Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 14-Day Trial for You or Your Team.

Learn More →

Simulation-based minimization

Simulation-based minimization We present a minimization algorithm that receives a Kripke structure M and returns the smallest structure that is simulation equivalent to M . The simulation equivalence relation is weaker than bisimulation but stronger than the simulation preorder. It strongly preserves ACTL and LTL (as sublogics of ACTL*).We show that every structure M has a unique-up-to-isomorphism reduced structure that is simulation equivalent to M and smallest in size. Our Minimizing Algorithm constructs this reduced structure. It first constructs the quotient structure for M , then eliminates transitions to little brothers, and finally deletes unreachable states.Since the first step of the algorithm is based on the simulation preorder over M , it has maximal space requirements. To reduce them, we present the Partitioning Algorithm, which constructs the quotient structure for M without ever building the simulation preorder. The Partitioning Algorithm has improved space complexity, but its time complexity might have worse. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png ACM Transactions on Computational Logic (TOCL) Association for Computing Machinery

Loading next page...
 
/lp/association-for-computing-machinery/simulation-based-minimization-F9skHZX9g8

References (23)

Publisher
Association for Computing Machinery
Copyright
Copyright © 2003 by ACM Inc.
ISSN
1529-3785
DOI
10.1145/635499.635502
Publisher site
See Article on Publisher Site

Abstract

We present a minimization algorithm that receives a Kripke structure M and returns the smallest structure that is simulation equivalent to M . The simulation equivalence relation is weaker than bisimulation but stronger than the simulation preorder. It strongly preserves ACTL and LTL (as sublogics of ACTL*).We show that every structure M has a unique-up-to-isomorphism reduced structure that is simulation equivalent to M and smallest in size. Our Minimizing Algorithm constructs this reduced structure. It first constructs the quotient structure for M , then eliminates transitions to little brothers, and finally deletes unreachable states.Since the first step of the algorithm is based on the simulation preorder over M , it has maximal space requirements. To reduce them, we present the Partitioning Algorithm, which constructs the quotient structure for M without ever building the simulation preorder. The Partitioning Algorithm has improved space complexity, but its time complexity might have worse.

Journal

ACM Transactions on Computational Logic (TOCL)Association for Computing Machinery

Published: Apr 1, 2003

There are no references for this article.