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Local abstraction refinement for probabilistic timed programs

Abstract:

We consider models of programs that incorporate probability, dense real-time and data. We present a new abstraction refinement method for computing minimum and maximum reachability probabilities for such models. Our approach uses strictly local refinement steps to reduce both the size of abstractions generated and the complexity of operations needed, in comparison to previous approaches of this kind. We implement the techniques and evaluate them on a selection of large case studies, including...

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Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1016/j.tcs.2013.07.013

Authors


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Institution:
University of Oxford
Division:
MPLS Division
Department:
Computer Science
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MPLS
Department:
Computer Science
Oxford college:
Trinity College
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MPLS Division
Department:
Computer Science
Role:
Author
Publisher:
Elsevier Publisher's website
Journal:
Theoretical Computer Science Journal website
Volume:
538
Pages:
37-53
Publication date:
2013-08-01
DOI:
ISSN:
0304-3975
Keywords:
Pubs id:
pubs:518308
UUID:
uuid:e821293c-2794-4fb9-9dbd-448ddcadd558
Local pid:
pubs:518308
Source identifiers:
518308
Deposit date:
2020-01-12

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