Abstract interpretation of programs as Markov decision processes
type: Dataset
description: We propose a formal language for the specification of trace properties of probabilistic, nondeterministic transition systems, encompassing the properties expressible in Linear Time Logic. Those formulas are in general undecidable on infinite deterministic transition systems and thus on infinite Markov decision processes. This language has both a semantics in terms of sets of traces, as well as another semantics in terms of measurable functions; we give and prove theorems linking the two semantics. We then apply abstract interpretation-based techniques to give upper bounds on the worst-case probability of the studied property. We propose an enhancement of this technique when the state space is partitioned — for instance along the program points — allowing the use of faster iteration methods.
landing page: 0167-6423
keyword: abstract-interpretation
keyword: infoeu-reposemanticsarticle
keyword: infoinfo-plcomputer-science-csprogramming-languages-cspl
keyword: journal-articles
keyword: mathmath-prmathematics-mathprobability-mathpr
keyword: nondeterminism
keyword: probabilities
keyword: program-semantics
issued: 2026-05-10T10:02:38.502986
modified: 2026-05-10T10:02:38.502991
language: en
contact point: Organization
  fn: CCSD

test_moissonnage_selune
type: Agent

Abstract interpretation of programs as Markov decision processes
type: Distribution
format: HTML
access URL: https://hal.science/hal-00084297
issued: 2026-05-10T10:02:38.516234
modified: 2026-05-10T10:02:38.493997