Application of Markov Modeling for Safety Assessment of Self-Diagnostic Programmable Instrumentations and Control Systems = Застосування Марковського моделювання для оцінки функціональної безпеки інформаційних та управляючих систем

Abstract

Markov modeling is a well-known analytical state space modeling technique which is widely applied for quantitative analysis of safety-critical systems. There are few roadblocks for greater application of Markov modeling: accounting of additional system components increases the model state space and complicates analysis; the non-numerically sophisticated user may find it difficult to select method and tool to provide an accurate analysis of constructed Markov model. Thus, achieving highly trusted result for safety-critical systems is a nontrivial task. In this paper we present the case-study on application of Markov modeling with deep testing the model features, for safety analysis of industrial self-diagnostic, programmable FPGA-based Instrumentation and Control system which operates on Nuclear Power Plant.