Inferring Expected Runtimes of Probabilistic Integer Programs Using Expected Sizes
Fabian Meyer, Marcel Hark, Jürgen Giesl · Lecture notes in computer science · 2021
Abstract We present a novel modular approach to infer upper bounds on the expected runtimes of probabilistic integer programs automatically. To this end, it computes bounds on the runtimes 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 .