Maha Ayub, Muhammad Waiz Khan, Muhammmad Umar Janjua
{"title":"Sound analysis and migration of data from Ethereum smart contracts","authors":"Maha Ayub, Muhammad Waiz Khan, Muhammmad Umar Janjua","doi":"10.1007/s10515-024-00422-3","DOIUrl":null,"url":null,"abstract":"<div><p>With the addition of multiple blockchain platforms in the ecosystem, the Dapp owners need to migrate their smart contracts from one platform to another to remain competitive, cost-effective, and secure. A smart contract is a piece of code that contains logic and data. To migrate a smart contract, whether it’s on the same blockchain platform or a different one, we need both its source code that represents the logic and data that indicate the state of the contract. The source code can be easily set up, but to complete the migration, we have to extract the current state of the contract. In this paper, we have developed an advanced state extraction technique that uses static analysis to analyze the smart contract’s call graph and events, and extracts the entire storage state from the storage trie, along with the proper associations across function calls, enabling users to visualize, manage, and transform the state as desired for migration. The soundness of the extracted state was confirmed using the method of abstract interpretation. Further, the migration adapter is designed to transform the extracted state into slot-value pairs and migrate it to the target blockchain. Using our new approach, we were able to completely analyze 14% more smart contracts with the extraction of 53% more data by analyzing function calls and event logs from 67,993 contracts and also migrated some contracts to the multiple popular EVM-compatible blockchains.</p></div>","PeriodicalId":55414,"journal":{"name":"Automated Software Engineering","volume":"31 1","pages":""},"PeriodicalIF":2.0000,"publicationDate":"2024-02-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Automated Software Engineering","FirstCategoryId":"94","ListUrlMain":"https://link.springer.com/article/10.1007/s10515-024-00422-3","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, SOFTWARE ENGINEERING","Score":null,"Total":0}
引用次数: 0
Abstract
With the addition of multiple blockchain platforms in the ecosystem, the Dapp owners need to migrate their smart contracts from one platform to another to remain competitive, cost-effective, and secure. A smart contract is a piece of code that contains logic and data. To migrate a smart contract, whether it’s on the same blockchain platform or a different one, we need both its source code that represents the logic and data that indicate the state of the contract. The source code can be easily set up, but to complete the migration, we have to extract the current state of the contract. In this paper, we have developed an advanced state extraction technique that uses static analysis to analyze the smart contract’s call graph and events, and extracts the entire storage state from the storage trie, along with the proper associations across function calls, enabling users to visualize, manage, and transform the state as desired for migration. The soundness of the extracted state was confirmed using the method of abstract interpretation. Further, the migration adapter is designed to transform the extracted state into slot-value pairs and migrate it to the target blockchain. Using our new approach, we were able to completely analyze 14% more smart contracts with the extraction of 53% more data by analyzing function calls and event logs from 67,993 contracts and also migrated some contracts to the multiple popular EVM-compatible blockchains.
期刊介绍:
This journal details research, tutorial papers, survey and accounts of significant industrial experience in the foundations, techniques, tools and applications of automated software engineering technology. This includes the study of techniques for constructing, understanding, adapting, and modeling software artifacts and processes.
Coverage in Automated Software Engineering examines both automatic systems and collaborative systems as well as computational models of human software engineering activities. In addition, it presents knowledge representations and artificial intelligence techniques applicable to automated software engineering, and formal techniques that support or provide theoretical foundations. The journal also includes reviews of books, software, conferences and workshops.