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Selective monitoring

Abstract:
We study selective monitors for labelled Markov chains. Monitors observe the outputs that are generated by a Markov chain during its run, with the goal of identifying runs as correct or faulty. A monitor is selective if it skips observations in order to reduce monitoring overhead. We are interested in monitors that minimize the expected number of observations. We establish an undecidability result for selectively monitoring general Markov chains. On the other hand, we show for non-hidden Markov chains (where any output identifies the state the Markov chain is in) that simple optimal monitors exist and can be computed efficiently, based on DFA language equivalence. These monitors do not depend on the precise transition probabilities in the Markov chain. We report on experiments where we compute these monitors for several open-source Java projects.
Publication status:
Published
Peer review status:
Reviewed (other)

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Publisher copy:
10.4230/LIPIcs.CONCUR.2018.20

Authors


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Institution:
University of Oxford
Division:
MPLS
Department:
Computer Science
Role:
Author


Publisher:
Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik
Host title:
29th International Conference on Concurrency Theory (CONCUR 2018) Beijing, China, September 4-7, 2018
Journal:
29th International Conference on Concurrency Theory More from this journal
Volume:
118
Pages:
20:1--20:16
Publication date:
2018-08-13
Acceptance date:
2018-06-08
DOI:
ISSN:
1868-8969
ISBN:
9783959770873


Pubs id:
pubs:859768
UUID:
uuid:9155eae0-4f63-4bb3-a83b-f9447115d38a
Local pid:
pubs:859768
Source identifiers:
859768
Deposit date:
2018-06-29

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