Extended dependency graphs and efficient distributed fixed-point computation

Andreas E. Dalsgaard, Søren Enevoldsen, Peter Fogh, Lasse S. Jensen, Tobias S. Jepsen, Isabella Kaufmann, Kim G. Larsen, Søren M. Nielsen, Mads Chr Olesen, Samuel Pastva, Jiri Srba

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13 Citationer (Scopus)

Abstract

Equivalence and model checking problems can be encoded into computing fixed points on dependency graphs. Dependency graphs represent causal dependencies among the nodes of the graph by means of hyper-edges. We suggest to extend the model of dependency graphs with so-called negation edges in order to increase their applicability. The graphs (as well as the verification problems) suffer from the state space explosion problem. To combat this issue, we design an on-the-fly algorithm for efficiently computing fixed points on extended dependency graphs. Our algorithm supplements previous approaches with the possibility to back-propagate, in certain scenarios, the domain value 0, in addition to the standard back-propagation of the value 1. Finally, we design a distributed version of the algorithm, implement it in an opensource tool, and demonstrate the efficiency of our general approach on the benchmark of Petri net models and CTL queries from the Model Checking Contest 2016.

OriginalsprogEngelsk
TitelApplication and Theory of Petri Nets and Concurrency - 38th International Conference, PETRI NETS 2017, Proceedings
Antal sider20
Vol/bind10258 LNCS
ForlagSpringer
Publikationsdato2017
Sider139-158
ISBN (Trykt)9783319578606
DOI
StatusUdgivet - 2017
Begivenhed38th International Conference on Application and Theory of Petri Nets and Concurrency, PETRI NETS 2017 - Zaragoza, Spanien
Varighed: 25 jun. 201730 jun. 2017

Konference

Konference38th International Conference on Application and Theory of Petri Nets and Concurrency, PETRI NETS 2017
Land/OmrådeSpanien
ByZaragoza
Periode25/06/201730/06/2017
NavnLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Vol/bind10258 LNCS
ISSN0302-9743

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