Algorithmic Optimisation Method for Improving Use Case Points Estimation

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F70883521%3A28140%2F15%3A43873810" target="_blank" >RIV/70883521:28140/15:43873810 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1371/journal.pone.0141887" target="_blank" >http://dx.doi.org/10.1371/journal.pone.0141887</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1371/journal.pone.0141887" target="_blank" >10.1371/journal.pone.0141887</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Algorithmic Optimisation Method for Improving Use Case Points Estimation

Popis výsledku v původním jazyce

This paper presents a new size estimation method that can be used to estimate size level for software engineering projects. The Algorithmic Optimisation Method is based on Use Case Points and on Multiple Least Square Regression. The method is derived into three phases. The first phase deals with calculation Use Case Points and correction coefficients values. Correction coefficients are obtained by using Multiple Least Square Regression. New project is estimated in the second and third phase. In the second phase Use Case Points parameters for new estimation are set up and in the third phase project estimation is performed. Final estimation is obtained by using newly developed estimation equation, which used two correction coefficients. The Algorithmic Optimisation Method performs approximately 43% better than the Use Case Points method, based on their magnitude of relative error score. All results were evaluated by standard approach: visual inspection, goodness of fit measure and statis

Název v anglickém jazyce

Algorithmic Optimisation Method for Improving Use Case Points Estimation

Popis výsledku anglicky

This paper presents a new size estimation method that can be used to estimate size level for software engineering projects. The Algorithmic Optimisation Method is based on Use Case Points and on Multiple Least Square Regression. The method is derived into three phases. The first phase deals with calculation Use Case Points and correction coefficients values. Correction coefficients are obtained by using Multiple Least Square Regression. New project is estimated in the second and third phase. In the second phase Use Case Points parameters for new estimation are set up and in the third phase project estimation is performed. Final estimation is obtained by using newly developed estimation equation, which used two correction coefficients. The Algorithmic Optimisation Method performs approximately 43% better than the Use Case Points method, based on their magnitude of relative error score. All results were evaluated by standard approach: visual inspection, goodness of fit measure and statis

Druh

J_x - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)

CEP obor

JC - Počítačový hardware a software

OECD FORD obor

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Projekt

—

Návaznosti

V - Vyzkumna aktivita podporovana z jinych verejnych zdroju

Rok uplatnění

2015

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

PLoS ONE

ISSN

1932-6203

e-ISSN

—

Svazek periodika

10

Číslo periodika v rámci svazku

11

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

14

Strana od-do

1-14

Kód UT WoS článku

000364422800011

EID výsledku v databázi Scopus

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