With the down-scaling of CMOS technology, the design complexity of very large-scale
integrated is increasing. Although the application of machine learning (ML) techniques in …

A method for approximate model checking of stochastic hybrid systems with provable
approximation guarantees is proposed. We focus on the probabilistic invariance problem for …

This work is concerned with the generation of finite abstractions of general state-space
processes to be employed in the formal verification of probabilistic properties by means of …

This paper deals with the problem of safety verification of non-linear hybrid systems. We start
from a classical method that uses interval arithmetic to check whether trajectories can move …

The interplay of random phenomena and continuous dynamics deserves increased
attention, especially in the context of wireless sensing and control applications. Safety …

Emerging industrial platforms such as the Internet of Things (IoT), Industrial Internet (II) in the
US and Industrie 4.0 in Europe have tremendously accelerated the development of new …

The availability of representative datasets is an essential prerequisite for many successful
artificial intelligence and machine learning models. However, in real life applications these …

We revisit the symbolic verification of Markov chains with respect to finite horizon
reachability properties. The prevalent approach iteratively computes step-bounded state …

Currently, detecting and isolating faults in hybrid systems is often done manually with the
help of human operators. In this paper we present a novel model-based diagnosis approach …

Stochastic reachability analysis (SRA) is a method of analyzing the behavior of control
systems which mix discrete and continuous dynamics. For probabilistic discrete systems it …