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dc.contributor.authorFernández-Bertoa, Manuel 
dc.contributor.authorMoreno, Nathalie
dc.contributor.authorBarquero, Gala
dc.contributor.authorBurgueño, Loli
dc.contributor.authorTroya, Javier
dc.contributor.authorVallecillo-Moreno, Antonio Jesus 
dc.date.accessioned2018-05-31T11:39:12Z
dc.date.available2018-05-31T11:39:12Z
dc.date.created2018
dc.date.issued2018-05-31
dc.identifier.urihttps://hdl.handle.net/10630/15882
dc.description.abstractUncertainty is an inherent property of any measure or estimation performed in any physical setting, and therefore it needs to be considered when modeling systems that manage real data. Although several modeling languages permit the representation of measurement uncertainty for describing certain system attributes, these aspects are not normally incorporated into their type systems. Thus, operating with uncertain values and propagating uncertainty are normally cumbersome processes, di cult to achieve at the model level. This paper proposes an extension of OCL and UML datatypes to incorporate data uncertainty coming from physical measurements or user estimations into the models, along with the set of operations de ned for the values of these types.en_US
dc.description.sponsorshipUniversidad de Málaga. Campus de Excelencia Internacional Andalucía Tech.en_US
dc.language.isoengen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectModelos matemáticosen_US
dc.titleExpressing Measurement Uncertainty in OCL/UML Datatypesen_US
dc.typeinfo:eu-repo/semantics/preprinten_US
dc.centroE.T.S.I. Informáticaen_US
dc.relation.eventtitle14th European Conference on Modelling Foundations and Applicationsen_US
dc.relation.eventplaceToulouse, Franciaen_US
dc.relation.eventdate25/06/2018en_US


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