An approach to adjust effort estimation of function point analysis
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F70883521%3A28140%2F21%3A63537898" target="_blank" >RIV/70883521:28140/21:63537898 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1007/978-3-030-77442-4_45" target="_blank" >http://dx.doi.org/10.1007/978-3-030-77442-4_45</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-030-77442-4_45" target="_blank" >10.1007/978-3-030-77442-4_45</a>
Alternative languages
Result language
angličtina
Original language name
An approach to adjust effort estimation of function point analysis
Original language description
This study presents a modified approach to adjust a software development effort estimation. The AdamOptimizer-based regression model is adopted to adjust and enhance the accuracy of effort estimation. This approach is derived into three phases. The first step deals with the logarithmized formula of effort estimation computed by Function Point Analysis and Productivity Delivery Rate. The Adam-Optimizer-based regression model is examined in the second phase, and the ISBSG repository 2020 release R1 is considered as a historical dataset in this paper. Moreover, the K-Fold cross-validation technique is adopted to tunning the training model. In the following phase, all results are evaluated by statistical significance and the goodness of fit measure. Finally, a proposed approach is compared with others: Capers Jones, and the Mean Effort. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
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)
Result continuities
Project
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Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2021
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Lecture Notes in Networks and Systems
ISBN
978-303077441-7
ISSN
23673370
e-ISSN
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Number of pages
16
Pages from-to
522-537
Publisher name
Springer Science and Business Media Deutschland GmbH
Place of publication
Berlín
Event location
Zlín
Event date
Apr 1, 2021
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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