Probabilistic Abstract Interpretation
- Cite this paper as:
- Cousot P., Monerau M. (2012) Probabilistic Abstract Interpretation. In: Seidl H. (eds) Programming Languages and Systems. ESOP 2012. Lecture Notes in Computer Science, vol 7211. Springer, Berlin, Heidelberg
Abstract interpretation has been widely used for verifying properties of computer systems. Here, we present a way to extend this framework to the case of probabilistic systems.
The probabilistic abstraction framework that we propose allows us to systematically lift any classical analysis or verification method to the probabilistic setting by separating in the program semantics the probabilistic behavior from the (non-)deterministic behavior. This separation provides new insights for designing novel probabilistic static analyses and verification methods.
We define the concrete probabilistic semantics and propose different ways to abstract them. We provide examples illustrating the expressiveness and effectiveness of our approach.