Analyzing correlation of the relationship between technical complexity factors and environmental complexity factors for software development effort estimation

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F70883521%3A28140%2F21%3A63537878" target="_blank" >RIV/70883521:28140/21:63537878 - isvavai.cz</a>

Výsledek na webu

<a href="https://link.springer.com/chapter/10.1007%2F978-3-030-90318-3_65" target="_blank" >https://link.springer.com/chapter/10.1007%2F978-3-030-90318-3_65</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-030-90318-3_65" target="_blank" >10.1007/978-3-030-90318-3_65</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Analyzing correlation of the relationship between technical complexity factors and environmental complexity factors for software development effort estimation

Popis výsledku v původním jazyce

In this paper, a new method called Correlation-based Feature Selection in Correction Factors is proposed. The method is based on the feature selection method used in software development effort estimation to reduce redundant correction factors. In this paper, the impact of correlation-based feature selection on the method’s estimation accuracy is investigated. Multiple linear regression was used as the basic technique for the correction factors preprocessed by the feature selection method. The results were evaluated using six unbiased accuracy measures through the 5-fold cross-validation over the historical dataset. The proposed method leads to a significant improvement in estimation accuracy by simplifying the evaluation of correction factor values in the use case points method, thus increasing the usefulness of the proposed method in practice. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Název v anglickém jazyce

Analyzing correlation of the relationship between technical complexity factors and environmental complexity factors for software development effort estimation

Popis výsledku anglicky

In this paper, a new method called Correlation-based Feature Selection in Correction Factors is proposed. The method is based on the feature selection method used in software development effort estimation to reduce redundant correction factors. In this paper, the impact of correlation-based feature selection on the method’s estimation accuracy is investigated. Multiple linear regression was used as the basic technique for the correction factors preprocessed by the feature selection method. The results were evaluated using six unbiased accuracy measures through the 5-fold cross-validation over the historical dataset. The proposed method leads to a significant improvement in estimation accuracy by simplifying the evaluation of correction factor values in the use case points method, thus increasing the usefulness of the proposed method in practice. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Druh

D - Stať ve sborníku

CEP obor

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OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach<br>I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2021

Kód důvěrnosti údajů

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

Název statě ve sborníku

Lecture Notes in Networks and Systems

ISBN

978-303090317-6

ISSN

23673370

e-ISSN

2367-3389

Počet stran výsledku

14

Strana od-do

835-848

Název nakladatele

Springer Science and Business Media Deutschland GmbH

Místo vydání

Berlín

Místo konání akce

Vsetín

Datum konání akce

1. 10. 2021

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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