Categorical Variable Segmentation Model for Software Development Effort Estimation

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F70883521%3A28140%2F19%3A63522740" target="_blank" >RIV/70883521:28140/19:63522740 - isvavai.cz</a>
Result on the web
<a href="https://ieeexplore.ieee.org/document/8610292" target="_blank" >https://ieeexplore.ieee.org/document/8610292</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/ACCESS.2019.2891878" target="_blank" >10.1109/ACCESS.2019.2891878</a>

Result language
angličtina
Original language name
Categorical Variable Segmentation Model for Software Development Effort Estimation
Original language description
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.
Czech name
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Czech description
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Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project
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Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year
2019
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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