DISL: Fueling Research with A Large Dataset of Solidity Smart Contracts
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Abstract (arXiv)
The DISL dataset features a collection of 514,506 unique Solidity files that have been deployed to Ethereum mainnet. It caters to the need for a large and diverse dataset of real-world smart contracts. DISL serves as a resource for developing machine learning systems and for benchmarking software engineering tools designed for smart contracts. By aggregating every verified smart contract from Etherscan up to January 15, 2024, DISL surpasses existing datasets in size and recency.
Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 11 of its 23 references that are in the map. First posted on arXiv 25 Mar 2024.
Builds on
11 of 23 references.
References · 11
- 2018The Adverse Effects of Code Duplication in Machine Learning Models of Codecited by 126
- 2019Slither: A Static Analysis Framework For Smart Contractscited by 89
- 2019Empirical Review of Automated Analysis Tools on 47,587 Ethereum Smart Contractscited by 36
- 2023Do you still need a manual smart contract audit?cited by 35
- 2020How Effective are Smart Contract Analysis Tools? Evaluating Smart Contract Static Analysis Tools Using Bug Injectioncited by 20
- 2023Efficient Avoidance of Vulnerabilities in Auto-completed Smart Contract Code Using Vulnerability-constrained Decodingcited by 14
- 2023DAppSCAN: Building Large-Scale Datasets for Smart Contract Weaknesses in DApp Projectscited by 9
- 2023Smart Contract and DeFi Security Tools: Do They Meet the Needs of Practitioners?cited by 8
- 2023Automated Summarization of Stack Overflow Postscited by 5
- 2021sGUARD: Towards Fixing Vulnerable Smart Contracts Automaticallycited by 3
- 2023Too Few Bug Reports? Exploring Data Augmentation for Improved Changeset-based Bug Localizationcited by 2
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Citing papers per year: 2025: 1.
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