A Fast Quantitative Analyzer for NetKAT

The problem is that network engineers need to reason about quantitative trade-offs like bandwidth, latency, and resilience, which existing tools do not support. The method introduces a fast analyzer using weighted NetKAT (wNetKAT) and a symbolic data structure called weighted symbolic packet programs (wSPPs) to compactly represent and compute quantitative network policies. Experimental evidence shows the Rust implementation is competitive with KATch on Boolean reachability and orders of magnitude faster than McNetKAT and Storm on probabilistic analyses, with a case study on Fat-tree and Jellyfish topologies demonstrating multi-objective design-time analysis. This matters because it provides a practical, parametric framework for fast quantitative reasoning about network properties, enabling engineers to explore design trade-offs at scale.