SYLOPFSYAug 2, 2016

Rate Reduction for State-labelled Markov Chains with Upper Time-bounded CSL Requirements

arXiv:1608.006587 citations
Originality Synthesis-oriented
AI Analysis

For researchers in formal verification and performance analysis, this work provides a method to adjust system parameters to meet probabilistic timing constraints.

The paper proposes algorithms to reduce controllable transition rates in continuous-time Markov chains so that states satisfy upper time-bounded CSL requirements. The algorithms are simple and based on a natural state space partitioning.

This paper presents algorithms for identifying and reducing a dedicated set of controllable transition rates of a state-labelled continuous-time Markov chain model. The purpose of the reduction is to make states to satisfy a given requirement, specified as a CSL upper time-bounded Until formula. We distinguish two different cases, depending on the type of probability bound. A natural partitioning of the state space allows us to develop possible solutions, leading to simple algorithms for both cases.

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