Dubois, DJDJDuboisTrubiani, CCTrubianiCasale, GGCasale2016-05-122017-01-192017-01-199th IEEE International Conference on Cloud Computing, 20172159-6190http://hdl.handle.net/10044/1/32496Performance assessment of cloud-based applications requires new methodologies to deal with the complexity of software systems and the variability of cloud resources. In this paper, we address the problem of reducing the total costs for running cloud-based applications while fulfilling servicelevel objectives (SLOs). To this end, we define an approach to refactor a cloud application in such a way that, when it is deployed, it requires less computational capacity and therefore less resources. We experimented our approach on top of a modified optimal provisioning heuristic designed for preemptible cloud resources and the results show that it reduces deployment costs, up to 60% when compared to the same approach, but without model-driven application refactoring.© 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Science & TechnologyTechnologyComputer Science, Hardware & ArchitectureComputer Science, Information SystemsComputer Sciencesoftware performance engineeringcloud computingapplication refactoringresource provisioningSPOT INSTANCESConference Paperhttps://www.dx.doi.org/10.1109/CLOUD.2016.0052PIEF-GA-2013-629982644869