Biblio
We present the first formal verification of state machine safety for the Raft consensus protocol, a critical component of many distributed systems. We connected our proof to previous work to establish an end-to-end guarantee that our implementation provides linearizable state machine replication. This proof required iteratively discovering and proving 90 system invariants. Our verified implementation is extracted to OCaml and runs on real networks. The primary challenge we faced during the verification process was proof maintenance, since proving one invariant often required strengthening and updating other parts of our proof. To address this challenge, we propose a methodology of planning for change during verification. Our methodology adapts classical information hiding techniques to the context of proof assistants, factors out common invariant-strengthening patterns into custom induction principles, proves higher-order lemmas that show any property proved about a particular component implies analogous properties about related components, and makes proofs robust to change using structural tactics. We also discuss how our methodology may be applied to systems verification more broadly.
Internet Service Providers (ISPs) use the Border Gateway Protocol (BGP) to announce and exchange routes for de- livering packets through the internet. ISPs must carefully configure their BGP routers to ensure traffic is routed reli- ably and securely. Correctly configuring BGP routers has proven challenging in practice, and misconfiguration has led to worldwide outages and traffic hijacks. This paper presents Bagpipe, a system that enables ISPs to declaratively express BGP policies and that automatically verifies that router configurations implement such policies. The novel initial network reduction soundly reduces policy verification to a search for counterexamples in a finite space. An SMT-based symbolic execution engine performs this search efficiently. Bagpipe reduces the size of its search space using predicate abstraction and parallelizes its search using symbolic variable hoisting. Bagpipe's policy specification language is expressive: we expressed policies inferred from real AS configurations, policies from the literature, and policies for 10 Juniper TechLibrary configuration scenarios. Bagpipe is efficient: we ran it on three ASes with a total of over 240,000 lines of Cisco and Juniper BGP configuration. Bagpipe is effective: it revealed 19 policy violations without issuing any false positives.