Effective Bug Triage Using Cold-Start Recommendation System

  • Rajusekhar Alle Savitribai Phule Pune University AISSMS COE, Pune, India
  • Aditya Aranya Savitribai Phule Pune University AISSMS COE, Pune, India
  • Abhishek Thakur Savitribai Phule Pune University AISSMS COE, Pune, India
  • Mr. Anilkumar J Kadam Savitribai Phule Pune University AISSMS COE, Pune, India
DOI: https://doi.org/10.53555/cse.v2i3.580
Keywords: Instance Selection, Feature Selection, Naive Bayesian Classifier, Bug triage, Prediction for reduction orders.

Abstract

Over 40-50% cost is spent in dealing with software bugs in Software companies. An
inevitable step of fixing bugs is bug triage, which aims to correctly assign a developer
to a new bug. To decrease the time cost in manual work, text classification techniques
are applied to implement automatic bug triage. A system can be constructed which will
address the problem of data reduction for bug triage, i.e., how to reduce the scale and
improve the quality of bug data. A combination of instance selection and feature
selection can be used simultaneously to reduce data scale on the bug dimension and the
word dimension. And this system will solve the Cold-Start Problem encountered in the
current system at the starting phase when there is no trained dataset and this system
will use designation-matching.

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Author Biographies

Rajusekhar Alle, Savitribai Phule Pune University AISSMS COE, Pune, India

Department of Computer Engineering, Savitribai Phule Pune University AISSMS COE, Pune, India

Aditya Aranya, Savitribai Phule Pune University AISSMS COE, Pune, India

Department of Computer Engineering, Savitribai Phule Pune University AISSMS COE, Pune, India

Abhishek Thakur, Savitribai Phule Pune University AISSMS COE, Pune, India

Department of Computer Engineering, Savitribai Phule Pune University AISSMS COE, Pune, India

Mr. Anilkumar J Kadam, Savitribai Phule Pune University AISSMS COE, Pune, India

Department of Computer Engineering, Savitribai Phule Pune University AISSMS COE, Pune, India

Published
2016-03-31
How to Cite
Alle, R., Aranya, A., Thakur, A., & J Kadam, M. A. (2016). Effective Bug Triage Using Cold-Start Recommendation System. IJRDO -Journal of Computer Science Engineering, 2(3), 28-31. https://doi.org/10.53555/cse.v2i3.580
Issue
Vol. 2 No. 3 (2016): IJRDO - Journal of Computer Science Engineering
Section
Articles

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