Abstract Model-based safety assessment (MBSA) has been one of the major research
thrusts of the System Safety Engineering community for about three decades. It has attracted …

Mastering the complexity of safety assurance for modern, software-intensive systems is
challenging in several domains, such as automotive, robotics, and avionics. Model-based …

Traditional system technology modeling in conceptual aircraft design mainly relies on
empirical knowledge and methods derived from conventional systems, for which valid …

Data-driven models (DDM) based on machine learning and other AI techniques play an
important role in the perception of increasingly autonomous systems. Due to the merely …

Promoted by the internet companies, continuous delivery is more and more appealing to
industries which develop systems with safety-critical functions. Since safety-critical systems …

More-electric, hybrid-electric, and all-electric aircraft have one important thing in common:
they increasingly rely on electrical components and electrical power systems for fulfilling …

Mastering the complexity of safety assurance for modern, software-intensive systems is
challenging in several domains, such as automotive, robotics, and avionics. Model-based …

In order to assess AI/ML-based systems in terms of safety, is it not sufficient to assure the
system in terms of possible failure but also consider functional weaknesses/insufficiencies of …

Fault Tree analysis is a widely used failure analysis methodology to assess a system in
terms of safety or reliability in many industrial application domains. However, with Fault Tree …

The rapid advancement of autonomy in robotic systems together with the increasing
interaction with humans in shared workspaces (eg collaborative robots), raises pressing …