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Input-profile-based software failure probability quantification for safety signal generation systems

Author

Listed:
  • Kang, Hyun Gook
  • Lim, Ho Gon
  • Lee, Ho Jung
  • Kim, Man Cheol
  • Jang, Seung Cheol

Abstract

The approaches for software failure probability estimation are mainly based on the results of testing. Test cases represent the inputs, which are encountered in an actual use. The test inputs for the safety-critical application such as a reactor protection system (RPS) of a nuclear power plant are the inputs which cause the activation of protective action such as a reactor trip. A digital system treats inputs from instrumentation sensors as discrete digital values by using an analog-to-digital converter. Input profile must be determined in consideration of these characteristics for effective software failure probability quantification. Another important characteristic of software testing is that we do not have to repeat the test for the same input value since the software response is deterministic for each specific digital input. With these considerations, we propose an effective software testing method for quantifying the failure probability. As an example application, the input profile of the digital RPS is developed based on the typical plant data. The proposed method in this study is expected to provide a simple but realistic mean to quantify the software failure probability based on input profile and system dynamics.

Suggested Citation

  • Kang, Hyun Gook & Lim, Ho Gon & Lee, Ho Jung & Kim, Man Cheol & Jang, Seung Cheol, 2009. "Input-profile-based software failure probability quantification for safety signal generation systems," Reliability Engineering and System Safety, Elsevier, vol. 94(10), pages 1542-1546.
    • Handle: RePEc:eee:reensy:v:94:y:2009:i:10:p:1542-1546
    DOI: 10.1016/j.ress.2009.02.018
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    References listed on IDEAS

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    1. Sohn, Se Do & Hyun Seong, Poong, 2006. "Testing digital safety system software with a testability measure based on a software fault tree," Reliability Engineering and System Safety, Elsevier, vol. 91(1), pages 44-52.
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    Cited by:

    1. Peng, R. & Li, Y.F. & Zhang, W.J. & Hu, Q.P., 2014. "Testing effort dependent software reliability model for imperfect debugging process considering both detection and correction," Reliability Engineering and System Safety, Elsevier, vol. 126(C), pages 37-43.
    2. Lee, Sang Hun & Lee, Seung Jun & Shin, Sung Min & Lee, Eun-chan & Kang, Hyun Gook, 2020. "Exhaustive testing of safety-critical software for reactor protection system," Reliability Engineering and System Safety, Elsevier, vol. 193(C).

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