On the Synchronization Power of Token Smart Contracts

Alpos, Orestis; Cachin, Christian; Marson, Giorgia Azzurra; Zanolini, Luca (2021). On the Synchronization Power of Token Smart Contracts (arXiv). Cornell University

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Modern blockchains support a variety of distributed applications beyond cryptocurrencies, including smart contracts, which let users execute arbitrary code in a distributed and decentralized fashion. Regardless of their intended application, blockchain platforms implicitly assume consensus for the correct execution of a smart contract, thus requiring that all transactions are totally ordered. It was only recently recognized that consensus is not necessary to prevent double-spending in a cryptocurrency (Guerraoui et al., PODC’19), contrary to common belief. This result suggests that current implementations may be sacrificing efficiency and scalability because they synchronize transactions much more tightly than actually needed. In this work, we study the synchronization requirements of Ethereum’s ERC20 token contract, one of the most widely adopted smart contacts. Namely, we model a smart-contract token as a concurrent object and analyze its consensus number as a measure of synchronization power. We show that the richer set of methods supported by ERC20 tokens, compared to standard cryptocurrencies, results in strictly stronger synchronization requirements. More surprisingly, the synchronization power
of ERC20 tokens depends on the object’s state and can thus be modified by method invocations. To prove this result, we develop a dedicated framework to express how the object’s state affects the needed synchronization level. Our findings indicate that ERC20 tokens, as well as other token standards, are more powerful and versatile than plain cryptocurrencies, and are subject to dynamic requirements. Developing specific synchronization protocols that exploit these dynamic requirements will pave the way towards more robust and scalable blockchain platforms.

Item Type:

Working Paper


08 Faculty of Science > Institute of Computer Science (INF)

UniBE Contributor:

Alpos, Orestis Charilaos, Cachin, Christian, Marson, Giorgia Azzurra, Zanolini, Luca


000 Computer science, knowledge & systems
500 Science > 510 Mathematics




Cornell University




Christian Cachin

Date Deposited:

10 Mar 2021 13:45

Last Modified:

05 Dec 2022 15:48

ArXiv ID:






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