An Abstract Monte-Carlo Method for the Analysis of Probabilistic Programs

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dc.creatorMonniaux, David
dc.date2007-01-30
dc.date.accessioned2026-07-07T07:43:50Z
dc.date.available2026-07-07T07:43:50Z
dc.descriptionWe introduce a new method, combination of random testing and abstract interpretation, for the analysis of programs featuring both probabilistic and non-probabilistic nondeterminism. After introducing "ordinary" testing, we show how to combine testing and abstract interpretation and give formulas linking the precision of the results to the number of iterations. We then discuss complexity and optimization issues and end with some experimental results.
dc.identifierhttps://arxiv.org/abs/cs/0701195
dc.identifierhttp://arxiv.org/abs/cs/0701195
dc.identifierPOPL: Annual Symposium on Principles of Programming Languages (2001) 93 - 101
dc.identifierdoi:10.1145/360204.360211
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/122982
dc.subjectProgramming Languages
dc.subjectPerformance
dc.titleAn Abstract Monte-Carlo Method for the Analysis of Probabilistic Programs
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