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In today’s competitive business environments, organizations increasingly need to model and deploy flexible and cost effective business processes. In this context, configurable process models are used to offer flexibility by representing process variants in a generic manner. Hence, the behavior of similar variants is grouped in a single model holding configurable elements. Such elements are then customized and configured depending on specific needs. However, the decision to configure an element may be incorrect leading to critical behavioral errors. Recently, process configuration has been extended to include Cloud resources allocation, to meet the need of business scalability by allowing access to on-demand IT resources. In this work, we propose a formal model based on propositional satisfiability formula allowing to find correct elements configuration including resources allocation ones. In addition, we propose to select optimal con- figurations based on Cloud resources cost. This approach allows to provide the designers with correct and cost-effective configuration decisions.

Cloud and Fog computing have been widely recognized as attractive solutions in both academic and industrial sectors. Despite their benefits, the adoption of Cloud and Fog computing still have considerable challenges to be handled due to the increase of client requirements. A crucial issue, in this context, is how to verify the correctness of Cloud and Fog systems. The use of formal methods is an efficient mean which provides a real help for the designer to evaluate the behaviour of a system and prevent errors before its implementation. In this paper, we present a systematic literature review (SLR) on the current state of the art in this field. We collect the existing studies on the use of formal methods for proving the correctness of Cloud and Fog systems. The proposed approaches are compared based on some technical properties such as the verification methods, the verification tools, the considered properties, and the application domains. In addition, future directions which need more investigations are presented. We believe that our paper will be useful for industry and academic researchers to understand the existing contributions that deal with the cor- rectness of Cloud and Fog systems. Moreover, it helps them to address several gaps in the literature.