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19

SEKE
2004
Springer

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Automatic bug triage using text categorization

13 years 10 months ago

Automatic bug triage using text categorization

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Bug triage, deciding what to do with an incoming bug report, is taking up increasing amount of developer resources in large open-source projects. In this paper, we propose to apply machine learning techniques to assist in bug triage by using text categorization to predict the developer that should work on the bug based on the bug’s description. We demonstrate our approach on a collection of 15,859 bug reports from a large open-source project. Our evaluation shows that our prototype, using supervised Bayesian learning, can correctly predict 30% of the report assignments to developers.

Davor Cubranic, Gail C. Murphy

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Bug Reports | Bug Triage | Large Open-source Project | SEKE 2004 |

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Added	02 Jul 2010
Updated	02 Jul 2010
Type	Conference
Year	2004
Where	SEKE
Authors	Davor Cubranic, Gail C. Murphy

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