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Inferring Expected Runtimes of Probabilistic Integer Programs Using Expected Sizes

Lecture notes in computer science, pp. 250–269

Abstract

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 .

Authors 3

  1. RWTH Aachen University

    Affiliation as printed

    LuFG Informatik 2, RWTH Aachen University, Aachen, Germany

  2. Marcel Hark corresponding Aachen LuFG Informatik 2

    RWTH Aachen University

    Affiliation as printed

    LuFG Informatik 2, RWTH Aachen University, Aachen, Germany

  3. Jürgen Giesl corresponding Aachen LuFG Informatik 2

    RWTH Aachen University

    Affiliation as printed

    LuFG Informatik 2, RWTH Aachen University, Aachen, Germany

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References 71