Abstract
Goal structuring notation (GSN) is commonly proposed as a structuring tool for arguing about the high-level properties (e.g. safety) of a system. However, this approach does not include the representation of uncertainties that may affect arguments. Several works extend this framework using uncertainty propagation methods. The ones based on Dempster-Shafer Theory (DST) are of interest as DST can model incomplete information. However, few works relate this approach with a logical representation of relations between elements of GSN, which is actually required to justify the chosen uncertainty propagation schemes. In this paper, we improve previous proposals including a logical formalism added to GSN, and an elicitation procedure for obtaining uncertainty information from expert judgements. We briefly present an application to a case study to validate our uncertainty propagation model in GSN that takes into account both incomplete and conflicting information.
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Notes
- 1.
Machine learning Model.
- 2.
The questionnaire is available in [11].
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Acknowledgement
A special thanks to the authors of [3], especially to Christophe GABREAU for answering the questionnaire concerning the assessment of the GSN presented in our case study.
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Idmessaoud, Y., Dubois, D., Guiochet, J. (2022). Uncertainty Elicitation and Propagation in GSN Models of Assurance Cases. In: Trapp, M., Saglietti, F., Spisländer, M., Bitsch, F. (eds) Computer Safety, Reliability, and Security. SAFECOMP 2022. Lecture Notes in Computer Science, vol 13414. Springer, Cham. https://doi.org/10.1007/978-3-031-14835-4_8
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