Formal Models and Analysis for Self-adaptive Cyber-physical Systems

Giese, Holger

doi:10.1007/978-3-319-57666-4_1

Cited by 3 publications

(2 citation statements)

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“…They validate their approach using formal specified MAPE-K templates that encode design expertise for a family of selfadaptive systems. Authors of Giese (2016) also present formal models and analysis for self-adaptive cyber-physical systems. They analyze the challenges face self-adaptive cyber-physical systems and outline their results through a generic approach based on extensions of graph transformations systems called SMARTOS.…”

Section: Formal Methods For Complex Adaptive Systemsmentioning

confidence: 99%

“…In many works, researchers tried to apply formal methods to verify the correctness of complex systems where they applied different concepts such as the process algebra CSP (Bartels and Kleine 2011), SOTA (Abeywickrama and Zambonelli 2012), MAPE-K (Iglesia and Weyns 2015), SMARTOS (Giese 2016), and LTL (Sadraddini and Belta 2017). In these works, researchers proved that the application of formal methods highly improve the security and correctness of complex systems.…”

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confidence: 99%

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Formal approach to model complex adaptive computing systems

Jarrar¹,

Wakrime

Balouki³

2020

Complex Adapt Syst Model

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Complex adaptive systems provide a significant number of concepts such as reaction, interaction, adaptation, and evolution. In general, these concepts are modelled employing different techniques which give an inexplicit vision on the system. Therefore, all concepts must be carefully modelled using the same approach to avoid contradiction and guarantee system homogeneity and correctness. However, developing a computing system that includes all these concepts using the same approach is not an easy task and requires a perfect understanding of the system’s behaviour. In this paper, we contribute as stepwise towards proposing an approach to model the most important concepts of complex adaptive systems while ensuring homogeneity and the correctness of models. For this aim, we present five standard agent-based models formalizing agent properties, reaction, interaction, adaptation, and evolution. These models are adapted to all cases of complex adaptive systems since they include an abstract description of these concepts. To implement our approach formally, we choose the Event-B method due to the strong assurance of bugs’ absence that it guarantees. Besides, it supports horizontal and vertical refinement which facilitates the specification process. Furthermore, the approach of this paper addresses the very abstract level of modelling which expand the use of this approach to other formal methods and tools.

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Section: Formal Methods For Complex Adaptive Systemsmentioning

confidence: 99%

mentioning

confidence: 99%