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- Lee, Seung Jun
- Nuclear Safety Assessment and Plant HMI Evolution Lab.
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DEVELOPMENT OF A BAYESIAN BELIEF NETWORK MODEL FOR QUANTIFYING SOFTWARE FAILURE PROBABILITY OF A PROTECTION SYSTEM
- Author(s)
- Chu, Tsong-Lun, Varuttamaseni, Athi, Yue, Meng, Lee, Seung Jun, Eom, Heung Seop, Kang, Hyun Gook, Kim, Man Cheol, Son, Han Seong, Yang, Steve
- Issued Date
- 2015-04-26
- Citation
- PSA 2015: International Topical Meeting of Probabilistic Safety Assessment and Analysis
- 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 faults 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.
- Publisher
- America Nuclear Society
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