@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} }