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Development of a Bayesian belief network model for quantifying software failure probability of a protection system
- Authors
- Chu, T.L.; Varuttamaseni, A.; Yue, M.; Lee, S.J.; Eom, H.S.; Kang, H.G.; Kim, M.C.; Son, H.S.; Yang, S.
- Issue Date
- Apr-2015
- Publisher
- American Nuclear Society
- Citation
- International Topical Meeting on Probabilistic Safety Assessment and Analysis, PSA 2015, v.2, pp 909 - 917
- Pages
- 9
- Journal Title
- International Topical Meeting on Probabilistic Safety Assessment and Analysis, PSA 2015
- Volume
- 2
- Start Page
- 909
- End Page
- 917
- ISSN
- 0000-0000
- Abstract
- A Bayesian Belief Network model for quantifying the probability of failure on demand of a protection system due to software failures is presented. It is based on the assumption that the quality in carrying out the software development activities determines the reliability of the software. The oval BBN model is a generic one that can be applied to any safety critical software. It uses the quality evaluation and debugging data of a specific software program to estimate the number of faults injected and the number of Ihults detected and removed in each phase of the development process. The estimated number of faults is then converted into a software failure probability using a Fault Size Distribution. © 2015 by the American Nuclear Society.
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