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.Základní údaje
Originální název
Start Pruning When Time Gets Urgent: Partial Order Reduction for Timed Systems
Autoři
BOENNELAND, Frederik M. (208 Dánsko), Peter G. JENSEN (208 Dánsko), Kim G. LARSEN (208 Dánsko), Marco MUNIZ (604 Peru) a Jiří SRBA (203 Česká republika, garant, domácí)
Vydání
Netherlands, Proceedings of the 30th International Conference on Computer Aided Verification (CAV'18), od s. 527-546, 20 s. 2018
Nakladatel
Springer
Další údaje
Jazyk
angličtina
Typ výsledku
Stať ve sborníku
Obor
10201 Computer sciences, information science, bioinformatics
Stát vydavatele
Nizozemské království
Utajení
není předmětem státního či obchodního tajemství
Forma vydání
tištěná verze "print"
Odkazy
Impakt faktor
Impact factor: 0.402 v roce 2005
Kód RIV
RIV/00216224:14330/18:00106625
Organizační jednotka
Fakulta informatiky
ISBN
978-3-319-96144-6
ISSN
UT WoS
000491481600028
Klíčová slova anglicky
partial order reduction; timed-arc Petri nets; stubborn sets
Změněno: 16. 5. 2022 14:34, Mgr. Michal Petr
Anotace
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.