IMPLEMENTATION OF REDUCING FEATURES TO IMPROVE CODE CHANGE BASED BUG PREDICTION BY USING COS-TRIAGE ALGORITHM

Veena Jadhav, Vandana Gaikwad, Netra Patil

Abstract: Today, we are getting plenty of bugs in the software because of variations in the software and hardware technologies. Bugs are nothing but Software faults, existing a severe challenge for system reliability and dependability. To identify the bugs from the software bug prediction is convenient approach. To visualize the presence of a bug in a source code file, recently, Machine learning classifiers approach is developed. Because of a huge number of machine learned features current classifier-based bug prediction have two major problems i) inadequate precision for practical usage ii) measured prediction time. In this paper we used two techniques first, cos-triage algorithm which have a go to enhance the accuracy and also lower the price of bug prediction and second, feature selection methods which eliminate less significant features. Reducing features get better the quality of knowledge extracted and also boost the speed of computation.

Keywords: Efficiency, Bug Prediction, Classification, Feature Selection, Accuracy.

DOI: https://doi.org/10.15623/ijret.2014.0311073