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Inferring Expected Runtimes of Probabilistic Integer Programs Using Expected Sizes (2010.06367v3)
Published 13 Oct 2020 in cs.LO
Abstract: We present a novel modular approach to infer upper bounds on the expected runtime of probabilistic integer programs automatically. To this end, it computes bounds on the runtime of program parts and on the sizes of their variables in an alternating way. To evaluate its power, we implemented our approach in a new version of our open-source tool KoAT.