USING DATA REDUCTION TECHNIQUES FOR EFFECTIVE BUG TRIAGE

An automatic bug triage process is an inevitable step to fix the software bugs. To decrease the manual and time cost, text classification techniques are applied to perform the automatic bug triage. The main goal of essential bug triaging software is to allocate possibly experience developers to new coming bug reports. The existing bug triage approach suffers from large scale and low quality bug data. The proposed system employs the combination of feature selection algorithm (FS) and instance selection algorithm (IS) for bug triage. These data reduction techniques are used to shrink the bug data and also to enhance the accuracy. The performance of proposed system is evaluated by using Mozilla bug data set. To show the effectiveness, scales of bug data is reduced to avoid the manual and time cost, upgrades the accuracy of bug triage with standard bug data in software maintenance.