Selective monitoring
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...
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| Veröffentlicht in: | Journal of computer and system sciences 2021-05, Vol.117, p.99-129 |
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| container_title | Journal of computer and system sciences |
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| creator | Grigore, Radu Kiefer, Stefan |
| description | 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. |
| doi_str_mv | 10.1016/j.jcss.2020.09.003 |
| format | Article |
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| ispartof | Journal of computer and system sciences, 2021-05, Vol.117, p.99-129 |
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| language | eng |
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| source | Elsevier ScienceDirect Journals Complete; Web of Science - Science Citation Index Expanded - 2021<img src="https://exlibris-pub.s3.amazonaws.com/fromwos-v2.jpg" /> |
| subjects | Automata Computer Science Computer Science, Hardware & Architecture Computer Science, Theory & Methods Language equivalence Markov chains Probabilistic systems Runtime monitoring Science & Technology Technology |
| title | Selective monitoring |
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