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

Hyun Gook Kang, Ho Gon Lim, Ho Jung Lee, Man Cheol Kim and Seung Cheol Jang

Reliability Engineering and System Safety, 2009, vol. 94, issue 10, 1542-1546

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.

Keywords: Software testing; Input profile; Safety-critical application; Software failure probability (search for similar items in EconPapers)
Date: 2009
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:94:y:2009:i:10:p:1542-1546

DOI: 10.1016/j.ress.2009.02.018

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