TAPAAL SMC: Statistical Model Checking of Stochastic Timed-Arc Petri Nets
For researchers and practitioners modeling stochastic real-time systems, this work provides a new modeling formalism and verification tool for TAPNs with stochastic behavior.
The paper introduces the first stochastic semantics for Timed-Arc Petri Nets (TAPNs) and implements statistical model checking (SMC) algorithms in the TAPAAL tool, demonstrating practical applicability on case studies.
Timed-Arc Petri net (TAPN) is a timed extension of the classical Petri net model where tokens have their age and input arcs are associated with time intervals restricting the ages of tokens available for transition firing. Additionally, a TAPN can also contain place invariants constraining the ages of tokens in places, inhibitor arcs preventing a transition from firing and transport arcs that preserve token ages upon firing. This set of features, as much as it allows us to model complex systems, also often makes verification problems computationally hard or even undecidable. Moreover, in order to model real-life examples, additional stochastic aspects are often necessary to capture the desired behaviour. We suggest the first stochastic semantics for TAPNs and design and implement the quantitative and qualitative Statistical Model Checking (SMC) algorithms in the model checker TAPAAL. We argue for the semantic choices we made in the stochastic semantics and prove that the semantics is well-behaving. On a number of case studies we demonstrate the practical applicability of our modelling formalism and its SMC implementation.