Background material: probability, conditional probability, Markov models, Queue modelling of OS, e.g. multi-tasking, proof (and uses) of Little¿s law. Workload modelling: exponential versus Pareto; call centre analysis. Simulation-how to generate random numbers from arbitrary distributions, steady state versus terminating; output analysis; some simple simulation applications. Reliability theory: oriented towards electronic systems, though e.g. passive component failure, and then to microprocessor (embedded software) systems through s/w failures Network Science: introduction to the fundamental ideas in network science: graph theory, network metrics, network models, network robustness. Approach to modelling emergence and topological robustness of supply networks, communication networks and general human-technology interaction.

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