11th EAI International Conference on Performance Evaluation Methodologies and Tools

Research Article

Perturbation of CTMC Trapping Probabilities with Application to Model Repair

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BibTeX Plain Text
  • @INPROCEEDINGS{10.4108/eai.5-12-2017.2274314,
    author={Alexander  Gouberman and Markus  Siegle and Bharath Siva Kumar  Tati},
    title={Perturbation of CTMC Trapping Probabilities with Application to Model Repair},
    proceedings={11th EAI International Conference on Performance Evaluation Methodologies and Tools},
    publisher={ACM},
    proceedings_a={VALUETOOLS},
    year={2018},
    month={8},
    keywords={markov chain perturbation trapping probability monotonicity csl model checking model repair},
    doi={10.4108/eai.5-12-2017.2274314}
}
  • Alexander Gouberman
    Markus Siegle
    Bharath Siva Kumar Tati
    Year: 2018
    Perturbation of CTMC Trapping Probabilities with Application to Model Repair
    VALUETOOLS
    ACM
    DOI: 10.4108/eai.5-12-2017.2274314
Alexander Gouberman1,*, Markus Siegle1, Bharath Siva Kumar Tati1
  • 1: Informatik III, Universität der Bundeswehr München, Germany
*Contact email: alexander.gouberman@unibw.de

Abstract

This paper studies properties of continuous-time Markov chains with one class of transient states and at least two absorbing states. We look at a perturbation of the chain that arises by uniformly decreasing all rates to absorption. For this situation, the monotonicity of the trapping probabilities is analysed, and their asymptotic limit is computed. The theoretical findings are then applied to a type of model repair problem, where a lower time-bounded and lower probability-bounded CSL until requirement needs to be satisfied. The paper presents an algorithm for this type of problem and proves its correctness.

Keywords
markov chain perturbation trapping probability monotonicity csl model checking model repair
Published
2018-08-10
Publisher
ACM
http://dx.doi.org/10.4108/eai.5-12-2017.2274314
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