Proceedings of the First International Workshop on Autonomous Systems Quality Assurance and Prediction with Digital Twins
Marsha Chechik (University of Toronto), Arianna Fedeli (Gran Sasso, Science Institute), Gianluca Filippone (Gran Sasso Science Institute),, Federico Formica (McMaster University), Mirgita Frasheri (Aarhus University),, Nico Hochgeschwender (University of Bremen)
TL;DR
This paper presents the proceedings of ASQAP 2025, focusing on how digital twin technology can enhance quality assurance processes in autonomous systems through various verification and validation methods.
Contribution
It introduces the latest research and industry insights on applying digital twins for quality assurance in autonomous systems, highlighting new approaches and challenges.
Findings
Digital twins improve autonomous system testing and validation.
Enhanced specification and verification methods using digital twins.
Industry-academic collaboration advances in autonomous system assurance.
Abstract
This volume contains the proceedings of the First International Workshop on Autonomous Systems Quality Assurance and Prediction with Digital Twins (ASQAP 2025), which was held in Hamilton, Canada, on May 4th, 2025, as a satellite event of ETAPS 2025. The aim of ASQAP 2025 is to gather experts from academia and industry to explore the potential of digital twin technology in supporting quality assurance in autonomous systems, including concepts such as specification, verification, validation, testing, analysis, and many others.
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