D 2018

Start Pruning When Time Gets Urgent: Partial Order Reduction for Timed Systems

BOENNELAND, Frederik M., Peter G. JENSEN, Kim G. LARSEN, Marco MUNIZ, Jiří SRBA et. al.

Basic information

Original name

Start Pruning When Time Gets Urgent: Partial Order Reduction for Timed Systems

Authors

BOENNELAND, Frederik M. (208 Denmark), Peter G. JENSEN (208 Denmark), Kim G. LARSEN (208 Denmark), Marco MUNIZ (604 Peru) and Jiří SRBA (203 Czech Republic, guarantor, belonging to the institution)

Edition

Netherlands, Proceedings of the 30th International Conference on Computer Aided Verification (CAV'18), p. 527-546, 20 pp. 2018

Publisher

Springer

Other information

Language

English

Type of outcome

Stať ve sborníku

Field of Study

10201 Computer sciences, information science, bioinformatics

Country of publisher

Netherlands

Confidentiality degree

není předmětem státního či obchodního tajemství

Publication form

printed version "print"

References:

Impact factor

Impact factor: 0.402 in 2005

RIV identification code

RIV/00216224:14330/18:00106625

Organization unit

Faculty of Informatics

ISBN

978-3-319-96144-6

ISSN

UT WoS

000491481600028

Keywords in English

partial order reduction; timed-arc Petri nets; stubborn sets
Změněno: 16/5/2022 14:34, Mgr. Michal Petr

Abstract

V originále

Partial order reduction for timed systems is a challenging topic due to the dependencies among events induced by time acting as a global synchronization mechanism. So far, there has only been a limited success in finding practically applicable solutions yielding significant state space reductions. We suggest a working and efficient method to facilitate stubborn set reduction for timed systems with urgent behaviour. We first describe the framework in the general setting of timed labelled transition systems and then instantiate it to the case of timed-arc Petri nets. The basic idea is that we can employ classical untimed partial order reduction techniques as long as urgent behaviour is enforced. Our solution is implemented in the model checker TAPAAL and the feature is now broadly available to the users of the tool. By a series of larger case studies, we document the benefits of our method and its applicability to real-world scenarios.