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International Journal of Reconfigurable Computing
Volume 2014, Article ID 724585, 8 pages
Research Article

Using Statistical Assertions to Guide Self-Adaptive Systems

1Department of Computing, Imperial College London, 180 Queen’s Gate, London SW7 2AZ, UK
2Software Engineering, EADS Innovation Works, Willy-Messerschmitt Street 1, 85521 Ottobrunn, Germany

Received 7 January 2014; Accepted 4 March 2014; Published 13 April 2014

Academic Editor: Marco D. Santambrogio

Copyright © 2014 Tim Todman et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Self-adaptive systems need to monitor themselves, to check their internal behaviour and design assumptions about runtime inputs and conditions. This kind of monitoring for self-adaptive systems can include collecting statistics about such systems themselves which can be computationally intensive (for detailed statistics) and hence time consuming, with possible negative impact on self-adaptive response time. To mitigate this limitation, we extend the technique of in-circuit runtime assertions to cover statistical assertions in hardware. The presented designs implement several statistical operators that can be exploited by self-adaptive systems; a novel optimization is developed for reducing the number of pairwise operators from to . To illustrate the practicability and industrial relevance of our proposed approach, we evaluate our designs, chosen from a class of possible application scenarios, for their resource usage and the tradeoffs between hardware and software implementations.