Local abstraction refinement for probabilistic timed programs
Research output: Contribution to journal › Article › peer-review
Colleges, School and Institutes
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.
|Journal||Theoretical Computer Science|
|Early online date||1 Aug 2013|
|Publication status||Published - 12 Jun 2014|
- Probabilistic verification, Abstraction refinement