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Software and Systems Modeling

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04-07-2019 | Special Section Paper

Incorporating measurement uncertainty into OCL/UML primitive datatypes

Authors: Manuel F. Bertoa, Loli Burgueño, Nathalie Moreno, Antonio Vallecillo

Published in: Software and Systems Modeling | Issue 5/2020

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Abstract

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 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.

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This is inspired by how various simple robots operate, in particular, Ozobot robots (https://ozobot.com).

Operations on basic datatypes normally use infix notation (e.g., \(x+y\), \(a<b\), \(P \ {\texttt {and}}\ Q\)). This is the notation that we already support in our USE implementation for the newly defined types (UReal, UBoolean, etc.). However, other languages that we have used to implement these new types (e.g., Java) do not support infix notation. Therefore, in the following we will use either an infix or prefix notation (x.add(y), a.lt(b), P.and(Q)) for the operations of these types, depending on the context and the language used.

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Title: Incorporating measurement uncertainty into OCL/UML primitive datatypes
Authors: Manuel F. Bertoa
Loli Burgueño
Nathalie Moreno
Antonio Vallecillo
Publication date: 04-07-2019
Publisher: Springer Berlin Heidelberg
Published in: Software and Systems Modeling / Issue 5/2020
Print ISSN: 1619-1366
Electronic ISSN: 1619-1374
DOI: https://doi.org/10.1007/s10270-019-00741-0

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