Dependability Analysis of Control Systems using SystemC and Statistical Model Checking

TL;DR

This paper introduces a framework combining SystemC modeling of stochastic Petri nets with statistical model checking to analyze the dependability of large embedded control systems, demonstrated through a case study.

Contribution

It presents a novel integration of stochastic Petri nets in SystemC with statistical model checking for dependability analysis of control systems.

Findings

Effective modeling of large embedded systems

Versatile property verification capabilities

Successful case study validation

Abstract

Stochastic Petri nets are commonly used for modeling distributed systems in order to study their performance and dependability. This paper proposes a realization of stochastic Petri nets in SystemC for modeling large embedded control systems. Then statistical model checking is used to analyze the dependability of the constructed model. Our verification framework allows users to express a wide range of useful properties to be verified which is illustrated through a case study.