Local abstraction refinement for probabilistic timed programs

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• 作者：Klaus Drä ; ger^a ; ^{klaus.draeger@cs.ox.ac.uk" class="auth_mail} ; Marta Kwiatkowska^a ; David Parker^b ; Hongyang Qu^a
• 关键词：Probabilistic verification ; Abstraction refinement
• 刊名：Theoretical Computer Science
• 出版年：12 June 2014
• 年：2014
• 卷：538
• 期：Complete
• 页码：37-53
• 全文大小：579 K

文摘

We consider models of programs that incorporate probability, dense real-time and data. We present a new abstraction refinement method for computing minimum and maximum reachability probabilities for such models. Our approach uses strictly local refinement steps to reduce both the size of abstractions generated and the complexity of operations needed, in comparison to previous approaches of this kind. We implement the techniques and evaluate them on a selection of large case studies, including some infinite-state probabilistic real-time models, demonstrating improvements over existing tools in several cases.