RT Journal Article
T1 Expressing Measurement Uncertainty in OCL/UML Datatypes
A1 Fernández-Bertoa, Manuel
A1 Moreno, Nathalie
A1 Barquero Moreno, Gala
A1 Burgueño-Caballero, Lola
A1 Troya-Castilla, Javier
A1 Vallecillo-Moreno, Antonio Jesús
K1 Modelos matemáticos
AB Uncertainty is an inherent property of any measure or estimation performed in any physical setting, and therefore it needs tobe 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.
YR 2018
FD 2018-05-31
LK https://hdl.handle.net/10630/15882
UL https://hdl.handle.net/10630/15882
LA eng
NO Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech.
DS RIUMA. Repositorio Institucional de la Universidad de Málaga
RD 28 feb 2026