Ye, Kangfeng, Foster, Simon orcid.org/0000-0002-9889-9514 and Woodcock, Jim orcid.org/0000-0001-7955-2702 (2021) Automated Reasoning for Probabilistic Sequential Programs with Theorem Proving. In: Fahrenberg, Uli, Gehrke, Mai, Santocanale, Luigi and Winter, Michael, (eds.) Relational and Algebraic Methods in Computer Science - 19th International Conference, RAMiCS 2021, Proceedings. 19th International Conference on Relational and Algebraic Methods in Computer Science, RAMiCS 2021, 02-05 Nov 2021 Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) . Springer , FRA , pp. 465-482.
Abstract
Semantics for nondeterministic probabilistic sequential pro- grams has been well studied in the past decades. In a variety of semantic models, how nondeterministic choice interacts with probabilistic choice is the most significant difference. In He, Morgan, and McIver’s relational model, probabilistic choice refines nondeterministic choice. This model is general because of its predicative-style semantics in Hoare and He’s Unifying Theories of Programming, and suitable for automated reasoning because of its algebraic feature. Previously, we gave probabilistic semantics to the RoboChart notation based on this model, and also formalised the proof that the semantic embedding is a homomorphism, and revealed interesting details. In this paper, we present our mechanisation of the proof in Isabelle/UTP enabling automated reasoning for probabilistic sequential programs including a subset of the RoboChart language. With mechanisation, we even reveal more interesting questions, hidden in the original model. We demonstrate several examples, including an ex- ample to illustrate the interaction between nondeterministic choice and probabilistic choice, and a RoboChart model for randomisation based on binary probabilistic choice.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | Funding Information: This work is funded by the EPSRC projects RoboCalc (Grant EP/M025756/1), RoboTest (Grant EP/R025479/1), and CyPhyAssure (CyPhyAssure Project: https://www.cs.york.ac.uk/circus/CyPhyAssure/) (Grant EP/S001190/1). The icons used in RoboChart have been made by Sarfraz Shoukat, Freepik, Google, Icomoon and Madebyoliver from www.flaticon.com, and are licensed under CC 3.0 BY. Publisher Copyright: © 2021, Springer Nature Switzerland AG. |
Keywords: | probabilistic programs,relational semantics,formal verification,theorem proving,modelling of uncertainty,Unifying Theories of Programming,RoboChart |
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Institution: | The University of York |
Academic Units: | The University of York > Faculty of Sciences (York) > Computer Science (York) |
Depositing User: | Pure (York) |
Date Deposited: | 01 Oct 2021 13:50 |
Last Modified: | 05 Jan 2025 00:46 |
Published Version: | https://doi.org/10.1007/978-3-030-88701-8_28 |
Status: | Published |
Publisher: | Springer |
Series Name: | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
Identification Number: | 10.1007/978-3-030-88701-8_28 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:178721 |