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Intelligence-Driven Optimization of Smart Contracts

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Abstract

In this chapter, we present an overview on how smart contracts could be optimized by intelligence-driven approaches. We empirically study the repetitiveness of smart contracts via cluster analysis and try to extract differentiated codes from the similar contracts. Differentiated codes are defined as the source codes except the repeated ones in two similar smart contracts, usually illustrating how a software feature is implemented or a programming issue is solved. Then, a differentiated code might be used to guide the update of a smart contract in its next version. Finally, we apply syntax and semantic similarities to discover its similar smart contracts from more than 120,000 smart contracts, and recommend the differentiated codes to the target smart contracts.

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Notes

  1. 1.

    https://etherscan.io.

  2. 2.

    A standard interface for tokens. https://eips.ethereum.org/EIPS/eip-20.

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Authors and Affiliations

  1. National Engineering Research Center of Digital Life, School of Data and Computer Science, Sun Yat-sen University, Guangzhou, China

    Yuan Huang & Queping Kong

  2. School of Management Science and Engineering, Hebei GEO University, Shijiazhuang, China

    Nan Jia

  3. Guangdong Key Laboratory for Big Data Analysis and Simulation of Public Opinion, School of Communication and Design, Sun Yat-sen University, Guangzhou, China

    Xiangping Chen

  4. Sun Yat-sen University, Guangzhou, China

    Zibin Zheng

  5. National Engineering Research Center of Digital Life, Sun Yat-sen University, Guangzhou, China

    Zibin Zheng

Authors
  1. Yuan Huang
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  2. Queping Kong
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  3. Nan Jia
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  4. Xiangping Chen
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  5. Zibin Zheng
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Corresponding author

Correspondence to Xiangping Chen .

Editor information

Editors and Affiliations

  1. School of Data and Computer Science, Sun Yat-sen University, Guangzhou, Guangdong, China

    Zibin Zheng

  2. Faculty of Information Technology, Macau University of Science and Technology, Macao, China

    Hong-Ning Dai

  3. School of Data and Computer Science, Sun Yat-sen University, Guangzhou, Guangdong, China

    Jiajing Wu

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Huang, Y., Kong, Q., Jia, N., Chen, X., Zheng, Z. (2021). Intelligence-Driven Optimization of Smart Contracts. In: Zheng, Z., Dai, HN., Wu, J. (eds) Blockchain Intelligence. Springer, Singapore. https://doi.org/10.1007/978-981-16-0127-9_4

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  • DOI: https://doi.org/10.1007/978-981-16-0127-9_4

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