TY  - JOUR
T1  - Auto-Bug Triager for Assisting Manual Bug Triage
AU - Kirubakaran, S. AU - Maheswari, K. AU - Revathi, K. Reshma 
JO  - Asian Journal of Information Technology
VL  - 15
IS  - 8
SP  - 1334
EP  - 1339
PY  - 2016
DA  - 2001/08/19
SN  - 1682-3915
DO  - ajit.2016.1334.1339
UR  - https://makhillpublications.co/view-article.php?doi=ajit.2016.1334.1339
KW  - Bug Triage process
KW  -manual triaging
KW  -data mining techniques
KW  -data reduction
KW  -India
AB  - Bug triage is an unescapable process in every software organization. A separate team in every software companies takes care of this process. The complete process occurs in manual which increases the production time and cost. One of the time taking tasks in bug triage process is assigning an appropriate developer to fix the new coming bugs than fixing that bug. Automation is the key solution for this problem. Since the bug reports are in free form of data, it is efficient to use data mining techniques to handle. In recent research, different techniques were applied by different authors trying to automate the bug triage process. But, up till now only 64% of triaging accuracy is achieved. Our survey shows that the decrease in accuracy is caused by one of the major problem called data reduction. In this study, we proposed a new framework called Auto-BugTriager which focuses on the elimination of data reduction problem to greater extent. Auto-BugTriager consist of three phases namely InfoZie, DataReduction and NBClassifier which works together to predict the recommendation list of expert developer for fixing the new bug. We have done the complete theoretical and experimental analysis of the proposed framework. Our analysis shows, that the proposed framework eliminated the problem of data reduction to greater extent, thus the data quality and accuracy of bug triage is increased.
ER  -