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Blockchain-based Software Effort Estimation: An Empirical Study

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dc.contributor.authorAhmed, Mansoor-
dc.contributor.authorIqbal, Naeem-
dc.contributor.authorHussain, Faraz-
dc.contributor.authorKhan, Murad-Ali-
dc.contributor.authorHelfert, Markus-
dc.contributor.authorImran,-
dc.contributor.authorKim, Jungsuk-
dc.date.accessioned2022-12-09T02:40:09Z-
dc.date.available2022-12-09T02:40:09Z-
dc.date.created2022-11-10-
dc.date.issued2022-10-
dc.identifier.issn2169-3536-
dc.identifier.urihttps://scholarworks.bwise.kr/gachon/handle/2020.sw.gachon/86238-
dc.description.abstractContext: The success or failure of any software development project significantly depends on the accuracy of its effort estimates. Software development effort estimation is the foundation for project bidding, budgeting, planning, and cost control. Problem: The literature shows that a lot of work has been done on software effort estimation. But still, there is a need for improvement in effort estimation by introducing new methodologies. The structured group-based and analogy-based effort estimations are the widely used estimation methods. Nevertheless, there are several shortcomings of using these methods such as lack of experts, lack of historical data, and biasness in expert opinion, which negatively affect the estimation results. Motivation: With the advancement of technologies, such limitations could be overcome. Such as leveraging the applicability of blockchain in several domains such as improvement in software development process and network security. Method: In this article, we have proposed a Blockchain-Based Software Effort Estimation (BBSEE) methodology to improve the software effort estimation. We employ the proposed method using Web and blockchain technologies. Moreover, we also proposed an evaluation criteria to assess the efficacy of the proposed method in terms of Mean Magnitude of Relative Error (MMRE), Mean Absolute Error (MAE), and percentage of successful predictions falling (PRED (25)). Result: We performed several case studies and analyses expert opinion of 52 organizations to present the efficacy of the proposed method. Conclusion: We observe that BBSEE method outperforms than expert judgment and analogy-based effort estimation methodologies in terms of software effort estimation. Author-
dc.language영어-
dc.language.isoen-
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)-
dc.relation.isPartOfIEEE Access-
dc.titleBlockchain-based Software Effort Estimation: An Empirical Study-
dc.typeArticle-
dc.type.rimsART-
dc.description.journalClass1-
dc.identifier.wosid000890187700001-
dc.identifier.doi10.1109/access.2022.3216840-
dc.identifier.bibliographicCitationIEEE Access, v.10, pp.120412 - 120425-
dc.description.isOpenAccessN-
dc.identifier.scopusid2-s2.0-85141463690-
dc.citation.endPage120425-
dc.citation.startPage120412-
dc.citation.titleIEEE Access-
dc.citation.volume10-
dc.contributor.affiliatedAuthorImran,-
dc.contributor.affiliatedAuthorKim, Jungsuk-
dc.type.docTypeArticle-
dc.subject.keywordAuthorAnalogy-based estimation-
dc.subject.keywordAuthorBlockchain-
dc.subject.keywordAuthorBlockchain-based software engineering-
dc.subject.keywordAuthorBlockchains-
dc.subject.keywordAuthorError analysis-
dc.subject.keywordAuthorEstimation-
dc.subject.keywordAuthorEstimation error-
dc.subject.keywordAuthorGroup-based estimation-
dc.subject.keywordAuthorNeural networks-
dc.subject.keywordAuthorSchedules-
dc.subject.keywordAuthorSoftware effort estimation-
dc.subject.keywordAuthorSoftware engineering-
dc.subject.keywordAuthorSoftware engineering-
dc.subject.keywordAuthorSoftware engineering-
dc.subject.keywordAuthorSoftware measurement-
dc.subject.keywordPlusEXPERT-JUDGMENT-
dc.subject.keywordPlusMODELS-
dc.subject.keywordPlusWORK-
dc.relation.journalResearchAreaComputer Science-
dc.relation.journalResearchAreaEngineering-
dc.relation.journalResearchAreaTelecommunications-
dc.relation.journalWebOfScienceCategoryComputer Science, Information Systems-
dc.relation.journalWebOfScienceCategoryEngineering, Electrical & Electronic-
dc.relation.journalWebOfScienceCategoryTelecommunications-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
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