A novel framework for labelling Duplicate and Non-Duplicate bugs
Manju Rohil, Sunesh Sunesh, Kulbhushan Bansal, Harish Rohil · International Journal of Intelligent Systems Technologies and Applications · 2023
Bug handling is an essential part in the software development life cycle. It can be very cumbersome, tedious and error-prone due to the complexity and size of software projects and teams. Duplicate bugs make the bug handling process even more tedious. In this paper, binary duplicate detection and ranking-based duplicate detection mechanisms have been combined together to deal with a two way duplication mechanisms. A novel framework has been proposed which predicts the label (duplicate or non-duplicate) for any newly arrived bug report. Further, if found as duplicate, the proposed framework produces a ranked list of bug reports which might be similar to the duplicate predicted bug report. The proposed framework has been experimentally validated using bug reports obtained from Eclipse, NetBeans and Mozilla Firefox projects of Bugzilla repository. From the experimental evaluations, we observed that deep learning-based models outperform traditional machine learning algorithms in bug report classification.