Conceptual Software Reliability Prediction Models for Nuclear Power Plant Safety Systems

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The objective of this project is to develop a method to predict the potential reliability of software to be used in a digital system instrumentation and control system. The reliability prediction is to make use of existing measures of software reliability such as those described in IEEE Std 982 and 982.2. This prediction must be of sufficient accuracy to provide a value for uncertainty that could be used in a nuclear power plant probabilistic risk assessment (PRA). For the purposes of the project, reliability was defined to be the probability that the digital system will successfully perform its intended safety ... continued below

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Johnson, G.; Lawrence, D. & Yu, H. April 3, 2000.

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Description

The objective of this project is to develop a method to predict the potential reliability of software to be used in a digital system instrumentation and control system. The reliability prediction is to make use of existing measures of software reliability such as those described in IEEE Std 982 and 982.2. This prediction must be of sufficient accuracy to provide a value for uncertainty that could be used in a nuclear power plant probabilistic risk assessment (PRA). For the purposes of the project, reliability was defined to be the probability that the digital system will successfully perform its intended safety function (for the distribution of conditions under which it is expected to respond) upon demand with no unintended functions that might affect system safety. The ultimate objective is to use the identified measures to develop a method for predicting the potential quantitative reliability of a digital system. The reliability prediction models proposed in this report are conceptual in nature. That is, possible prediction techniques are proposed and trial models are built, but in order to become a useful tool for predicting reliability, the models must be tested, modified according to the results, and validated. Using methods outlined by this project, models could be constructed to develop reliability estimates for elements of software systems. This would require careful review and refinement of the models, development of model parameters from actual experience data or expert elicitation, and careful validation. By combining these reliability estimates (generated from the validated models for the constituent parts) in structural software models, the reliability of the software system could then be predicted. Modeling digital system reliability will also require that methods be developed for combining reliability estimates for hardware and software. System structural models must also be developed in order to predict system reliability based upon the reliability of the individual hardware/software components. Existing modeling techniques--such as fault tree analyses or reliability block diagrams--can probably be adapted to bridge the gaps between the reliability of the hardware components, the individual software elements, and the overall digital system. This project builds upon previous work to survey and rank potential measurement methods which could be used to measure software product reliability 3. This survey and ranking identified candidate measures for use in predicting the reliability of digital computer-based control and protection systems for nuclear power plants. Additionally, information gleaned from the study can be used to supplement existing review methods during an assessment of software-based digital systems.

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1,100 Kilobytes pages

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  • Other Information: PBD: 3 Apr 2000

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  • Report No.: UCRL-ID-138577
  • Grant Number: W-7405-Eng-48
  • DOI: 10.2172/791856 | External Link
  • Office of Scientific & Technical Information Report Number: 791856
  • Archival Resource Key: ark:/67531/metadc742660

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Reports, articles and other documents harvested from the Office of Scientific and Technical Information.

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  • April 3, 2000

Added to The UNT Digital Library

  • Oct. 19, 2015, 7:39 p.m.

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  • May 5, 2016, 9:09 p.m.

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Johnson, G.; Lawrence, D. & Yu, H. Conceptual Software Reliability Prediction Models for Nuclear Power Plant Safety Systems, report, April 3, 2000; California. (digital.library.unt.edu/ark:/67531/metadc742660/: accessed April 21, 2018), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.