Kirigami, the Verifiable Art of Network Cutting

02/12/2022
by   Tim Alberdingk Thijm, et al.
0

We introduce a modular verification approach to network control plane verification, where we cut a network into smaller fragments to improve the scalability of SMT solving. Users provide an annotated cut which describes how to generate these fragments from the monolithic network, and we verify each fragment independently, using the annotations to define assumptions and guarantees over fragments akin to assume-guarantee reasoning. We prove this modular network verification procedure is sound and complete with respect to verification over the monolithic network. We implement this procedure as Kirigami, an extension of NV - a network verification language and tool - and evaluate it on industrial topologies with synthesized policies. We observe a 2-8x improvement in end-to-end NV verification time, with SMT solve time improving by up to 6 orders of magnitude.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
04/21/2022

Modular Control Plane Verification via Temporal Invariants

Satisfiability Modulo Theory (SMT)-based tools for network control plane...
research
06/05/2022

ACORN: Network Control Plane Abstraction using Route Nondeterminism

Networks are hard to configure correctly, and misconfigurations occur fr...
research
04/20/2022

LIGHTYEAR: Using Modularity to Scale BGP Control Plane Verification

Current network control plane verification tools cannot scale to large n...
research
04/16/2020

Solving bitvectors with MCSAT: explanations from bits and pieces (long version)

We present a decision procedure for the theory of fixed-sized bitvectors...
research
06/01/2019

Formal Modeling and SMT-Based Parameterized Verification of Data-Aware BPMN

We propose DAB -- a data-aware extension of BPMN where the process opera...
research
05/26/2020

Deepzzle: Solving Visual Jigsaw Puzzles with Deep Learning andShortest Path Optimization

We tackle the image reassembly problem with wide space between the fragm...
research
02/10/2023

Incremental Satisfiability Modulo Theory for Verification of Deep Neural Networks

Constraint solving is an elementary way for verification of deep neural ...

Please sign up or login with your details

Forgot password? Click here to reset