Accurate Smart Contract Verification Through Direct Modelling

Marescotti, Matteo; Otoni, Rodrigo; Alt, Leonardo; Eugster, Patrick; Hyvärinen, Antti E. J.; Sharygina, Natasha

doi:10.1007/978-3-030-61467-6_12

Cited by 19 publications

(11 citation statements)

References 25 publications

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“…Proving correctness and finding bugs in smart contracts is useful in different abstraction targets. The technical details of how smart contracts are encoded by SolCMC are presented in [34]. In this tool paper the emphasis is on orthogonal topics: the usage of options, generation of counterexamples in Solidity-like syntax, interfacing with different Horn solvers, and how contract invariants can be obtained.…”

Section: Related Workmentioning

confidence: 99%

“…SolCMC encodes a smart contract as a system of constrained Horn clauses, based on [34]. The checker supports loops, multi-transaction computation paths, contract invariants, tracking contract balances throughout their lifetimes, and precise multi-contract calls.…”

Section: The Chc Verification Enginementioning

confidence: 99%

“…SolCMC's CHC encoding is based on the imperative encoding of [25], and is presented in detail in [34]. Horn logic is a popular formalism for expressing reachability problems.…”

Section: Horn Encodingmentioning

confidence: 99%

“…Since 2019, this compiler ships with a robust, builtin, easy-to-use, symbolic model checker SolCMC [16], formerly called SMTChecker. SolCMC models a smart contract, that is, a program for the Ethereum platform, and its properties as a system of constrained Horn clauses (CHCs) amenable to IC3-style model checking [34]. Since its deployment, SolCMC has increasingly served a dual purpose.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

SolCMC: Solidity Compiler’s Model Checker

Alt¹,

Blicha

Hyvärinen

et al. 2022

Lecture Notes in Computer Science

Self Cite

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Formally verifying smart contracts is important due to their immutable nature, usual open source licenses, and high financial incentives for exploits. Since 2019 the Ethereum Foundation’s Solidity compiler ships with a model checker. The checker, called SolCMC, has two different reasoning engines and tracks closely the development of the Solidity language. We describe SolCMC’s architecture and use from the perspective of developers of both smart contracts and tools for software verification, and show how to analyze nontrivial properties of real life contracts in a fully automated manner.

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Section: Related Workmentioning

confidence: 99%

Section: The Chc Verification Enginementioning

confidence: 99%

“…SolCMC's CHC encoding is based on the imperative encoding of [25], and is presented in detail in [34]. Horn logic is a popular formalism for expressing reachability problems.…”

Section: Horn Encodingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

SolCMC: Solidity Compiler’s Model Checker

Alt¹,

Blicha

Hyvärinen

et al. 2022

Lecture Notes in Computer Science

Self Cite

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show abstract

“…The latter are most related to SmartACE since their focus is on functional correctness, as opposed to generic rules (e.g., the absence of reentrancy [15] and integer overflows). Existing techniques for functional correctness are either deductive, and require that most invariants be provided manually (i.e., [18,42]), or are automated but neglect the parameterized nature of smart contracts (i.e., [29,30,35,39]). The tools that do acknowledge parameterization employ static analysis [26,6].…”

Section: Related Workmentioning

confidence: 99%

Compositional Verification of Smart Contracts Through Communication Abstraction (Extended)

Wesley¹,

Christakis²,

Navas³

et al. 2021

Preprint

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Solidity smart contracts are programs that manage up to 2 160 users on a blockchain. Verifying a smart contract relative to all users is intractable due to state explosion. Existing solutions either restrict the number of users to under-approximate behaviour, or rely on manual proofs. In this paper, we present local bundles that reduce contracts with arbitrarily many users to sequential programs with a few representative users. Each representative user abstracts concrete users that are locally symmetric to each other relative to the contract and the property. Our abstraction is semi-automated. The representatives depend on communication patterns, and are computed via static analysis. A summary for the behaviour of each representative is provided manually, but a default summary is often sufficient. Once obtained, a local bundle is amenable to sequential static analysis. We show that local bundles are relatively complete for parameterized safety verification, under moderate assumptions. We implement local bundle abstraction in SmartACE, and show order-of-magnitude speedups compared to a state-of-the-art verifier.

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