TOWARD A MODEL-DRIVEN ENGINEERING FRAMEWORK FOR REPRODUCIBLE SIMULATION EXPERIMENT LIFECYCLE MANAGEMENT

2014-12-10
Teran-Somohano, Alejandro
Dayibas, Orcun
Yılmaz, Levent
Smith, Alice
Goal-directed reproducible experimentation with simulation models is still a significant challenge. The underutilization of design of experiments, limited transparency in the collection and analysis of results, and ad-hoc adaptation of experiments as learning takes place continue to hamper reproducibility and hence cause a credibility gap. In this study, we propose a strategy that leverages the synergies between model-driven engineering, intelligent agent technology, and variability modeling to support the management of the lifecycle of a simulation experiment. Experiment design and workflow models are introduced for configurable experiment synthesis and execution. Feature-based variability modeling is used to design a family of experiments, which can be leveraged by ontology-driven software agents to configure, execute, and reproduce experiments. Online experiment adaptation is proposed as a strategy to facilitate dynamic experiment model updating as objectives shift from validation to variable screening, understanding, and optimization.

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Citation Formats
A. Teran-Somohano, O. Dayibas, L. Yılmaz, and A. Smith, “TOWARD A MODEL-DRIVEN ENGINEERING FRAMEWORK FOR REPRODUCIBLE SIMULATION EXPERIMENT LIFECYCLE MANAGEMENT,” 2014, p. 2726, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/62879.