From the 1 of 12 linked papers with an AI index.
5 papers · 1 filter
A Fast Quantitative Analyzer for NetKAT
Thomas Lu, Qiancheng Fu, Kevin Batz +5
The paper introduces a fast analyzer for quantitative network properties using weighted NetKAT, employing a symbolic data structure and specialized algorithms to efficiently comput…
Scalable Probabilistic Program Verification via Typed Extended Decision Diagrams
Daniel Basgöze, Kevin Batz, Sebastian Junges +1
Weakest pre-expectations are the probabilistic program analogue to weakest preconditions in classical programs. Deductive verification approaches aim to establish bounds on these q…
Caesar: A Deductive Verifier for Probabilistic Programs
Philipp Schröer, Kevin Batz, Umut YiÄit Dural +4
Caesar is a deductive verifier for probabilistic programs. At its core lies HeyVL, a quantitative intermediate verification language based on the real-valued logic HeyLo. HeyVL all…
Weighted NetKAT: A Programming Language For Quantitative Network Verification
Emmanuel Suárez Acevedo, Tiago Ferreira, Kevin Batz +3
We introduce weighted NetKAT, a domain-specific language for modeling and verifying quantitative network properties. The language is parametric on a semiring, enabling the treatmen…
Generating Functions Meet Occupation Measures: Invariant Synthesis for Probabilistic Loops (Extended Version)
Darion Haase, Kevin Batz, Adrian Gallus +4
A fundamental computational task in probabilistic programming is to infer a program's output (posterior) distribution from a given initial (prior) distribution. This problem is cha…