Symbolic Model Checking of stutter invariant properties Using Generalized Testing Automata

Ala Eddine Ben Salem 1 Alexandre Duret-Lutz Fabrice Kordon 1 Yann Thierry-Mieg 1
1 MoVe - Modélisation et Vérification
LIP6 - Laboratoire d'Informatique de Paris 6
Abstract : In a previous work, we showed that a kind of ω-automata known as Transition-based Generalized Testing Automata (TGTA) can outperform the Büchi automata traditionally used for explicit model checking when verifying stutter-invariant properties. In this work, we investigate the use of these generalized testing automata to improve symbolic model checking of stutter-invariant LTL properties. We propose an efficient symbolic encoding of stuttering transitions in the product between a model and a TGTA. Saturation techniques available for decision diagrams then benefit from the presence of stuttering self-loops on all states of TGTA. Experimentation of this approach confirms that it outperforms the symbolic approach based on (transition-based) Generalized Büchi Automata.
Type de document :
Communication dans un congrès
20th International Conference on Tools and Algorithms for the Construction and Analysis of Systems, TACAS 2014, Apr 2014, Grenoble, France. Springer, 8413, pp.440-454, Lecture Notes in Computer Science. 〈10.1007/978-3-642-54862-8_38〉
Liste complète des métadonnées
https://hal.archives-ouvertes.fr/hal-01216559
Contributeur : Lip6 Publications <>
Soumis le : vendredi 16 octobre 2015 - 14:38:01
Dernière modification le : jeudi 22 novembre 2018 - 15:04:54

Lien texte intégral

openaccess

Identifiants

Collections

UPMC | LIP6 | SORBONNE-UNIVERSITE

Citation

Ala Eddine Ben Salem, Alexandre Duret-Lutz, Fabrice Kordon, Yann Thierry-Mieg. Symbolic Model Checking of stutter invariant properties Using Generalized Testing Automata. 20th International Conference on Tools and Algorithms for the Construction and Analysis of Systems, TACAS 2014, Apr 2014, Grenoble, France. Springer, 8413, pp.440-454, Lecture Notes in Computer Science. 〈10.1007/978-3-642-54862-8_38〉. 〈hal-01216559〉

Exporter

BibTeX TEI DC DCterms EndNote

Partager

Métriques

Consultations de la notice

85

Contact

support.ccsd.cnrs.fr
hal.support@ccsd.cnrs.fr
Logo CCSD