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Validation of an approach for quantitative measurement and prediction model

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dc.contributor.authorSong, K.W.-
dc.contributor.authorPark, J.-
dc.contributor.authorLee, K.-
dc.date.accessioned2023-03-09T00:42:08Z-
dc.date.available2023-03-09T00:42:08Z-
dc.date.issued2005-
dc.identifier.issn0302-9743-
dc.identifier.urihttps://scholarworks.bwise.kr/cau/handle/2019.sw.cau/65536-
dc.description.abstractSoftware organizations are in need of methods to understand, structure, and improve the data they are collection. We have developed an approach for use when a large number of diverse metrics are already being collected by a software organization. The Approach combines two methods. One looks at an organization's measurement framework in a goal-oriented fashion and the other looks at it in the performance pyramid by quantitative method. We present model-based performance prediction at software development time in order to optimize a project of organization and strengthen control of it and thus, accomplish its objectives by determining its process capability and project capability through the proposed three models(PCM, ECM, PPM) by developing strategies to improve the process and, by planning the most suitable project to its vision with Project Prediction Model (PPM).-
dc.format.extent14-
dc.language영어-
dc.language.isoENG-
dc.publisherSPRINGER-VERLAG BERLIN-
dc.titleValidation of an approach for quantitative measurement and prediction model-
dc.typeArticle-
dc.identifier.bibliographicCitationSOFTWARE ENGINEERING RESEARCH, MANAGEMENT AND APPLICATIONS, v.3647, pp 187 - 200-
dc.description.isOpenAccessN-
dc.identifier.wosid000236904500014-
dc.identifier.scopusid2-s2.0-33745144650-
dc.citation.endPage200-
dc.citation.startPage187-
dc.citation.titleSOFTWARE ENGINEERING RESEARCH, MANAGEMENT AND APPLICATIONS-
dc.citation.volume3647-
dc.type.docTypeArticle; Proceedings Paper-
dc.publisher.location독일-
dc.relation.journalResearchAreaComputer Science-
dc.relation.journalWebOfScienceCategoryComputer Science, Software Engineering-
dc.relation.journalWebOfScienceCategoryComputer Science, Theory & Methods-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
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