利用工件树来发展和重用安全用例

Ankit Agrawal, S. Khoshmanesh, Michael Vierhauser, Mona Rahimi, J. Cleland-Huang, R. Lutz
{"title":"利用工件树来发展和重用安全用例","authors":"Ankit Agrawal, S. Khoshmanesh, Michael Vierhauser, Mona Rahimi, J. Cleland-Huang, R. Lutz","doi":"10.1109/ICSE.2019.00124","DOIUrl":null,"url":null,"abstract":"Safety Assurance Cases (SACs) are increasingly used to guide and evaluate the safety of software-intensive systems. They are used to construct a hierarchically organized set of claims, arguments, and evidence in order to provide a structured argument that a system is safe for use. However, as the system evolves and grows in size, a SAC can be difficult to maintain. In this paper we utilize design science to develop a novel solution for identifying areas of a SAC that are affected by changes to the system. Moreover, we generate actionable recommendations for updating the SAC, including its underlying artifacts and trace links, in order to evolve an existing safety case for use in a new version of the system. Our approach, Safety Artifact Forest Analysis (SAFA), leverages traceability to automatically compare software artifacts from a previously approved or certified version with a new version of the system. We identify, visualize, and explain changes in a Delta Tree. We evaluate our approach using the Dronology system for monitoring and coordinating the actions of cooperating, small Unmanned Aerial Vehicles. Results from a user study show that SAFA helped users to identify changes that potentially impacted system safety and provided information that could be used to help maintain and evolve a SAC.","PeriodicalId":6736,"journal":{"name":"2019 IEEE/ACM 41st International Conference on Software Engineering (ICSE)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2019-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"14","resultStr":"{\"title\":\"Leveraging Artifact Trees to Evolve and Reuse Safety Cases\",\"authors\":\"Ankit Agrawal, S. Khoshmanesh, Michael Vierhauser, Mona Rahimi, J. Cleland-Huang, R. Lutz\",\"doi\":\"10.1109/ICSE.2019.00124\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Safety Assurance Cases (SACs) are increasingly used to guide and evaluate the safety of software-intensive systems. They are used to construct a hierarchically organized set of claims, arguments, and evidence in order to provide a structured argument that a system is safe for use. However, as the system evolves and grows in size, a SAC can be difficult to maintain. In this paper we utilize design science to develop a novel solution for identifying areas of a SAC that are affected by changes to the system. Moreover, we generate actionable recommendations for updating the SAC, including its underlying artifacts and trace links, in order to evolve an existing safety case for use in a new version of the system. Our approach, Safety Artifact Forest Analysis (SAFA), leverages traceability to automatically compare software artifacts from a previously approved or certified version with a new version of the system. We identify, visualize, and explain changes in a Delta Tree. We evaluate our approach using the Dronology system for monitoring and coordinating the actions of cooperating, small Unmanned Aerial Vehicles. Results from a user study show that SAFA helped users to identify changes that potentially impacted system safety and provided information that could be used to help maintain and evolve a SAC.\",\"PeriodicalId\":6736,\"journal\":{\"name\":\"2019 IEEE/ACM 41st International Conference on Software Engineering (ICSE)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-05-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"14\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 IEEE/ACM 41st International Conference on Software Engineering (ICSE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICSE.2019.00124\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE/ACM 41st International Conference on Software Engineering (ICSE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSE.2019.00124","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 14

摘要

安全保证案例(SACs)越来越多地用于指导和评估软件密集型系统的安全性。它们被用来构造一组分层组织的声明、论证和证据,以提供一个结构化的论证,说明系统可以安全使用。然而,随着系统的发展和规模的增长,SAC可能难以维护。在本文中,我们利用设计科学来开发一种新的解决方案,用于识别受系统变化影响的SAC区域。此外,我们为更新SAC(包括其底层工件和跟踪链接)生成可操作的建议,以便发展现有的安全案例,以便在系统的新版本中使用。我们的方法,安全工件森林分析(SAFA),利用可追溯性来自动比较来自先前批准或认证版本的软件工件与系统的新版本。我们识别、可视化并解释Delta树中的变化。我们利用无人机系统评估我们的方法,以监测和协调合作的小型无人机的行动。来自用户研究的结果表明,SAFA帮助用户识别可能影响系统安全的变化,并提供可用于帮助维护和发展SAC的信息。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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
Leveraging Artifact Trees to Evolve and Reuse Safety Cases
Safety Assurance Cases (SACs) are increasingly used to guide and evaluate the safety of software-intensive systems. They are used to construct a hierarchically organized set of claims, arguments, and evidence in order to provide a structured argument that a system is safe for use. However, as the system evolves and grows in size, a SAC can be difficult to maintain. In this paper we utilize design science to develop a novel solution for identifying areas of a SAC that are affected by changes to the system. Moreover, we generate actionable recommendations for updating the SAC, including its underlying artifacts and trace links, in order to evolve an existing safety case for use in a new version of the system. Our approach, Safety Artifact Forest Analysis (SAFA), leverages traceability to automatically compare software artifacts from a previously approved or certified version with a new version of the system. We identify, visualize, and explain changes in a Delta Tree. We evaluate our approach using the Dronology system for monitoring and coordinating the actions of cooperating, small Unmanned Aerial Vehicles. Results from a user study show that SAFA helped users to identify changes that potentially impacted system safety and provided information that could be used to help maintain and evolve a SAC.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
VFix: Value-Flow-Guided Precise Program Repair for Null Pointer Dereferences Search-Based Energy Testing of Android Scalable Approaches for Test Suite Reduction A System Identification Based Oracle for Control-CPS Software Fault Localization Training Binary Classifiers as Data Structure Invariants
×
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