Networks employ complex, and hence error-prone, routing control plane configurations. In many cases, the impact of errors manifests only under failures and leads to devastating effects. Thus, it is important to proactively verify control plane behavior under arbitrary link failures. State-of-the-art verifiers are either too slow or impractical to use for such verification tasks. In this paper we propose a new high level abstraction for control planes, ARC, that supports fast control plane analyses under arbitrary failures. ARC can check key invariants without generating the data plane\u2014which is the main reason for current tools\u2019 ineffectiveness. This is possible because of the nature of verification tasks and the constrained nature of control plane designs in networks today. We develop algorithms to derive a network\u2019s ARC from its configuration files. Our evaluation over 314 networks shows that ARC computation is quick, and that ARC can verify key invariants in under 1s in most cases, which is orders-of-magnitude faster than the state-of-the-art.<\/p>\n","protected":false},"excerpt":{"rendered":"
Networks employ complex, and hence error-prone, routing control plane configurations. In many cases, the impact of errors manifests only under failures and leads to devastating effects. Thus, it is important to proactively verify control plane behavior under arbitrary link failures. State-of-the-art verifiers are either too slow or impractical to use for such verification tasks. 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