SCStudio: a secure and efficient integrated development environment for smart contracts

Meng Ren, Fuchen Ma, Zijing Yin, Huizhong Li, Ying Fu, Ting Chen, Yu Jiang
{"title":"SCStudio: a secure and efficient integrated development environment for smart contracts","authors":"Meng Ren, Fuchen Ma, Zijing Yin, Huizhong Li, Ying Fu, Ting Chen, Yu Jiang","doi":"10.1145/3460319.3469078","DOIUrl":null,"url":null,"abstract":"With the increasing popularity of block-chain technologies, more and more engineers use smart contracts for application implementation. Traditional supporting tools can either provide code completions based on static libraries or detect a limited set of vulnerabilities, which results in the manpower waste during coding and miss-detection of bugs. In this work, we propose SCStudio, a unified smart contract development platform, which aims to help developers implement more secure smart contracts easily. The core idea is to realize real-time security-reinforced recommendation through pattern-based learning; and to perform security-oriented validation via integrated testing. SCStudio was implemented as a plug-in of VS Code. It has been used as the official development tool of WeBank and integrated as the recommended development tool by FISCO-BCOS community. In practice, it outperforms existing contract development environments, such as Remix, improving the average word suggestion accuracy by 30%-60% and helping detect about 25% more vulnerabilities. The video is presented at https://youtu.be/l6hW3Ds5Tkg.","PeriodicalId":188008,"journal":{"name":"Proceedings of the 30th ACM SIGSOFT International Symposium on Software Testing and Analysis","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 30th ACM SIGSOFT International Symposium on Software Testing and Analysis","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3460319.3469078","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 7

Abstract

With the increasing popularity of block-chain technologies, more and more engineers use smart contracts for application implementation. Traditional supporting tools can either provide code completions based on static libraries or detect a limited set of vulnerabilities, which results in the manpower waste during coding and miss-detection of bugs. In this work, we propose SCStudio, a unified smart contract development platform, which aims to help developers implement more secure smart contracts easily. The core idea is to realize real-time security-reinforced recommendation through pattern-based learning; and to perform security-oriented validation via integrated testing. SCStudio was implemented as a plug-in of VS Code. It has been used as the official development tool of WeBank and integrated as the recommended development tool by FISCO-BCOS community. In practice, it outperforms existing contract development environments, such as Remix, improving the average word suggestion accuracy by 30%-60% and helping detect about 25% more vulnerabilities. The video is presented at https://youtu.be/l6hW3Ds5Tkg.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
SCStudio:一个安全高效的智能合约集成开发环境
随着区块链技术的日益普及,越来越多的工程师使用智能合约来实现应用。传统的支持工具要么提供基于静态库的代码补全,要么检测有限的漏洞集,这导致了编码过程中的人力浪费和错误检测的缺失。在这项工作中,我们提出了SCStudio,这是一个统一的智能合约开发平台,旨在帮助开发人员轻松实现更安全的智能合约。其核心思想是通过基于模式的学习实现实时的安全增强推荐;并通过集成测试执行面向安全的验证。SCStudio是作为VS Code的插件实现的。作为微众银行官方开发工具,被FISCO-BCOS社区整合为推荐开发工具。在实践中,它优于现有的合约开发环境,如Remix,将平均单词建议准确率提高了30%-60%,并帮助检测大约25%的漏洞。该视频在https://youtu.be/l6hW3Ds5Tkg上发布。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Semantic table structure identification in spreadsheets Parema: an unpacking framework for demystifying VM-based Android packers TERA: optimizing stochastic regression tests in machine learning projects Empirically evaluating readily available information for regression test optimization in continuous integration RESTest: automated black-box testing of RESTful web APIs
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1