Checking smart contracts with structural code embedding
Smart contracts have been increasingly used together with blockchains to automate financial and business transactions. However, many bugs and vulnerabilities have been identified in many contracts which raises serious concerns about smart contract security, not to mention that the blockchain systems...
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sg-smu-ink.sis_research-66092022-08-10T01:43:59Z Checking smart contracts with structural code embedding GAO, Zhipeng JIANG, Lingxiao XIA, Xin LO, David GRUNDY, John Smart contracts have been increasingly used together with blockchains to automate financial and business transactions. However, many bugs and vulnerabilities have been identified in many contracts which raises serious concerns about smart contract security, not to mention that the blockchain systems on which the smart contracts are built can be buggy. Thus, there is a significant need to better maintain smart contract code and ensure its high reliability. In this paper, we propose an automated approach to learn characteristics of smart contracts in Solidity, useful for repetitive contract code, bug detection and contract validation. Our new approach is based on word embeddings and vector space comparison. We parse smart contract code into word streams with code structural information, convert code elements (e.g., statements, functions) into numerical vectors that are supposed to encode the code syntax and semantics, and compare the similarities among the vectors encoding code and known bugs, to identify potential issues. We have implemented the approach in a prototype, named SmartEmbed, and evaluated it with more than 22,000 smart contracts collected from the Ethereum blockchain. Results show that our tool can effectively identify many repetitive instances of Solidity code, where the clone ratio is around 90%. Code clones such as type-III or even type-IV semantic clones can also be detected. Our tool can identify more than 500 clone related bugs based on our bug databases efficiently and accurately. Our tool can also help to efficiently validate any given smart contract against the known set of bugs, which can help to improve the users' confidence in the reliability of the contract. 2021-12-01T08:00:00Z text application/pdf https://ink.library.smu.edu.sg/sis_research/5606 info:doi/10.1109/TSE.2020.2971482 https://ink.library.smu.edu.sg/context/sis_research/article/6609/viewcontent/TSE20SmartEmbed.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University smart contract code embedding clone detection bug detection ethereum blockchain Software Engineering |
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smart contract code embedding clone detection bug detection ethereum blockchain Software Engineering GAO, Zhipeng JIANG, Lingxiao XIA, Xin LO, David GRUNDY, John Checking smart contracts with structural code embedding |
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Smart contracts have been increasingly used together with blockchains to automate financial and business transactions. However, many bugs and vulnerabilities have been identified in many contracts which raises serious concerns about smart contract security, not to mention that the blockchain systems on which the smart contracts are built can be buggy. Thus, there is a significant need to better maintain smart contract code and ensure its high reliability. In this paper, we propose an automated approach to learn characteristics of smart contracts in Solidity, useful for repetitive contract code, bug detection and contract validation. Our new approach is based on word embeddings and vector space comparison. We parse smart contract code into word streams with code structural information, convert code elements (e.g., statements, functions) into numerical vectors that are supposed to encode the code syntax and semantics, and compare the similarities among the vectors encoding code and known bugs, to identify potential issues. We have implemented the approach in a prototype, named SmartEmbed, and evaluated it with more than 22,000 smart contracts collected from the Ethereum blockchain. Results show that our tool can effectively identify many repetitive instances of Solidity code, where the clone ratio is around 90%. Code clones such as type-III or even type-IV semantic clones can also be detected. Our tool can identify more than 500 clone related bugs based on our bug databases efficiently and accurately. Our tool can also help to efficiently validate any given smart contract against the known set of bugs, which can help to improve the users' confidence in the reliability of the contract. |
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GAO, Zhipeng JIANG, Lingxiao XIA, Xin LO, David GRUNDY, John |
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GAO, Zhipeng JIANG, Lingxiao XIA, Xin LO, David GRUNDY, John |
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GAO, Zhipeng |
title |
Checking smart contracts with structural code embedding |
title_short |
Checking smart contracts with structural code embedding |
title_full |
Checking smart contracts with structural code embedding |
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Checking smart contracts with structural code embedding |
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Checking smart contracts with structural code embedding |
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checking smart contracts with structural code embedding |
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Institutional Knowledge at Singapore Management University |
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2021 |
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https://ink.library.smu.edu.sg/sis_research/5606 https://ink.library.smu.edu.sg/context/sis_research/article/6609/viewcontent/TSE20SmartEmbed.pdf |
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