Weighted NetKAT: A Programming Language For Quantitative Network Verification
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Abstract (arXiv)
We introduce weighted NetKAT, a domain-specific language for modeling and verifying quantitative network properties. The language is parametric on a semiring, enabling the treatment of a wide range of quantities in a uniform way. We provide a denotational semantics and an equivalent operational semantics, the latter based on a novel model of weighted NetKAT automata (WNKA) capturing the stateful behavior of our language. With WNKA, we obtain a class of generic decision procedures for reasoning about quantitative safety and reachability in a fully automatic way, even in the presence of possibly unbounded iteration. We demonstrate the applicability of our framework in a case study using Internet2's Abilene network as the underlying topology.
Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). First posted on arXiv 15 Apr 2026.
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- 2026SMT-Based Active Learning of Weighted Automatacited by 0
- 2026SMT-Based Active Learning of Weighted Automata8 May 2026