The Border Gateway Protocol (BGP) is employed by autonomous systems (ASes), such as network operators or ISPs, to build routing tables. However, depending on the routing policies implemented by these ASes, BGP may fail to converge, potentially rendering the network inoperative. This paper introduces a workflow that leverages SMT solvers and rewriting tools to automate the verification of BGP convergence within a given AS network. We encode the convergence conditions defined by the Metarouting theoretical framework as an SMT problem. While SMT solvers can automatically determine whether BGP will converge, they do not generate counterexample traces in cases of divergence. To overcome this shortcoming, we propose a sound divergence criterion. We also construct an executable model for verifying BGP convergence, which can be automated using the Maude rewriting tool to produce witness traces in divergent scenarios. The effectiveness of our approach is demonstrated through a series of experiments.

Abstract Rewriting Modulo SMT combines two powerful automated deduction techniques (1) rewriting and (2) SMT-solving. Rewriting enables the specification of behavior of systems using rewriting rules, while SMT theories specify system properties. Rewriting Modulo SMT is enabled by combining existing tools, such as Maude and SMT solvers. Search algorithms used for carrying out Rewriting Modulo SMT, however, cannot exploit the incremental solving features available in SMT solvers as they are based on breadth-first search. This paper addresses this limitation by proposing Incremental Rewriting Modulo SMT Theories, which is a syntactical restriction to rewriting rules. This restriction turns out to naturally be used in several applications of Rewriting Modulo SMT, including the verification of algorithms, cyber-physical systems, and security protocols. Moreover, we propose a Hybrid-Search algorithm for Incremental Rewriting Modulo SMT Theories that combines breadth-first search and depth-first search, thus enabling incremental SMT-solving. We demonstrate through a collection of existing benchmarks that the Hybrid-Search algorithm can achieve a 10 times performance improvement in verification times.

This paper presents DeCon, a declarative programming language for implementing smart contracts and specifying contract-level properties. Driven by the observation that smart contract operations and contract-level properties can be naturally expressed as relational constraints, DeCon models each smart contract as a set of relational tables that store transaction records. This relational representation of smart contracts enables convenient specification of contract properties, facilitates run-time monitoring of potential property violations, and brings clarity to contract debugging via data provenance. Specifically, a DeCon program consists of a set of declarative rules and violation query rules over the relational representation, describing the smart contract implementation and contract-level properties, respectively. We have developed a tool that can compile DeCon programs into executable Solidity programs, with instrumentation for run-time property monitoring. Our case studies demonstrate that DeCon can implement realistic smart contracts such as ERC20 and ERC721 digital tokens. Our evaluation results reveal the marginal overhead of DeCon compared to the open-source reference implementation, incurring 14% median gas overhead for execution, and another 16% median gas overhead for run-time verification.