A review of the regression models applicable to software project effort estimation

Huynh Thai, Hoc; Vo Van, Hai; Ho, Le Thi Kim Nhung

dc.title	A review of the regression models applicable to software project effort estimation	en
dc.contributor.author	Huynh Thai, Hoc
dc.contributor.author	Vo Van, Hai
dc.contributor.author	Ho, Le Thi Kim Nhung
dc.relation.ispartof	Advances in Intelligent Systems and Computing
dc.identifier.issn	2194-5357 Scopus Sources, Sherpa/RoMEO, JCR
dc.identifier.isbn	978-3-03-031361-6
dc.date.issued	2019
utb.relation.volume	1047
dc.citation.spage	399
dc.citation.epage	407
dc.event.title	3rd Conference on Computational Methods in Systems and Software (CoMeSySo)
dc.event.location	online
dc.event.sdate	2019-10-03
dc.event.edate	2019-10-05
dc.type	conferenceObject
dc.language.iso	en
dc.publisher	Springer
dc.identifier.doi	10.1007/978-3-030-31362-3_39
dc.relation.uri	https://link.springer.com/chapter/10.1007/978-3-030-31362-3_39
dc.subject	Software Project Effort Estimation (SPEE)	en
dc.subject	regression model	en
dc.subject	stepwise regression	en
dc.subject	regression clustering	en
dc.subject	AOM	en
dc.subject	RCMLR	en
dc.subject	WCO	en
dc.description.abstract	Software Project Effort Estimation - (further only SPEE), is an essential step in a software project; related to approximating Development Effort before development is completed, and is an important software development activity. Its accuracy has a significant effect on a project's success. The major intent of this paper is to review existing Software Project Effort Estimation – (further only SPEE), exhaustively by exploring Regression Models for modern SPEEs. © 2019, Springer Nature Switzerland AG.	en
utb.faculty	Faculty of Applied Informatics
dc.identifier.uri	http://hdl.handle.net/10563/1009482
utb.identifier.obdid	43881129
utb.identifier.scopus	2-s2.0-85075602746
utb.identifier.wok	000627307100038
utb.source	d-scopus
dc.date.accessioned	2019-12-20T12:39:23Z
dc.date.available	2019-12-20T12:39:23Z
dc.description.sponsorship	Faculty of Applied Informatics, Tomas Bata University in Zlin [RO30196021025, IGA/CebiaTech/2019/002]
utb.contributor.internalauthor	Huynh Thai, Hoc
utb.contributor.internalauthor	Vo Van, Hai
utb.contributor.internalauthor	Ho, Le Thi Kim Nhung
utb.fulltext.affiliation	Huynh Thai Hoc, Vo Van Hai, Ho Le Thi Kim Nhung Faculty of Applied Informatics, Tomas Bata University in Zlin, Nad Stranemi 4511, 76001 Zlin, Czech Republic {huynh_thai,vo_van,lho}@utb.cz
utb.fulltext.dates	-
utb.fulltext.sponsorship	This work was supported by the Faculty of Applied Informatics, Tomas Bata University in Zlín, under Project RO30196021025 and under Project IGA/CebiaTech/2019/002.
utb.wos.affiliation	[Huynh Thai Hoc; Vo Van Hai; Ho Le Thi Kim Nhung] Tomas Bata Univ Zlin, Fac Appl Informat, Stranemi 4511, Zlin 76001, Czech Republic
utb.scopus.affiliation	Faculty of Applied Informatics, Tomas Bata University in Zlin, Nad Stranemi 4511, Zlin, 76001, Czech Republic
utb.fulltext.projects	RO30196021025
utb.fulltext.projects	IGA/CebiaTech/2019/002
utb.fulltext.faculty	Faculty of Applied Informatics
utb.fulltext.faculty	Faculty of Applied Informatics
utb.fulltext.faculty	Faculty of Applied Informatics