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Statements

Subject Item
n2:RIV%2F70883521%3A28140%2F14%3A43871355%21RIV15-MSM-28140___
rdf:type
skos:Concept n10:Vysledek
dcterms:description
This article is aimed to using the analytical programming and the Use Case Points method to estimate time effort in software engineering. The calculation of Use Case Points method is strictly algorithmically defined, and the calculation of this method is simple and fast. Despite a lot of research on this field, there are many attempts to calibrating the weights of Use Case Points method. In this paper is described idea that equation used in Use Case Points method could be less accurate in estimation than other equations. The aim of this research is to create new method, that will be able to create new equations for Use Case Points method. Analytical programming with self-organizing migration algorithm is used for this task. The experimental results shows that this method improving accuracy of effort estimation by 25-40%. This article is aimed to using the analytical programming and the Use Case Points method to estimate time effort in software engineering. The calculation of Use Case Points method is strictly algorithmically defined, and the calculation of this method is simple and fast. Despite a lot of research on this field, there are many attempts to calibrating the weights of Use Case Points method. In this paper is described idea that equation used in Use Case Points method could be less accurate in estimation than other equations. The aim of this research is to create new method, that will be able to create new equations for Use Case Points method. Analytical programming with self-organizing migration algorithm is used for this task. The experimental results shows that this method improving accuracy of effort estimation by 25-40%.
dcterms:title
Using Analytical Programming and UCP Method for Effort Estimation Using Analytical Programming and UCP Method for Effort Estimation
skos:prefLabel
Using Analytical Programming and UCP Method for Effort Estimation Using Analytical Programming and UCP Method for Effort Estimation
skos:notation
RIV/70883521:28140/14:43871355!RIV15-MSM-28140___
n3:aktivita
n15:S
n3:aktivity
S
n3:dodaniDat
n8:2015
n3:domaciTvurceVysledku
n4:4916891 n4:5163587 n4:3877515 n4:8672008
n3:druhVysledku
n13:D
n3:duvernostUdaju
n21:S
n3:entitaPredkladatele
n17:predkladatel
n3:idSjednocenehoVysledku
52402
n3:idVysledku
RIV/70883521:28140/14:43871355
n3:jazykVysledku
n9:eng
n3:klicovaSlova
effort estimation; UCP; Use Case Points; SOMA; self-organizing migration algorithm; Analytical programming
n3:klicoveSlovo
n5:Use%20Case%20Points n5:SOMA n5:effort%20estimation n5:Analytical%20programming n5:self-organizing%20migration%20algorithm n5:UCP
n3:kontrolniKodProRIV
[AD89D460C323]
n3:mistoKonaniAkce
on-line
n3:mistoVydani
Heidelberg
n3:nazevZdroje
Advances in Intelligent Systems and Computing. 285
n3:obor
n12:JC
n3:pocetDomacichTvurcuVysledku
4
n3:pocetTvurcuVysledku
4
n3:rokUplatneniVysledku
n8:2014
n3:tvurceVysledku
Prokopová, Zdenka Sehnálek, Stanislav Urbánek, Tomáš Šilhavý, Radek
n3:typAkce
n16:WRD
n3:zahajeniAkce
2014-04-28+02:00
s:issn
2194-5357
s:numberOfPages
11
n18:doi
10.1007/978-3-319-06740-7_49
n19:hasPublisher
Springer-Verlag. Berlin
n14:isbn
978-3-319-06739-1
n20:organizacniJednotka
28140