Derrick, J., Doherty, S., Dongol, B. et al. (2 more authors) (2021) Brief announcement: On strong observational refinement and forward simulation. In: 35th International Symposium on Distributed Computing (DISC 2021). 35th International Symposium on Distributed Computing (DISC 2021), 04-08 Oct 2021, Freiburg, Germany. Leibniz International Proceedings in Informatics (LIPIcs), 209 . Schloss Dagstuhl , 55:1-55:4. ISBN 9783959772105
Abstract
Hyperproperties are correctness conditions for labelled transition systems that are more expressive than traditional trace properties, with particular relevance to security. Recently, Attiya and Enea studied a notion of strong observational refinement that preserves all hyperproperties. They analyse the correspondence between forward simulation and strong observational refinement in a setting with finite traces only. We study this correspondence in a setting with both finite and infinite traces. In particular, we show that forward simulation does not preserve hyperliveness properties in this setting. We extend the forward simulation proof obligation with a progress condition, and prove that this progressive forward simulation does imply strong observational refinement.
Metadata
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Copyright, Publisher and Additional Information: | © John Derrick, Simon Doherty, Brijesh Dongol, Gerhard Schellhorn, and Heike Wehrheim; licensed under Creative Commons License CC-BY 4.0 (https://creativecommons.org/licenses/by/4.0/legalcode) | ||||
Keywords: | Strong Observational Refinement; Hyperproperties; Forward Simulation | ||||
Dates: |
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Institution: | The University of Sheffield | ||||
Academic Units: | The University of Sheffield > Faculty of Science (Sheffield) | ||||
Funding Information: |
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Depositing User: | Symplectic Sheffield | ||||
Date Deposited: | 22 Nov 2021 17:03 | ||||
Last Modified: | 22 Nov 2021 17:17 | ||||
Status: | Published | ||||
Publisher: | Schloss Dagstuhl | ||||
Series Name: | Leibniz International Proceedings in Informatics (LIPIcs) | ||||
Refereed: | Yes | ||||
Identification Number: | https://doi.org/10.4230/LIPIcs.DISC.2021.55 | ||||
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