Towards a correction factors-based software productivity using ensemble approach for early software development effort estimation
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F70883521%3A28140%2F22%3A63555918" target="_blank" >RIV/70883521:28140/22:63555918 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1007/978-3-031-09070-7_35" target="_blank" >http://dx.doi.org/10.1007/978-3-031-09070-7_35</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-031-09070-7_35" target="_blank" >10.1007/978-3-031-09070-7_35</a>
Alternative languages
Result language
angličtina
Original language name
Towards a correction factors-based software productivity using ensemble approach for early software development effort estimation
Original language description
Accuracy of effort estimation is one of the necessary conditions for efficiently managing software development projects. Since the information available in the early stages of software development is insufficient, software sizing metrics are considered critical factors for effort estimation. However, there is no consistent method for converting software sizing into the corresponding effort. Previous estimation methods have not considered software productivity a critical factor in estimating effort based on software sizing. This paper proposes a software productivity model based on correction factors in the Optimizing Correction Factors method through an ensemble construction mechanism of three popular machine learning techniques. The results show that using the proposed software productivity minimizes the estimation error of the methods compared to using fixed productivity metrics. © 2022, 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
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2022
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
978-3-031-09069-1
ISSN
2367-3370
e-ISSN
2367-3389
Number of pages
13
Pages from-to
413-425
Publisher name
Springer International Publishing AG
Place of publication
Basel
Event location
on-line
Event date
Apr 26, 2022
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000893645700035