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Verifying Probabilistic Procedural Programs

Authors: Javier Esparza; Kousha Etessami;

Verifying Probabilistic Procedural Programs

Abstract

Monolithic finite-state probabilistic programs have been abstractly modeled by finite Markov chains, and the algorithmic verification problems for them have been investigated very extensively. In this paper we survey recent work conducted by the authors together with colleagues on he algorithmic verification of probabilistic procedural programs ([BKS,EKM04,EY04]). Probabilistic procedural programs can more naturally be modeled by recursive Markov chains ([EY04)], or equivalently, probabilistic pushdown automata ([EKM04)]. A very rich theory emerges for these models. While our recent work solves a number of verification problems for these models, many intriguing questions remain open.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
11
Average
Top 10%
Top 10%
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