Compositional Verification of Real-time MULTI-CORE SAFETY Critical Systems
MULTI-CORE SAFETY was a three year research project granted by the Danish Council for Independent Research.
The goal of MULTI-CORE-SAFETY can be stated as:
To take a giant leap forward in schedulability analysis for multi-core architectures; analyzing industrial sized systems with more accuracy and flexibility through the use of compositional model checking techniques.
It was grated in 2017, and lasted from August 2017 to July 2021, with a one year extension because of COVID.
The project involved researchers from Aalborg University (Denmark), University of Pennsylvania (USA) and INRIA (France).
- Ulrik Nyman, Associate Professor, Department of Computer Science, Aalborg University
- Brian Nielsen, Associate Professor, Department of Computer Science, Aalborg University
- Insup Lee, Professor at Department of Computer and Information Science, University of Pennsylvania
- Axel Legay, Research Leader of ESTASYS (Efficient STAtistical methods in SYstems of Systems), INRIA Rennes
- Linh Thi Xuan Phan, Assistant Professor at Department of Computer and Information Science, University of Pennsylvania
- Oleg Sokolsky, Research Professor at Department of Computer and Information Science, University of Pennsylvania
- Jalil Boudjadar, Assistant Professor, Software Engineering Department, Aarhus University
- Martin Kristjansen, PhD student, Department of Computer Science, Aalborg University
Publications
- Generic Formal Framework for Compositional Analysis of Hierarchical Scheduling Systems (pdf)
- A Modeling Framework for Schedulability Analysis of Distributed Avionics Systems (pdf)
- A Compositional Approach for Schedulability Analysis of Distributed Avionics Systems (pdf)
- Combining Task-level and System-level Scheduling Modes for Mixed Criticality Systems (pdf) (DS-RT-presentation)
- Schedulability Analysis of Distributed Multi-core Avionics Systems with UPPAAL (Journal page, pdf)
- Model-based optimization of ARINC-653 partition scheduling (pdf)
Project number: DFF-7017-00348
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