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Prediction accuracy measurements as a fitness function for software effort estimation

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dc.title Prediction accuracy measurements as a fitness function for software effort estimation en
dc.contributor.author Urbánek, Tomáš
dc.contributor.author Prokopová, Zdenka
dc.contributor.author Šilhavý, Radek
dc.contributor.author Veselá, Veronika
dc.relation.ispartof SpringerPlus
dc.identifier.issn 2193-1801 Scopus Sources, Sherpa/RoMEO, JCR
dc.date.issued 2015
utb.relation.volume 4
utb.relation.issue 1
dc.citation.spage 1
dc.citation.epage 17
dc.type article
dc.language.iso en
dc.publisher SpringerOpen
dc.identifier.doi 10.1186/s40064-015-1555-9
dc.relation.uri http://springerplus.springeropen.com/articles/10.1186/s40064-015-1555-9
dc.subject Analytical programming en
dc.subject Differential evolution en
dc.subject Effort estimation en
dc.subject Prediction accuracy measures en
dc.subject Software engineering en
dc.subject Use case points en
dc.description.abstract This paper evaluates the usage of analytical programming and different fitness functions for software effort estimation. Analytical programming and differential evolution generate regression functions. These functions are evaluated by the fitness function which is part of differential evolution. The differential evolution requires a proper fitness function for effective optimization. The problem is in proper selection of the fitness function. Analytical programming and different fitness functions were tested to assess insight to this problem. Mean magnitude of relative error, prediction 25 %, mean squared error (MSE) and other metrics were as possible candidates for proper fitness function. The experimental results shows that means squared error performs best and therefore is recommended as a fitness function. Moreover, this work shows that analytical programming method is viable method for calibrating use case points method. All results were evaluated by standard approach: visual inspection and statistical significance. © 2015, Urbanek et al. en
utb.faculty Faculty of Applied Informatics
dc.identifier.uri http://hdl.handle.net/10563/1005787
utb.identifier.obdid 43874074
utb.identifier.scopus 2-s2.0-84949993577
utb.identifier.wok 000368718000002
utb.identifier.pubmed 26697288
utb.source j-scopus
dc.date.accessioned 2016-04-12T11:51:56Z
dc.date.available 2016-04-12T11:51:56Z
dc.description.sponsorship Tomas Bata University in Zlin [IGA/CebiaTech/2015/034]
dc.rights Attribution-NonCommercial-NoDerivs 4.0 Unported
dc.rights.uri http://creativecommons.org/licenses/by-nc-nd/4.0/
dc.rights.access openAccess
utb.contributor.internalauthor Urbánek, Tomáš
utb.contributor.internalauthor Prokopová, Zdenka
utb.contributor.internalauthor Šilhavý, Radek
utb.contributor.internalauthor Veselá, Veronika
utb.fulltext.affiliation Tomas Urbanek *, Zdenka Prokopova, Radek Silhavy, Veronika Vesela * Correspondence: turbanek@fai.utb.cz Department of Computer and Comunication systems, Tomas Bata University in Zlin, Nad Stranemi 4511, Zlin, Czech Republic
utb.fulltext.dates Received: 1 October 2015 Accepted: 24 November 2015 Published online: 15 December 2015
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