2020/08/12 by Andrea Di Sorbo, Sonia Laudanna, Di Sorbo, Andrea +7 · 2 citations
Computer Science · Engineering · #Blockchain Technology Applications and Security #Computation and Language (cs.CL) #Cryptography and Security (cs.CR) #FOS: Computer and information sciences #Green IT and Sustainability #Mobile Crowdsensing and Crowdsourcing #Software Engineering (cs.SE)
paper · pdf · doi:10.48550/arxiv.2008.05449
openalex publication_date 2020/08/12 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Nowadays, more and more applications are developed for running on a distributed ledger technology, namely dApps. The business logic of dApps is usually implemented within smart contracts developed through Solidity, a programming language for writing smart contracts on different blockchain platforms, including the popular Ethereum. In Ethereum, the smart contracts run on the machines of miners and the gas corresponds to the execution fee compensating such computing resources. However, the deployment and execution costs of a smart contract depend on the implementation choices done by developers. Unappropriated design choices could lead to higher gas consumption than necessary. In this paper, we (i) identify a set of 19 Solidity code smells affecting the deployment and transaction costs of a smart contract, and (ii) assess the relevance of such smells through a survey involving 34 participants. On top of these smells, we propose GasMet, a suite of metrics for statically evaluating the code quality of a smart contract from the gas consumption perspective. An experiment involving 2,186 smart contracts demonstrates that the proposed metrics have direct associations with deployment costs. The metrics in our suite can be used for more easily identifying source code segments that need optimizations.