Dependability Analysis of Control Systems using SystemC and Statistical Model Checking
This work addresses dependability verification for embedded control systems, but it appears incremental by applying existing techniques to a specific domain.
The paper tackled the modeling and analysis of large embedded control systems by implementing stochastic Petri nets in SystemC and using statistical model checking to verify dependability properties, as demonstrated in a case study.
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.