Abstract
‘Semantics and Efficient Simulation Algorithms on an Expressive Multi-Level Modeling Language,” by Helms et al. presents new work on the domain-specific modelling and simulation language ML-Rules [Maus et al. 2011]. For the first time, the language is given a formal semantics that establishes the relationship between the language and its underlying mathematical model, continuous time Markov chains. Furthermore, subclasses of the language are identified for which it is possible to specify and implement more efficient approaches to simulation. These new algorithms are demonstrated on substantial case studies. This replicated computation report focuses on the ML-Rules modelling tool, specifically, the new algorithms as demonstrated in the case studies in the paper [Helms et al. 2017]. The software was straightforward to install and use, and all experimental results from the paper could be reproduced.
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