Computer-Aided Generation of Assurance Cases

被引:3
作者
Wang, Timothy E. [1 ]
Oh, Chanwook [2 ]
Low, Matthew [2 ]
Amundson, Isaac [3 ]
Daw, Zamira [4 ]
Pinto, Alessandro [5 ]
Chiodo, Massimiliano L. [1 ]
Wang, Guoqiang [1 ]
Hasan, Saqib [3 ]
Melville, Ryan [1 ]
Nuzzo, Pierluigi [2 ]
机构
[1] Raytheon Technol Res Ctr, Berkeley, CA 94705 USA
[2] Univ Southern Calif, Los Angeles, CA USA
[3] Collins Aerosp, Cedar Rapids, IA USA
[4] Univ Stuttgart, Stuttgart, Germany
[5] NASA Jet Prop Lab, Pasadena, CA USA
来源
COMPUTER SAFETY, RELIABILITY, AND SECURITY, SAFECOMP 2023 WORKSHOPS | 2023年 / 14182卷
基金
美国国家科学基金会;
关键词
Assurance case; contracts; synthesis; validation; confidence;
D O I
10.1007/978-3-031-40953-0_12
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Assurance cases (ACs) have gained attention in the aerospace, medical, and other heavily-regulated industries as a means for providing structured arguments on why a product is dependable (i.e., safe, secure, etc.) for its intended application. Challenges in AC construction stem from the complexity and uniqueness of the designs, the heterogeneous nature of the required supporting evidence, and the need to assess the quality of an argument. We present an automated AC generation framework that facilitates the construction, validation, and confidence assessment of ACs based on dependability argument patterns and confidence patterns capturing domain knowledge. The ACs are instantiated with a system's specification and evaluated based on the available design and verification evidence. Aerospace case studies illustrate the framework's effectiveness, efficiency, and scalability.
引用
收藏
页码:135 / 148
页数:14
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