Expected-Cost Analysis for Probabilistic Programs and Semantics-Level Adaption of Optional Stopping Theorems
Programming Languages
2021-03-31 v1
Abstract
In this article, we present a semantics-level adaption of the Optional Stopping Theorem, sketch an expected-cost analysis as its application, and survey different variants of the Optional Stopping Theorem that have been used in static analysis of probabilistic programs.
Keywords
Cite
@article{arxiv.2103.16105,
title = {Expected-Cost Analysis for Probabilistic Programs and Semantics-Level Adaption of Optional Stopping Theorems},
author = {Di Wang and Jan Hoffmann and Thomas Reps},
journal= {arXiv preprint arXiv:2103.16105},
year = {2021}
}
Comments
arXiv admin note: substantial text overlap with arXiv:2001.10150