Assurance cases are used to document an argument that a system - such as a critical software system - satisfies some desirable property (e.g., safety, security, or reliability). Demonstrating high confidence that the claims made based on an assurance case can be trusted is crucial to the success of the case. Researchers have proposed quantification of confidence as a Baconian probability ratio of eliminated concerns about the assurance case to the total number of identified concerns. In this paper, we extend their work by mapping this discrete ratio to a continuous probability distribution - a beta distribution - enabling different visualizations of the confidence in a claim. Further, the beta distribution allows us to quantify and visualize theuncertainty associated with the expressed confidence. Additionally, by transforming the assurance case into a reasoning structure, we show how confidence calculations can be performed using beta distributions.
|Original language||English (US)|
|Title of host publication||Proceedings - 17th IEEE International Symposium on High Assurance Systems Engineering, HASE 2016|
|Editors||Radu Babiceanu, Helene Waeselynck, Jie Xu, Raymond A. Paul, Bojan Cukic|
|Publisher||IEEE Computer Society|
|Number of pages||8|
|State||Published - Mar 1 2016|
|Event||17th IEEE International Symposium on High Assurance Systems Engineering, HASE 2016 - Orlando, United States|
Duration: Jan 7 2016 → Jan 9 2016
|Name||Proceedings of IEEE International Symposium on High Assurance Systems Engineering|
|Other||17th IEEE International Symposium on High Assurance Systems Engineering, HASE 2016|
|Period||1/7/16 → 1/9/16|
Bibliographical noteFunding Information:
Acknowledgment: This work has been partially supported by NSF grant CNS- 1035715.