A systematic review of unsupervised learning techniques for software defect prediction

Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/20523

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DC Field	Value	Language
dc.contributor.author	Li, N	-
dc.contributor.author	Shepperd, M	-
dc.contributor.author	Guo, Y	-
dc.date.accessioned	2020-03-16T11:09:13Z	-
dc.date.available	2020-06	-
dc.date.available	2020-03-16T11:09:13Z	-
dc.date.issued	2020-02-22	-
dc.identifier	106287	-
dc.identifier.citation	Li, N., Shepperd, M. and Guo, Y. (2020) 'A systematic review of unsupervised learning techniques for software defect prediction', Information and Software Technology, 122, 106287 (15 pp.). doi: 10.1016/j.infsof.2020.106287	en_US
dc.identifier.issn	0950-5849	-
dc.identifier.uri	https://bura.brunel.ac.uk/handle/2438/20523	-
dc.description.sponsorship	National Key Basic Research Program of China [2018YFB1004401]; the National Natural Science Foundation of China [61972317, 61402370].	en_US
dc.format.extent	1 - 15	-
dc.language	en	-
dc.language.iso	en	en_US
dc.publisher	Elsevier BV	en_US
dc.subject	unsupervised learning	en_US
dc.subject	software defect prediction	en_US
dc.subject	machine learning	en_US
dc.subject	systematic review	en_US
dc.subject	meta-analysis	en_US
dc.title	A systematic review of unsupervised learning techniques for software defect prediction	en_US
dc.type	Article	en_US
dc.identifier.doi	https://doi.org/10.1016/j.infsof.2020.106287	-
dc.relation.isPartOf	Information and Software Technology	-
pubs.publication-status	Published	-
pubs.volume	122	-
Appears in Collections:	Dept of Computer Science Embargoed Research Papers

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