“…The test of condition (F implies t < t ) (step 6.3) is done in O(1) as follows D t t < 0. Recall that: The correctness and the completeness of this partial order are shown in [12,14] for one-safe and non zeno time Petri nets with no unbounded intervals. The non zenoness assumption guarantees that each enabled transition will eventually become firable unless it is disabled by another firing.…”
Section: Partial Order Reductionsmentioning
confidence: 99%
“…Several approaches have been developed that apply partial order reduction to model checking systems: the persistent set method [8], the ample set method [9], the stubborn set method [13], and the ready set method [11,12]. The common characteristic of all these methods is that they explore only a certain subset of execution paths from each state (state class).…”
Section: Partial Order Reductionsmentioning
confidence: 99%
“…Partial order reduction techniques take advantage of this by generating and exploring a graph with only a reduced set of firing sequences. At the same time, in order to preserve the truth value of the property to be verified, the reduced graph should contain, at least, one representative firing sequence from each class of equivalent firing sequences [5,6,8,9,10,11,12,13]. This paper proposes an efficient abstraction for time Petri nets which is both smaller and faster to compute than those proposed in the literature.…”
Section: Introductionmentioning
confidence: 96%
“…Many techniques have been developed to alleviate this problem. Among these techniques, we consider here the abstraction [1,2,3,4,7,10,11] and partial order techniques [5,6,8,9,11,12,13,14].…”
We consider here Time Petri nets (TPN model). We first propose an abstraction to its generally infinite state space which preserves linear properties 1 of the TPN model. Comparing with TPN abstractions proposed in the literature, our abstraction produces graphs which are both smaller and faster to compute. In addition, our characterization of abstracted states allows a significative gain in space. Afterwards, we show how to apply Yoneda's partial order reduction technique to construct directly reduced graphs useful to verify LT L −X properties of the model. Using our approach, both time and space complexities are significantly reduced.
“…The test of condition (F implies t < t ) (step 6.3) is done in O(1) as follows D t t < 0. Recall that: The correctness and the completeness of this partial order are shown in [12,14] for one-safe and non zeno time Petri nets with no unbounded intervals. The non zenoness assumption guarantees that each enabled transition will eventually become firable unless it is disabled by another firing.…”
Section: Partial Order Reductionsmentioning
confidence: 99%
“…Several approaches have been developed that apply partial order reduction to model checking systems: the persistent set method [8], the ample set method [9], the stubborn set method [13], and the ready set method [11,12]. The common characteristic of all these methods is that they explore only a certain subset of execution paths from each state (state class).…”
Section: Partial Order Reductionsmentioning
confidence: 99%
“…Partial order reduction techniques take advantage of this by generating and exploring a graph with only a reduced set of firing sequences. At the same time, in order to preserve the truth value of the property to be verified, the reduced graph should contain, at least, one representative firing sequence from each class of equivalent firing sequences [5,6,8,9,10,11,12,13]. This paper proposes an efficient abstraction for time Petri nets which is both smaller and faster to compute than those proposed in the literature.…”
Section: Introductionmentioning
confidence: 96%
“…Many techniques have been developed to alleviate this problem. Among these techniques, we consider here the abstraction [1,2,3,4,7,10,11] and partial order techniques [5,6,8,9,11,12,13,14].…”
We consider here Time Petri nets (TPN model). We first propose an abstraction to its generally infinite state space which preserves linear properties 1 of the TPN model. Comparing with TPN abstractions proposed in the literature, our abstraction produces graphs which are both smaller and faster to compute. In addition, our characterization of abstracted states allows a significative gain in space. Afterwards, we show how to apply Yoneda's partial order reduction technique to construct directly reduced graphs useful to verify LT L −X properties of the model. Using our approach, both time and space complexities are significantly reduced.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.