Logic and stochastic modeling with S m A r T

We describe the main features of SmArT, a software package providing a seamless environment for the logic and probabilistic analysis of complex systems. SmArT can combine different formalisms in the same modeling study. For the analysis of logical behavior, both explicit and symbolic state-space generation techniques, as well as symbolic CTL model-checking algorithms, are available. For the study of stochastic and timing behavior, both sparse-storage and Kronecker-based numerical solution approaches are available when the underlying process is a Markov chain, while discrete-event simulation is always applicable regardless of the stochastic nature of the process, and certain classes of non-Markov models can also be solved numerically. Finally, since SmArT targets both the classroom and realistic industrial settings as a learning, research, and application tool, it is written in a modular way that allows for easy integration of new formalisms and solution algorithms.