Measuring Confidence of Assurance Cases in Safety-Critical Domains Lin, Chung-Ling Shen, Wuwei Cheng, Betty 2020-01-04T08:30:15Z 2020-01-04T08:30:15Z 2020-01-07
dc.description.abstract Evaluation of assurance cases typically requires certifiers’ domain knowledge and experience, and, as such, most software certification has been conducted manually. Given the advancement in uncertainty theories and software traceability, we envision that these technologies can synergistically be combined and leveraged to offer some degree of automation to improve the certifiers’ capability to perform software certification. To this end, we present DS4AC, a novel confidence calculation framework that 1) applies the Dempster-Shafer theory to calculate the confidence between a parent claim and its children claims; and 2) uses the vector space model to evaluate the confidence for the evidence items using traceability information. We illustrate our approach on two different applications, where safety is the key property of interest for both systems. In both cases, we use the Goal Structuring Notation to represent the respective assurance cases and provide proof of concept results that demonstrate the DS4AC framework can automate portions of the evaluation of assurance cases, thereby reducing the burden of manual certification process.
dc.format.extent 10 pages
dc.identifier.doi 10.24251/HICSS.2020.778
dc.identifier.isbn 978-0-9981331-3-3
dc.language.iso eng
dc.relation.ispartof Proceedings of the 53rd Hawaii International Conference on System Sciences
dc.rights Attribution-NonCommercial-NoDerivatives 4.0 International
dc.subject Cybersecurity and Software Assurance
dc.subject dempster-shafer theory
dc.subject software certification
dc.subject software traceability
dc.subject vector space model (vsm)
dc.title Measuring Confidence of Assurance Cases in Safety-Critical Domains
dc.type Conference Paper
dc.type.dcmi Text
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