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To accurately make adaptation decisions, a self-adaptive system needs precisemeans to analyze itself at runtime. To this end, runtime verification can beused in the feedback loop to check that the managed system satisfies itsrequirements formalized as temporal-logic properties. These requirements,however, may change due to system evolution or uncertainty in the environment,managed system, and requirements themselves. Thus, the properties underinvestigation by the runtime verification have to be dynamically adapted torepresent the changing requirements while preserving the knowledge aboutrequirements satisfaction gathered thus far, all with minimal latency. Toaddress this need, we present a runtime verification approach for self-adaptivesystems with changing requirements. Our approach uses property specificationpatterns to automatically obtain automata with precise semantics that are thebasis for runtime verification. The automata can be safely adapted duringruntime verification while preserving intermediate verification results toseamlessly reflect requirement changes and enable continuous verification. Weevaluate our approach on an Arduino prototype of the Body Sensor Network andthe Timescales benchmark. Results show that our approach is over five timesfaster than the typical approach of redeploying and restarting runtime monitorsto reflect requirements changes, while improving the system's trustworthinessby avoiding interruptions of verification.

Runtime Verification of Self-Adaptive Systems with Changing Requirements