RT Journal Article
T1 Incorporating Measurement Uncertainty into OCL/UML Primitive Datatypes
A1 Fernández-Bertoa, Manuel
A1 Burgueño-Caballero, Lola
A1 Moreno, Nathalie
A1 Vallecillo-Moreno, Antonio Jesús
K1 Incertidumbre (Teoría de la información)
AB The correct representation of the relevant properties of a system is an essential requirement for the effective use and wide adoption of model-based practices in industry. Uncertainty is one of the inherent properties of any measurement or estimation that is obtained in any physical setting; as such, it must be considered when modeling software systems that deal with real data. Although a few modeling languages enable the representation of measurement uncertainty, these aspects are not normally incorporated into their type systems. Therefore, operating with uncertain values and propagating their uncertainty become cumbersome processes, which hinder their realization in real environments. This paper proposes an extension of OCL/UML primitive datatypes that enables the representation of the uncertainty that comes from physical measurements or user estimates into the models, together with an algebra of operations that are defined for the values of these types.
YR 2020
FD 2020-06-01
LK https://hdl.handle.net/10630/19571
UL https://hdl.handle.net/10630/19571
LA eng
NO Preprint publicado en  la revista Software & System Modeling :Bertoa, M.F., Burgueño, L., Moreno, N., Vallecillo, A. "Incorporating measurement uncertainty into OCL/UML primitive datatypes." Softw Syst Model (2019). https://doi.org/10.1007/s10270-019-00741-0)
NO TIN2014-52034-R, TIN2016-75944-R and PGC2018-094905-B-I0
DS RIUMA. Repositorio Institucional de la Universidad de Málaga
RD 21 ene 2026