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Experimental approach to evaluate software reliability in hardware-software integrated environment
- Source :
- Nuclear Engineering and Technology, Vol 52, Iss 7, Pp 1462-1470 (2020)
- Publication Year :
- 2020
- Publisher :
- Elsevier BV, 2020.
-
Abstract
- Reliability in safety-critical systems and equipment is of vital importance, so the probabilistic safety assessment (PSA) has been widely used for many years in the nuclear industry to address reliability in a quantitative manner. As many nuclear power plants (NPPs) become digitalized, evaluating the reliability of safety-critical software has become an emerging issue. Due to a lack of available methods, in many conventional PSA models only hardware reliability is addressed with the assumption that software reliability is perfect or very high compared to hardware reliability. This study focused on developing a new method of safety-critical software reliability quantification, derived from hardware-software integrated environment testing. Since the complexity of hardware and software interaction makes the possible number of test cases for exhaustive testing well beyond a practically achievable range, an importance-oriented testing method that assures the most efficient test coverage was developed. Application to the test of an actual NPP reactor protection system demonstrated the applicability of the developed method and provided insight into complex software-based system reliability.
- Subjects :
- Computer science
business.industry
020209 energy
Code coverage
Probabilistic logic
02 engineering and technology
Probabilistic safety assessment
Software reliability
Digital instrumentation and control
lcsh:TK9001-9401
Reactor protection system
Software quality
030218 nuclear medicine & medical imaging
Reliability engineering
03 medical and health sciences
0302 clinical medicine
Test case
Software
Nuclear Energy and Engineering
0202 electrical engineering, electronic engineering, information engineering
Failure modes and effects analysis
lcsh:Nuclear engineering. Atomic power
business
Failure mode and effects analysis
Reliability (statistics)
Subjects
Details
- ISSN :
- 17385733
- Volume :
- 52
- Database :
- OpenAIRE
- Journal :
- Nuclear Engineering and Technology
- Accession number :
- edsair.doi.dedup.....b57d6c47ff55e0a4ed8fa34c6e337205
- Full Text :
- https://doi.org/10.1016/j.net.2020.01.004