z-logo
open-access-imgOpen Access
ROLE OF DATA MINING CLASSIFICATION TECHNIQUE IN SOFTWARE DEFECT PREDICTION
Author(s) -
Dr.A.R.Pon Periyasamy,
Mrs A.Misbahulhuda
Publication year - 2017
Publication title -
zenodo (cern european organization for nuclear research)
Language(s) - English
DOI - 10.5281/zenodo.571209
Subject(s) - data mining , computer science , software bug , software , programming language
Software defect prediction is the process of locating defective modules in software. Software quality may be a field of study and apply that describes the fascinating attributes of software package product. The performance should be excellent with none defects. Software quality metrics are a set of software package metrics that target the standard aspects of the product, process, and project. The software package defect prediction model helps in early detection of defects and contributes to their economical removal and manufacturing a top quality software package supported many metrics. The most objective of paper is to assist developers determine defects supported existing software package metrics victimization data mining techniques and thereby improve the software package quality. In this paper, role of various classification techniques in software defect prediction process are analyzed

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here