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Verifying Distributed Adaptive Real-Time Systems

Podcast
In this podcast, James Edmondson and Sagar Chaki describe an architecture and approach to engineering high-assurance software for Distributed Adaptive Real-Time (DART) systems.
Publisher

Software Engineering Institute

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Abstract

Making sure government and privately owned drones share international air space safely and effectively is a top priority for government officials. Distributed Adaptive Real-Time (DART) systems are key to many areas of Department of Defense (DoD) capability, including the safe execution of autonomous, multi-unmanned aerial systems missions having civilian benefits. DART systems promise to revolutionize several such areas of mutual civilian-DoD interest, such as robotics, transportation, energy, and health care. To fully realize the potential of DART systems, however, the software controlling them must be engineered for high-assurance and certified to operate safely and effectively. In short, these systems must satisfy guaranteed and highly-critical safety requirements (e.g., collision avoidance) while adapting smartly to achieve application requirements, such as protection coverage, while operating in dynamic and uncertain environments. In this podcast, James Edmondson and Sagar Chaki describe an architecture and approach to engineering high-assurance software for DART systems.

About the Speaker

Sagar Chaki

Sagar Chaki

Sagar Chaki is an SEI alumni employee.

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James Edmondson

James Edmondson

James Edmondson is an SEI alumni employee.

James Edmondson, a senior researcher at the SEI, builds middleware for distributed artificial intelligence. He specializes in real-time systems, control, and distributed algorithms.

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