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Evaluation of Resilience in Self-Adaptive Systems Using Probabilistic Model-Checking

Cámara, Javier and de Lemos, Rogério (2012) Evaluation of Resilience in Self-Adaptive Systems Using Probabilistic Model-Checking. In: 2012 7th International Symposium on Software Engineering for Adaptive and Self-Managing Systems (SEAMS). IEEE, pp. 53-62. ISBN 978-1-4673-1788-7. E-ISBN 978-1-4673-1787-0. (doi:10.1109/SEAMS.2012.6224391) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided) (KAR id:31879)

The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided.
Official URL:
http://dx.doi.org/10.1109/SEAMS.2012.6224391

Abstract

The provision of assurances for self-adaptive systems presents its challenges since uncertainties associated with its operating environment often hamper the provision of absolute guarantees that system properties can be satisfied. In this paper, we define an approach for the verification of self-adaptive systems that relies on stimulation and probabilistic model-checking to provide levels of confidence regarding service delivery. In particular, we focus on resilience properties that enable us to assess whether the system is able to maintain trustworthy service delivery in spite of changes in its environment. The feasibility of our proposed approach for the provision of assurances is evaluated in the context of the Znn.com case study.

Item Type: Book section
DOI/Identification number: 10.1109/SEAMS.2012.6224391
Uncontrolled keywords: assurances , evaluation , probabilistic model checking , resilience , self-adaptation , stimulation
Subjects: Q Science > QA Mathematics (inc Computing science) > QA 76 Software, computer programming, > QA76.76 Computer software
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Computing
Depositing User: Rogerio de Lemos
Date Deposited: 23 Oct 2012 23:26 UTC
Last Modified: 16 Nov 2021 10:09 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/31879 (The current URI for this page, for reference purposes)

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