Predicting the fix time of bugs

Predicting the fix time of bugs

Giger, E.
Pinzger, M.
Gall, H.C.

Electrical Engineering, Mathematics and Computer Science

Software Technology

2013-12-31

Two important questions concerning the coordination of development effort are which bugs to fix first and how long it takes to fix them. In this paper we investigate empirically the relationships between bug report attributes and the time to fix. The objective is to compute prediction models that can be used to recommend whether a new bug should and will be fixed fast or will take more time for resolution. We examine in detail if attributes of a bug report can be used to build such a recommender system. We use decision tree analysis to compute and 10-fold cross validation to test prediction models. We explore prediction models in a series of empirical studies with bug report data of six systems of the three open source projects Eclipse, Mozilla, and Gnome. Results show that our models perform significantly better than random classification. For example, fast fixed Eclipse Platform bugs were classified correctly with a precision of 0.654 and a recall of 0.692. We also show that the inclusion of postsubmission bug report data of up to one month can further improve prediction models. Preprint accepted for publication in the Proceedings of the 2nd International Workshop on Recommendation Systems for Software Engineering (RSSE), Cape Town (South Africa) May, 2010

http://resolver.tudelft.nl/uuid:dd5dca96-2c8e-4bb3-ab02-369d9540c8d7

Delft University of Technology, Software Engineering Research Group

1872-5392

Technical Report Series TUD-SERG-2010-015

Institutional Repository

report

© 2010 The Author(s) . Software Engineering Research Group, Department of Software Technology, Faculty of Electrical Engineering, Mathematics and Computer Science, Delft University of Technology