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A Learning to Rank Approach using Boltzmann Learning for Software Defect Prediction

Author(s):

Bhanu Priya , CT Institute of Technology & Research, Jalandhar, Punjab 144008, India; Sarabjit Kaur, CT Institute of Technology & Research, Jalandhar, Punjab 144008, India

Keywords:

Software Defects, Software Defect Prediction, Defect Prediction model, Learning to Rank Approach, Enhanced Learning to Rank Approach

Abstract

Software Defect Prediction is very useful for find out the defects from the different modules of the software. There are a variety of approaches which can be used for predicting defects from the software modules. In this paper, Learning-to-rank approach can be apply. The results can be based on the number of test cases. This paper also concerned with enhanced learning to rank approach which is used for increase the rate of defect prediction. It also shows the comparison of the learning to rank approach and enhanced learning to rank approach. The enhancement is based upon the Boltzmann learning. This paper mainly focuses on the showing results of LTR approach and Enhanced LTR approach.

Other Details

Paper ID: IJSRDV4I70407
Published in: Volume : 4, Issue : 7
Publication Date: 01/10/2016
Page(s): 605-609

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