Calibrating function complexity in enhancement project for improving function points analysis estimation

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

dc.title	Calibrating function complexity in enhancement project for improving function points analysis estimation	en
dc.contributor.author	Vo Van, Hai
dc.contributor.author	Ho, Le Thi Kim Nhung
dc.contributor.author	Huynh Thai, Hoc
dc.relation.ispartof	Lecture Notes in Networks and Systems
dc.identifier.issn	2367-3370 Scopus Sources, Sherpa/RoMEO, JCR
dc.identifier.isbn	978-3-03-090317-6
dc.date.issued	2021
utb.relation.volume	232 LNNS
dc.citation.spage	857
dc.citation.epage	869
dc.event.title	5th Computational Methods in Systems and Software, CoMeSySo 2021
dc.event.location	online
dc.event.sdate	2021-10-01
dc.event.edate	2021-10-01
dc.type	conferenceObject
dc.language.iso	en
dc.publisher	Springer Science and Business Media Deutschland GmbH
dc.identifier.doi	10.1007/978-3-030-90318-3_67
dc.relation.uri	https://link.springer.com/chapter/10.1007%2F978-3-030-90318-3_67
dc.subject	effort estimation	en
dc.subject	function point analysis	en
dc.subject	multiple linear regression	en
dc.subject	software measurement	en
dc.description.abstract	Producing a good software product on time and within budget, the initial software estimation takes a significant role. Reality has shown that most software fails because the initial software estimation is not correct. Many researchers have proposed methods for software estimation. It has been developed since the 70s of the last century, but it is still of great interest until now. We also know that creating a new software product is difficult; it is even more difficult to innovate. In the framework of this paper, we propose an improved method based on the FPA method of IFPUG. We named this proposed model is Calibrating Function Complexity in Enhancement Project (CFCEP). This method is based on the Linear Regression technique to give coefficients of function complexity. The experimental results based on the ISBSG dataset show that the estimation based on this new coefficient gives much better results than using the coefficients of the standard FPA method. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.	en
utb.faculty	Faculty of Applied Informatics
dc.identifier.uri	http://hdl.handle.net/10563/1010732
utb.identifier.obdid	43882981
utb.identifier.scopus	2-s2.0-85120580616
utb.source	d-scopus
dc.date.accessioned	2021-12-22T11:51:36Z
dc.date.available	2021-12-22T11:51:36Z
dc.description.sponsorship	IGA/CebiaTech/2021/001
utb.contributor.internalauthor	Vo Van, Hai
utb.contributor.internalauthor	Ho, Le Thi Kim Nhung
utb.contributor.internalauthor	Huynh Thai, Hoc
utb.fulltext.affiliation	Vo Van Hai1, Ho Le Thi Kim Nhung1 and Huynh Thai Hoc 1 1 Tomas Bata University in Zlin, Faculty of Applied Informatics, Nad Stranemi 4511, Zlin 76001, Czech Republic {vo_van, lho, huynh_thai}@utb.cz
utb.fulltext.dates	-
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utb.fulltext.sponsorship	This work was supported by the Faculty of Applied Informatics, Tomas Bata University in Zlín, under project IGA/CebiaTech/2021/001.
utb.scopus.affiliation	Faculty of Applied Informatics, Tomas Bata University in Zlin, Nad Stranemi 4511, Zlin, 76001, Czech Republic
utb.fulltext.projects	IGA/CebiaTech/2021/001
utb.fulltext.faculty	Faculty of Applied Informatics
utb.fulltext.ou	-