Volume : V, Issue : V, May - 2016

Automatic Bug Classification using Data Reduction Techniques

Anita Kunjir, Laxman Mulik, Bhupesh Kumar, Prof. G. V. Mane

Abstract :

 Now a day software companies spend 45 present cost for software bugs. Set of bug fixing is bug triage which is main goal is assigning new bug to correct potential developer. The existing bug triage system work with text classification techniques, which build classifiers from training data sets of bug report. These approaches facing problem from the large scale and low quality bug sets. In this paper we propose feature selection and instance selection techniques for bug triage to reduction bug data sets. In this paper we are studied combination of the feature selection algorithm CH, instance selection algorithm ICF. We evaluate the training set reduction on the bug data of Mozilla. The data reduction can be reduce data scale and improving the accuracy of bug triage

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Article: Download PDF    DOI : https://www.doi.org/10.36106/gjra  

Cite This Article:

Anita Kunjir, Laxman Mulik, Bhupesh Kumar Automatic Bug Classification using Data Reduction Techniques Global Journal For Research Analysis, Vol: 5, Issue : 5 MAY 2016

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