Neural networks as a machine learning technique are increasingly deployed in various domains. Despite their performance and their continuous improvement, the deployment of neural networks in safety-critical systems, in particular for autonomous mobility, ...

Abstraction-based techniques are an attractive approach for synthesizing correct-by-construction controllers to satisfy high-level temporal requirements. A main bottleneck for successful application of these techniques is the memory requirement, both ...

We present a scalable methodology to verify stochastic hybrid systems for inequality linear temporal logic (iLTL) or inequality metric interval temporal logic (iMITL). Using the Mori–Zwanzig reduction method, we construct a finite-state Markov chain ...

We consider the problem of safety analysis of probabilistic hybrid systems, which capture discrete, continuous and probabilistic behaviors. We present a novel counterexample guided abstraction refinement (CEGAR) algorithm for a subclass of probabilistic ...

We propose techniques to construct abstractions for nonlinear dynamics in terms of relations expressed in linear arithmetic. Such relations are useful for translating the closed loop verification problem of control software with continuous-time, ...

We propose and extend an approach for the verification of safety properties for parameterized timed systems modeled as networks of timed automata. For this task, we introduce an incremental workflow that is based on our algorithm IC3 with Zones. It ...

Abstractions can cause spurious results, which need to be verified in the concrete system to gain conclusive results. Verification based on a multi-valued logic can distinguish between conclusive and inconclusive results, provides increased precision, ...