---
res:
bibo_abstract:
- The fundamental model-checking problem, given as input a model and a specification,
asks for the algorithmic verification of whether the model satisfies the specification.
Two classical models for reactive systems are graphs and Markov decision processes
(MDPs). A basic specification formalism in the verification of reactive systems
is the strong fairness (aka Streett) objective, where given different types of
requests and corresponding grants, the requirement is that for each type, if the
request event happens infinitely often, then the corresponding grant event must
also happen infinitely often. All omega-regular objectives can be expressed as
Streett objectives and hence they are canonical in verification. Consider graphs/MDPs
with n vertices, m edges, and a Streett objectives with k pairs, and let b denote
the size of the description of the Streett objective for the sets of requests
and grants. The current best-known algorithm for the problem requires time O(min(n^2,
m sqrt{m log n}) + b log n). In this work we present randomized near-linear time
algorithms, with expected running time O~(m + b), where the O~ notation hides
poly-log factors. Our randomized algorithms are near-linear in the size of the
input, and hence optimal up to poly-log factors. @eng
bibo_authorlist:
- foaf_Person:
foaf_givenName: Krishnendu
foaf_name: Chatterjee, Krishnendu
foaf_surname: Chatterjee
foaf_workInfoHomepage: http://www.librecat.org/personId=2E5DCA20-F248-11E8-B48F-1D18A9856A87
orcid: 0000-0002-4561-241X
- foaf_Person:
foaf_givenName: Wolfgang
foaf_name: Dvorák, Wolfgang
foaf_surname: Dvorák
- foaf_Person:
foaf_givenName: Monika
foaf_name: Henzinger, Monika
foaf_surname: Henzinger
- foaf_Person:
foaf_givenName: Alexander
foaf_name: Svozil, Alexander
foaf_surname: Svozil
bibo_doi: 10.4230/LIPICS.CONCUR.2019.7
bibo_volume: 140
dct_date: 2019^xs_gYear
dct_language: eng
dct_publisher: Schloss Dagstuhl - Leibniz-Zentrum für Informatik@
dct_title: Near-linear time algorithms for Streett objectives in graphs and MDPs@
...