Ankit Agrawal, S. Khoshmanesh, Michael Vierhauser, Mona Rahimi, J. Cleland-Huang, R. Lutz
{"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":"25 1","pages":"1222-1233"},"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}
引用次数: 14
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.