22 citations · 26 across the 11 of their papers we have counts for
10 papers · 1 filter
Type-Directed Discretization of Probabilistic Programs (Extended Version)
Katherine Wu, Jules Jacobs, Kevin Batz +1
We study exact discretization as a semantics-preserving transformation for recursive, higher-order probabilistic programs with continuous distributions. We target programs where co…
Multiobjective Preexpectation Reasoning for Probabilistic Programs
Lena Verscht, Hannah Mertens, Kevin Batz +3
Probabilistic programs with nondeterminism model planning problems in which a strategy resolves the nondeterminism to optimize an expected outcome. We study the multiobjective sett…
A Fast Quantitative Analyzer for NetKAT
Thomas Lu, Qiancheng Fu, Kevin Batz +5
When designing a network, engineers must navigate trade-offs (e.g., one topology offers more aggregate bandwidth, another lower latency or better resilience) that demand reasoning…
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 Yiğit 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…