Kontaktujte nás | Jazyk: čeština English
Název: | Categorical variable segmentation model for software development effort estimation | ||||||||||
Autor: | Šilhavý, Petr; Šilhavý, Radek; Prokopová, Zdenka | ||||||||||
Typ dokumentu: | Recenzovaný odborný článek (English) | ||||||||||
Zdrojový dok.: | IEEE Access. 2019, vol. 7, p. 9618-9626 | ||||||||||
ISSN: | 2169-3536 (Sherpa/RoMEO, JCR) | ||||||||||
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DOI: | https://doi.org/10.1109/ACCESS.2019.2891878 | ||||||||||
Abstrakt: | This paper proposes a new software development effort estimation model. The new model's design is based on the function point analysis, categorical variable segmentation (CVS), and stepwise regression. The stepwise regression method is used for the creation of the unique estimation model of each segment. The estimation accuracy of the proposed model is compared to clustering-based models and the international function point user group model. It is shown that the proposed model increases estimation accuracy when compared to baseline methods: non-clustered functional point analysis and clustering-based models. The new CVS model achieves a significantly higher accuracy than the baseline methods. © 2013 IEEE. | ||||||||||
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