  Many embedded and real-time systems have a inherent probabilistic behaviour
(sensors data, unreliable hardware,...). In that context, it is crucial to
evaluate system properties such as "the probability that a particular hardware
fails". Such properties can be evaluated by using probabilistic model checking.
However, this technique fails on models representing realistic embedded and
real-time systems because of the state space explosion. To overcome this
problem, we propose a verification framework based on Statistical Model
Checking. Our framework is able to evaluate probabilistic and temporal
properties on large systems modelled in SystemC, a standard system-level
modelling language. It is fully implemented as an extension of the Plasma-lab
statistical model checker. We illustrate our approach on a multi-lift system
case study.

Software Engineering;Logic in Computer Science