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6 - Expected Runtime Analyis by Program Verification

Published online by Cambridge University Press:  18 November 2020

Gilles Barthe
Affiliation:
Max Planck Institute for Security and Privacy
Joost-Pieter Katoen
Affiliation:
RWTH Aachen University, Germany
Alexandra Silva
Affiliation:
University College London
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Summary

This chapter is concerned with analysing the expected runtime of probabilistic programs by exploiting program verification techniques. We introduce a weakest pre-conditioning framework á la Dijkstra that enables to determine the expected runtime in a compositional manner. Like weakest pre-conditions, it is a reasoning framework at the syntax level of programs. Applications of the weakest pre-conditioning framework include determining the expected runtime of randomised algorithms, as well as determining whether a program is positive almost-surely terminating, i.e., whether the expected number of computation steps until termination is finite for every possible input. For Bayesian networks, a restricted class of probabilistic programs, we show that the expected runtime analysis can be fully automated. In this way, the simulation time under rejection sampling can be determined. This is particularly useful for ill-conditioned inference queries.

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Publisher: Cambridge University Press
Print publication year: 2020
Creative Commons
Creative Common License - CCCreative Common License - BY
This content is Open Access and distributed under the terms of the Creative Commons Attribution licence CC-BY 4.0 https://creativecommons.org/cclicenses/

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