Title :
Where Should We Fix This Bug? A Two-Phase Recommendation Model
Author :
Dongsun Kim ; Yida Tao ; Sunghun Kim ; Zeller, A.
Author_Institution :
Dept. of Comput. Sci. & Eng., Hong Kong Univ. of Sci. & Technol., Kowloon, China
Abstract :
To support developers in debugging and locating bugs, we propose a two-phase prediction model that uses bug reports\´ contents to suggest the files likely to be fixed. In the first phase, our model checks whether the given bug report contains sufficient information for prediction. If so, the model proceeds to predict files to be fixed, based on the content of the bug report. In other words, our two-phase model "speaks up" only if it is confident of making a suggestion for the given bug report; otherwise, it remains silent. In the evaluation on the Mozilla "Firefox" and "Core" packages, the two-phase model was able to make predictions for almost half of all bug reports; on average, 70 percent of these predictions pointed to the correct files. In addition, we compared the two-phase model with three other prediction models: the Usual Suspects, the one-phase model, and BugScout. The two-phase model manifests the best prediction performance.
Keywords :
formal verification; program debugging; BugScout; Core packages; Firefox packages; Mozilla packages; bug report; debugging; speaks up; two-phase model; two-phase prediction model; two-phase recommendation model; Computational modeling; Computer bugs; Data mining; Feature extraction; Noise; Predictive models; Software; Bug reports; machine learning; patch file prediction;
Journal_Title :
Software Engineering, IEEE Transactions on
DOI :
10.1109/TSE.2013.24