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While model checking is a powerful technique to analyze the properties of a model, it can be very expensive or even impossible, if the model comprises many states that have to be explored. Simulation-based model checking is an alternative, where the properties defined in temporal logics are not checked on the model itself but on traces produced during model execution. However, for stochastic models...
The increase and diversity of simulation methods bears witness of the need for more efficient discrete event simulations in computational biology-but how efficient are those methods, and how to ensure an efficient simulation for a concrete model? As the performance of simulation methods depends on the model, the simulator, and the infrastructure, general answers to those questions are likely to remain...
Simulation replication is a necessity for all stochastic simulations. Its efficient execution is particularly important when additional techniques are used on top, such as optimization or sensitivity analysis. One way to improve replication efficiency is to ensure that the best configuration of the simulation system is used for execution. A selection of the best configuration is possible when the...
Model validation is essential in modeling and simulation. It ldquofinalizesrdquo the modeling process, and provides the base for reliable experiments with the model, and thus to gain trustworthy insights of the system under study. Diverse techniques have been developed addressing different needs and are used during different phases in the modeling and simulation life cycle. Experimental model validation...
Compartments play an important role in molecular and cell biology modeling, which motivated the development of BETA-BINDERS, a formalism which is an extension of the pi-CALCULUS. To execute BETA-BINDERS models, sophisticated simulators are required to ensure a sound and efficient execution. Parallel and distributed simulation represents one means to achieve the later. However, stochastically scheduled...
Stochastic simulations may require many replications until their results are statistically significant. Each replication corresponds to a standalone simulation job, so that these can be computed in parallel. This paper presents a grid-inspired approach to distribute such independent jobs over a set of computing resources that host simulation services, all of which are managed by a central master service...
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