Expressing Measurement Uncertainty in Software Models

Abstract

Uncertainty is an inherent property of any measure or estimation performed in any physical setting, and therefore it needs to be taken into consideration when modelling systems that manage real data. Although several modelling 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 and difficult to achieve at the model level. This paper proposes an extension of the UML and OCL types to incorporate data uncertainty coming from physical measurements or user estimations into the models, together with the set of operations defined for the values of these types.