Research Blog

EDDIs will be useful to you if you develop an autonomous system, a driverless car, or a mobile robot, or a complex system of systems such as a multi-robot factory system, or a swarm of drones performing a collaborative task, e.g. inspection and maintenance. The autonomy and open/cooperative nature of these systems pose new challenges for dependability. We explore how these can be addressed with new dependability monitoring technologies. Autonomous vehicles, unmanned aerial

Large Language Models (LLMs) have rapidly transformed how industries approach complex decision-making, from customer service automation to high-stakes operational environments. As their deployment expands into safety-critical domains, the need for robust mechanisms to prevent unsafe outputs and hallucinations has never been more urgent. To address this, researchers at the University of Hull have introduced SafeLLM, a novel framework that combines statistical safety filtering

HIP-HOPS: Automated Dependability Analysis and Evolutionary Design of Systems - HiP-HOPS tool website Challenge Imagine that you develop a steer-by-wire systems of cars. In Fig. 1, you see a high-level Matlab-Simulink model of a steer-by-wire system that has been designed by Volvo. Fig. 1. Example of a complex system: top-level model of a steer-by-wire system for cars by Volvo The model is already complex with many components and interactions; most of the boxes are sub