ARepair: A Repair Framework for Alloy

Kaiyuan Wang, Allison Sullivan, S. Khurshid
{"title":"ARepair: A Repair Framework for Alloy","authors":"Kaiyuan Wang, Allison Sullivan, S. Khurshid","doi":"10.1109/ICSE-Companion.2019.00049","DOIUrl":null,"url":null,"abstract":"Researchers have proposed many automated program repair techniques for imperative languages, e.g. Java. However, little work has been done to repair programs written in declarative languages, e.g. Alloy. We proposed ARepair, the first automated program repair technique for faulty Alloy models. ARepair takes as input a faulty Alloy model and a set of tests that capture the desired model properties, and produces a fixed model that passes all tests. ARepair uses tests written for the recently introduced AUnit framework, which provides a notion of unit testing for Alloy models. In this paper, we describes our Java implementation of ARepair, which is a command-line tool, released as an open-source project on GitHub. Our experimental results show that ARepair is able to fix 28 out of 38 real-world faulty models we collected. The demo video for ARepair can be found at https://youtu.be/436drvWvbEU.","PeriodicalId":273100,"journal":{"name":"2019 IEEE/ACM 41st International Conference on Software Engineering: Companion Proceedings (ICSE-Companion)","volume":"136 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE/ACM 41st International Conference on Software Engineering: Companion Proceedings (ICSE-Companion)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSE-Companion.2019.00049","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 9

Abstract

Researchers have proposed many automated program repair techniques for imperative languages, e.g. Java. However, little work has been done to repair programs written in declarative languages, e.g. Alloy. We proposed ARepair, the first automated program repair technique for faulty Alloy models. ARepair takes as input a faulty Alloy model and a set of tests that capture the desired model properties, and produces a fixed model that passes all tests. ARepair uses tests written for the recently introduced AUnit framework, which provides a notion of unit testing for Alloy models. In this paper, we describes our Java implementation of ARepair, which is a command-line tool, released as an open-source project on GitHub. Our experimental results show that ARepair is able to fix 28 out of 38 real-world faulty models we collected. The demo video for ARepair can be found at https://youtu.be/436drvWvbEU.
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
ARepair:一种合金修复框架
研究人员已经为命令式语言(如Java)提出了许多自动程序修复技术。然而,修复用声明性语言(如Alloy)编写的程序的工作很少。我们提出了ARepair,这是第一个用于故障合金模型的自动程序修复技术。ARepair将一个有故障的Alloy模型和一组捕获所需模型属性的测试作为输入,并生成一个通过所有测试的固定模型。ARepair使用为最近引入的AUnit框架编写的测试,该框架为Alloy模型提供了单元测试的概念。在本文中,我们描述了ARepair的Java实现,ARepair是一个命令行工具,作为GitHub上的开源项目发布。我们的实验结果表明,ARepair能够修复我们收集的38个实际故障模型中的28个。ARepair的演示视频可以在https://youtu.be/436drvWvbEU上找到。
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
On the Deterioration of Learning-Based Malware Detectors for Android Quantifying Patterns and Programming Strategies in Block-Based Programming Environments A Data-Driven Security Game to Facilitate Information Security Education Toward Detection and Characterization of Variability Bugs in Configurable C Software: An Empirical Study Mimicking User Behavior to Improve In-House Test Suites
×
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