AuthorsM. Zhang, B. Selic, S. Ali, T. Yue, O. Okariz and R. Norgren
TitleUnderstanding Uncertainty in Cyber-Physical Systems: A Conceptual Model
AfilliationSoftware Engineering, Software Engineering, Software Engineering
Project(s)U-Test: Testing Cyber-Physical Systems under Uncertainty: Systematic, Extensible, and Configurable Model-based and Search-based Testing Methodologies, The Certus Centre (SFI)
Publication TypeTechnical reports
Year of Publication2015
PublisherSimula Research Laboratory
Other NumbersTR 2015-3
KeywordsCyber-Physical Systems, Model-based Testing, Search-Based Testing, UML, Uncertainty

Uncertainty is intrinsic in most technical systems, including Cyber-Physical Systems (CPS). Therefore, handling uncertainty in a graceful manner during the real operation of CPS is critical. Since designing, developing, and testing modern and highly sophisticated CPS is an expanding field, a step to-wards dealing with uncertainty is to identify, define, and classify uncertainties at various levels of CPS. This will help develop a systematic and comprehen-sive understanding of uncertainty. To that end, we propose a conceptual model for uncertainty specifically designed for CPS. Since the study of uncertainty in CPS development and testing is still irrelatively unexplored, this conceptual model was derived in a large part by reviewing existing work on uncertainty in other fields, including philosophy, physics, statistics, and healthcare. The con-ceptual model is mapped to the three logical levels of CPS: Application, Infra-structure, and Integration. It is captured using UML class diagrams, including relevant OCL constraints. To validate the conceptual model, we identified, clas-sified, and specified uncertainties in two distinct industrial case studies.


This work is supported by U-Test project (Testing Cyber-Physical Systems under Uncertainty).

Citation Key23476