An Extension of HybridSynchAADL and Its Application to Collaborating Autonomous UAVs - Lee, Jaehun; Bae, Kyungmin; Ölveczky, Peter Csaba (Leveraging Applications of Formal Methods, Verification and Validation. Adaptation and Learning, 2022)
Many collective adaptive systems consist of distributed nodes that communicate with each other and with their physical environments, but that logically should operate in a synchronous way. HybridSynchAADL is a recent modeling language and formal analysis tool for such virtually synchronous cyber-physical systems (CPSs). HybridSynchAADL uses the Hybrid PALS equivalence to reduce the hard problem of designing and verifying virtually synchronous CPSs—with network delays, asynchronous communication, imprecise local clocks, continuous dynamics, etc.—to the much easier tasks of designing and verifying their underlying synchronous designs. Up to now HybridSynchAADL has lacked important programming language features, such as compound data types and user-defined functions, which made it difficult to model advanced control logics of collective adaptive systems. In this paper, we extend the HybridSynchAADL language, its formal semantics, and its analysis tool to support these programming language features. We apply our extension of HybridSynchAADL to design and analyze a collection of collaborating autonomous drones that adapt to their environments.