Static Analysis and Stochastic Search for Reachability Problem

Xinwei Chai (1, 2) , Tony Ribeiro (1) , Morgan Magnin (1, 2) , Olivier Roux (1, 2) , Katsumi Inoue (3)

1 LS2N - Laboratoire des Sciences du Numérique de Nantes
2 LS2N - équipe MéForBio - Méthodes Formelles pour la Bioinformatique
3 NII - National Institute of Informatics

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,

Mots clés: Heuristics; Answer Set Programming; Local Causality Graph; Reachability problem; Asynchronous Binary Automata Network

Domaines: Bio-informatique [q-bio.QM]; Modélisation et simulation

Xinwei Chai, Tony Ribeiro, Morgan Magnin, Olivier Roux, Katsumi Inoue. Static Analysis and Stochastic Search for Reachability Problem. 9th Workshop on Static Analysis and Systems Biology (SASB 2018), Aug 2018, Freiburg, Germany. ⟨hal-01951251⟩