Abstract
Feature modeling is a widely accepted variability modeling technique for supporting decision-making scenarios, by representing decisions as features. However, there are scenarios where domain concepts have multiple implementation alternatives that have to be analyzed from large-scale data sources. Therefore, a manual selection of an optimal solution from within the alternatives space or even the complete representation of the domain is an unsuitable task. To solve this issue, we created a feature modeling metamodel and two specific processes to represent domain and implementation alternative models, and to search for optimal solutions whilst considering a set of optimization objectives. We applied this approach to a cloud computing case study and obtained an optimal provider configuration for deploying a JEE application.
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Notes
- 1.
These models can be found at https://github.com/CoCoResearch/FSGCLoud.
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Ochoa, L., González-Rojas, O., Verano, M., Castro, H. (2016). Searching for Optimal Configurations Within Large-Scale Models: A Cloud Computing Domain. In: Link, S., Trujillo, J. (eds) Advances in Conceptual Modeling. ER 2016. Lecture Notes in Computer Science(), vol 9975. Springer, Cham. https://doi.org/10.1007/978-3-319-47717-6_6
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DOI: https://doi.org/10.1007/978-3-319-47717-6_6
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