Inferring Expected Runtimes of Probabilistic Integer Programs Using Expected Sizes

arXiv (Cornell University)

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.

Authors 2

1. Marcel Hark Aachen LuFG Informatik 2

   RWTH Aachen University

   Affiliation as printed

   LuFG Informatik 2 , RWTH Aachen University , Aachen , Germany

2. Jürgen Giesl Aachen LuFG Informatik 2

   RWTH Aachen University

   Affiliation as printed

   LuFG Informatik 2 , RWTH Aachen University , Aachen , Germany