By the same authors

Efficient runtime quantitative verification using caching, lookahead, and nearly-optimal reconfiguration

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Published copy (DOI)



Publication details

Title of host publication9th International Symposium on Software Engineering for Adaptive and Self-Managing Systems, SEAMS 2014 - Proceedings
DatePublished - 1 Jan 2014
Number of pages10
PublisherAssociation for Computing Machinery (ACM)
Original languageEnglish
ISBN (Print)9781450328647


Self-adaptive systems used in safety-critical and businesscritical applications must continue to comply with strict non-functional requirements while evolving in order to adapt to changing workloads, environments, and goals. Runtime quantitative verification (RQV) has been proposed as an effective means of enhancing self-adaptive systems with this capability. However, RQV frequently fails to provide the fast response times and low computation overheads required by real-world self-adaptive systems. In this paper, we investigate how three techniques, namely caching, lookahead and nearly-optimal reconfiguration, and combinations thereof, can help address this limitation. Extensive experiments in a case study involving the RQV-driven self-adaptation of an unmanned underwater vehicle indicate that these techniques can lead to significant reductions in RQV response times and computation overheads.

    Research areas

  • Continuous-time Markov chains, Probabilistic model checking, Quantitative verification, Self-adaptation


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