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Software architecture influence on software effort estimation

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dc.title Software architecture influence on software effort estimation en
dc.contributor.author Vo Van, Hai
dc.contributor.author Tin, Nguyen Thuong
dc.contributor.author Prokopová, Zdenka
dc.relation.ispartof Lecture Notes in Networks and Systems
dc.identifier.issn 2367-3389 Scopus Sources, Sherpa/RoMEO, JCR
dc.identifier.issn 2367-3370 Scopus Sources, Sherpa/RoMEO, JCR
dc.identifier.isbn 9789819652372
dc.identifier.isbn 9783031931055
dc.identifier.isbn 9789819662968
dc.identifier.isbn 9783031999963
dc.identifier.isbn 9783031950162
dc.identifier.isbn 9783031947698
dc.identifier.isbn 9783032004406
dc.identifier.isbn 9783031910074
dc.identifier.isbn 9783031926105
dc.identifier.isbn 9789819639410
dc.date.issued 2026
utb.relation.volume 1471 LNNS
dc.citation.spage 321
dc.citation.epage 331
dc.event.title 8th International Conference on Computational Methods in Systems and Software, CoMeSySo 2024
dc.event.sdate 2024-10-23
dc.event.edate 2024-10-26
dc.type conferenceObject
dc.language.iso en
dc.publisher Springer Science and Business Media Deutschland GmbH
dc.identifier.doi 10.1007/978-3-031-94770-4_25
dc.relation.uri https://link.springer.com/chapter/10.1007/978-3-031-94770-4_25
dc.subject machine learning en
dc.subject software architecture en
dc.subject software effort estimation en
dc.subject cluster analysis en
dc.subject clustering algorithms en
dc.subject construction industry en
dc.subject learning systems en
dc.subject clustering data en
dc.subject cost implementations en
dc.subject machine-learning en
dc.subject project implementation time en
dc.subject software effort en
dc.subject software effort estimation en
dc.subject software industry en
dc.subject software project en
dc.subject software architecture en
dc.description.abstract In the construction industry, choosing a different architecture will lead to very different techniques, costs, and project implementation time. The same goes for software projects. Choosing an appropriate software architecture requires consideration of many factors. This choice significantly affects the success rate of the project. Many software architectures have been proposed in the past and have been successfully applied in the software industry. This study proposes a model to evaluate the influence of software architecture on the accuracy of software effort estimation. This work is done by clustering data according to software architecture and then applying the FPA method and the proposed model to estimate software effort. Experimental results show that clustering data according to software architecture provides higher estimation accuracy than non-clustering data on both the FPA method and the proposed model. en
utb.faculty Faculty of Applied Informatics
dc.identifier.uri http://hdl.handle.net/10563/1012520
utb.identifier.scopus 2-s2.0-105012358175
dc.date.accessioned 2025-10-16T07:25:46Z
dc.date.available 2025-10-16T07:25:46Z
dc.description.sponsorship This study was supported by the Faculty of Business Information Technology, College of Technology and Design, University of Economics Ho Chi Minh City, under Project CTD-2024-02 and the Faculty of Applied Informatics, Tomas Bata University in Zl\u00EDn, under Project RO 302106002025/2102.
utb.ou Department of Computer and Communication Systems
utb.contributor.internalauthor Prokopová, Zdenka
utb.fulltext.sponsorship This study was supported by the Faculty of Business Information Technology, College of Technology and Design, University of Economics Ho Chi Minh City, under Project CTD-2024-02 and the Faculty of Applied Informatics, Tomas Bata University in Zlín, under Project RO 302106002025/2102.
utb.scopus.affiliation University of Economics Ho Chi Minh City, Ho Chi Minh City, Viet Nam; Industrial University of Ho Chi Minh City, Ho Chi Minh City, Viet Nam; Tomas Bata University in Zlin, Zlin, Czech Republic
utb.fulltext.projects CTD-2024-02
utb.fulltext.projects RO 302106002025/2102
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