
year = {2010},
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).},
annote = {internationalconference},
}