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Static Analysis and Stochastic Search for Reachability Problem
Author(s) -
Xinwei Chai,
Tony Ribeiro,
Morgan Magnin,
Olivier Roux,
Katsumi Inoue
Publication year - 2020
Publication title -
electronic notes in theoretical computer science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.242
H-Index - 60
ISSN - 1571-0661
DOI - 10.1016/j.entcs.2020.06.008
Subject(s) - reachability , computer science , automaton , asynchronous communication , static analysis , theoretical computer science , binary number , state space , hybrid system , reachability problem , mathematical optimization , mathematics , machine learning , computer network , statistics , arithmetic , programming language
This paper focuses on a major improvement on the analysis of reachability properties in large-scale dynamical biological models. To tackle such models, where classical model checkers fail due to state space explosion led by exhaustive search. Alternative static analysis approaches have been proposed, but they may also fail in certain cases due to non-exhaustive search. In this paper, we introduce a hybrid approach ASPReach, which combines static analysis and stochastic search to break the limits of both approaches. We tackle this issue on a modeling framework we recently introduced, Asynchronous Binary Automata Network (ABAN). We show that ASPReach is able to analyze efficiently some reachability properties which could not be solved by existing methods. We studied also various cases from biological literature, emphasizing the merits of our approach in terms of conclusiveness and performance. keyword: Model checking,

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