Quantitative Safety: Linking Proof-Based Verification with Model Checking for Probabilistic Systems

This paper presents a novel approach for augmenting proof-based verification with performance-style analysis of the kind employed in state-of-the-art model checking tools for probabilistic systems. Quantitative safety properties usually specified as probabilistic system invariants and modeled in pro...

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Main Author: Ukachukwu Ndukwu
Format: Article
Language:English
Published: Open Publishing Association 2009-12-01
Series:Electronic Proceedings in Theoretical Computer Science
Online Access:http://arxiv.org/pdf/0912.1900v1
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author Ukachukwu Ndukwu
author_facet Ukachukwu Ndukwu
author_sort Ukachukwu Ndukwu
collection DOAJ
description This paper presents a novel approach for augmenting proof-based verification with performance-style analysis of the kind employed in state-of-the-art model checking tools for probabilistic systems. Quantitative safety properties usually specified as probabilistic system invariants and modeled in proof-based environments are evaluated using bounded model checking techniques. Our specific contributions include the statement of a theorem that is central to model checking safety properties of proof-based systems, the establishment of a procedure; and its full implementation in a prototype system (YAGA) which readily transforms a probabilistic model specified in a proof-based environment to its equivalent verifiable PRISM model equipped with reward structures. The reward structures capture the exact interpretation of the probabilistic invariants and can reveal succinct information about the model during experimental investigations. Finally, we demonstrate the novelty of the technique on a probabilistic library case study.
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spelling doaj.art-8b7cd338a0c74b5e87fb0af7bbb5730d2022-12-22T01:19:31ZengOpen Publishing AssociationElectronic Proceedings in Theoretical Computer Science2075-21802009-12-0113Proc. QFM 2009273910.4204/EPTCS.13.3Quantitative Safety: Linking Proof-Based Verification with Model Checking for Probabilistic SystemsUkachukwu NdukwuThis paper presents a novel approach for augmenting proof-based verification with performance-style analysis of the kind employed in state-of-the-art model checking tools for probabilistic systems. Quantitative safety properties usually specified as probabilistic system invariants and modeled in proof-based environments are evaluated using bounded model checking techniques. Our specific contributions include the statement of a theorem that is central to model checking safety properties of proof-based systems, the establishment of a procedure; and its full implementation in a prototype system (YAGA) which readily transforms a probabilistic model specified in a proof-based environment to its equivalent verifiable PRISM model equipped with reward structures. The reward structures capture the exact interpretation of the probabilistic invariants and can reveal succinct information about the model during experimental investigations. Finally, we demonstrate the novelty of the technique on a probabilistic library case study.http://arxiv.org/pdf/0912.1900v1
spellingShingle Ukachukwu Ndukwu
Quantitative Safety: Linking Proof-Based Verification with Model Checking for Probabilistic Systems
Electronic Proceedings in Theoretical Computer Science
title Quantitative Safety: Linking Proof-Based Verification with Model Checking for Probabilistic Systems
title_full Quantitative Safety: Linking Proof-Based Verification with Model Checking for Probabilistic Systems
title_fullStr Quantitative Safety: Linking Proof-Based Verification with Model Checking for Probabilistic Systems
title_full_unstemmed Quantitative Safety: Linking Proof-Based Verification with Model Checking for Probabilistic Systems
title_short Quantitative Safety: Linking Proof-Based Verification with Model Checking for Probabilistic Systems
title_sort quantitative safety linking proof based verification with model checking for probabilistic systems
url http://arxiv.org/pdf/0912.1900v1
work_keys_str_mv AT ukachukwundukwu quantitativesafetylinkingproofbasedverificationwithmodelcheckingforprobabilisticsystems