Quantitative verification tools compute probabilities, expected rewards, or steady-state
values for formal models of stochastic and timed systems. Exact results often cannot be …

Statistical model checking avoids the state space explosion problem in verification and
naturally supports complex non-Markovian formalisms. Yet as a simulation-based approach …

Statistical model checking avoids the state space explosion problem in verification and
naturally supports complex non-Markovian formalisms. Yet as a simulation-based approach …

Neural networks (NN) are taking over ever more decisions thus far taken by humans, even
though verifiable system-level guarantees are far out of reach. Neither is the verification …

The analysis of formal models that include quantitative aspects such as timing or
probabilistic choices is performed by quantitative verification tools. Broad and mature tool …

We present an overview of Plasma Lab, a modular statistical model checking (SMC) platform
that facilitates multiple SMC algorithms, multiple modelling and query languages and has …

We depend on the safe, reliable, and timely operation of cyber-physical systems ranging
from smart grids to avionics components. Many of them involve time-dependent behaviours …

Lightweight scheduler sampling brings statistical model checking to nondeterministic
formalisms with undiscounted properties, in constant memory. Its direct application to …

Markov automata are a compositional modelling formalism with continuous stochastic time,
discrete probabilities, and nondeterministic choices. In this article, we present extensions to …

In the formal verification of stochastic systems, statistical model checking uses simulation to
overcome the state space explosion problem of probabilistic model checking. Yet its runtime …