Abstract
In recent years, we have observed the increasing interest in the system property resilience. We ascribe this increasing interest to the rapidly growing number of deployed, complex, socio-technical systems, which are facing uncertainty about changes they are expected to experience during their life-cycle and ways to deal with them. This paper contributes to current resilience research by focusing on the different definitions given for this system property, highlighting the risk that, using different terms in different communities, this contributes to create a “tower of Babel” problem, with the consequent difficulty in exchanging ideas and working together towards a common goal. We adopt an extended definition of dependability to define resilience. Based on that, we identify features of resilient systems, capture properties falling under the resilience umbrella, and define a conceptual framework for resilience characterization including how changes affect the system, strategies to design resilience, and discuss metrics for quantifying resilience at design and runtime.
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Notes
- 1.
If the system dynamics is described by means of some stochastic model, \(\mu (T)\) is a random variable, whose moments or probability distribution can be used as actual resilience metrics.
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Raffaela Mirandola has been partially supported by the Swedish KK-Stiftelsens project No. KKS - 20170232.
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Andersson, J., Grassi, V., Mirandola, R., Perez-Palacin, D. (2019). A Distilled Characterization of Resilience and Its Embraced Properties Based on State-Spaces. In: Calinescu, R., Di Giandomenico, F. (eds) Software Engineering for Resilient Systems. SERENE 2019. Lecture Notes in Computer Science(), vol 11732. Springer, Cham. https://doi.org/10.1007/978-3-030-30856-8_2
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