Modeling is an efficient and cost-effective way to represent a real-world system. A model can represent key aspects of the system, including the underlying requirements, the components, and how those components communicate with one another. While traditional programming practices have produced a wide range of relatively independent simulation methods, predictive models of extremely complex natural and artificial systems will require a more scalable, more collaborative approach to modeling. This project strives for software that will help researchers develop, debug, document, share, and integrate simulation code.
Computer simulation is the discipline of designing a model of an actual or theoretical physical system, executing the model on a digital computer, and analyzing the execution output. The model can be simulated, enabling designers to test designs before hardware is available, or to test conditions that are either difficult or expensive to replicate in the real world. Iterating between modeling and simulation can improve the quality of the system design early, reducing the number of errors found later in the design process.
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