A systematic review of unsupervised learning techniques for software defect prediction

Unsupervised machine learners have been increasingly applied to software defect prediction. It is an approach that may be valuable for software practitioners because it reduces the need for labeled training data. Investigate the use and performance of unsupervised learning techniques in software def...

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Bibliographic Details

Published in:	Information and software technology Vol. 122; p. 106287
Main Authors:	Li, Ning, Shepperd, Martin, Guo, Yuchen
Format:	Journal Article
Language:	English
Published:	Elsevier B.V 01.06.2020
Subjects:	Machine learning Meta-analysis Software defect prediction Systematic review Unsupervised learning Systematic review Software defect prediction Unsupervised learning Machine learning Meta-analysis
ISSN:	0950-5849, 1873-6025
Online Access:	Get full text
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