Paul Butcher
- UK Programme Manager and Head of Dynamic Analysis
- AdaCore, UK
Paul is the UK Programme Manager, Head of Dynamic Analysis for AdaCore, and the Lead Engineer for GNATfuzz. He has over 25 years of experience in developing and verifying embedded safety-critical real-time systems. Before joining AdaCore, Paul was a consultant engineer, working for UK aerospace companies such as Leonardo Helicopters, BAE Systems, Thales UK, and QinetiQ. Before becoming a consultant, Paul worked as a Software Developer and Safety Engineer for the Typhoon platform, safety-critical automated train driving software, military UAVs, the Tactical Processor for the Wildcat platform, and mission planning systems for Typoon, EH101, and Wildcat. Paul graduated from the University of Portsmouth with a Bachelor’s Degree with Honours in Computing and a Higher National Diploma in Software Engineering.
Sessions
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AI and ML in Testing
Accelerating Airworthiness: Automation's Role in Faster Verification for DO-178C Certification
AI and ML are emerging in aerospace and avionics, raising complex testing and certification challenges, presenting significant verification and validation challenges. AI use cases are broadly categorized into narrow/specialized AI (e.g., object detection) and generative models, which pose greater unpredictability due to non-deterministic outputs. Current architectures favour non-safety-critical, passive AI/ML systems operating in parallel with primary avionics functions—supporting anomaly detection, predictive maintenance, and decision support. In light of limited data availability, what methods are most appropriate for testing and validating? How do you approach verification and validation of non-deterministic AI systems within the constraints of deterministic safety standards like ED-324/DO-178C? Where will EUROCAE technical standards (WG114) support the development of systems and the certification of aeronautical systems implementing AI-technologies?