Review of Quantitative Software Reliability Methods

PDF Version Also Available for Download.

Description

The current U.S. Nuclear Regulatory Commission (NRC) licensing process for digital systems rests on deterministic engineering criteria. In its 1995 probabilistic risk assessment (PRA) policy statement, the Commission encouraged the use of PRA technology in all regulatory matters to the extent supported by the state-of-the-art in PRA methods and data. Although many activities have been completed in the area of risk-informed regulation, the risk-informed analysis process for digital systems has not yet been satisfactorily developed. Since digital instrumentation and control (I&C) systems are expected to play an increasingly important role in nuclear power plant (NPP) safety, the NRC established a ... continued below

Creation Information

Chu, T.L.; Yue, M.; Martinez-Guridi, M. & Lehner, J. September 17, 2010.

Context

This report is part of the collection entitled: Office of Scientific & Technical Information Technical Reports and was provided by UNT Libraries Government Documents Department to Digital Library, a digital repository hosted by the UNT Libraries. It has been viewed 52 times . More information about this report can be viewed below.

Who

People and organizations associated with either the creation of this report or its content.

Provided By

UNT Libraries Government Documents Department

Serving as both a federal and a state depository library, the UNT Libraries Government Documents Department maintains millions of items in a variety of formats. The department is a member of the FDLP Content Partnerships Program and an Affiliated Archive of the National Archives.

Contact Us

What

Descriptive information to help identify this report. Follow the links below to find similar items on the Digital Library.

Description

The current U.S. Nuclear Regulatory Commission (NRC) licensing process for digital systems rests on deterministic engineering criteria. In its 1995 probabilistic risk assessment (PRA) policy statement, the Commission encouraged the use of PRA technology in all regulatory matters to the extent supported by the state-of-the-art in PRA methods and data. Although many activities have been completed in the area of risk-informed regulation, the risk-informed analysis process for digital systems has not yet been satisfactorily developed. Since digital instrumentation and control (I&C) systems are expected to play an increasingly important role in nuclear power plant (NPP) safety, the NRC established a digital system research plan that defines a coherent set of research programs to support its regulatory needs. One of the research programs included in the NRC's digital system research plan addresses risk assessment methods and data for digital systems. Digital I&C systems have some unique characteristics, such as using software, and may have different failure causes and/or modes than analog I&C systems; hence, their incorporation into NPP PRAs entails special challenges. The objective of the NRC's digital system risk research is to identify and develop methods, analytical tools, and regulatory guidance for (1) including models of digital systems into NPP PRAs, and (2) using information on the risks of digital systems to support the NRC's risk-informed licensing and oversight activities. For several years, Brookhaven National Laboratory (BNL) has worked on NRC projects to investigate methods and tools for the probabilistic modeling of digital systems, as documented mainly in NUREG/CR-6962 and NUREG/CR-6997. However, the scope of this research principally focused on hardware failures, with limited reviews of software failure experience and software reliability methods. NRC also sponsored research at the Ohio State University investigating the modeling of digital systems using dynamic PRA methods. These efforts, documented in NUREG/CR-6901, NUREG/CR-6942, and NUREG/CR-6985, included a functional representation of the system's software but did not explicitly address failure modes caused by software defects or by inadequate design requirements. An important identified research need is to establish a commonly accepted basis for incorporating the behavior of software into digital I&C system reliability models for use in PRAs. To address this need, BNL is exploring the inclusion of software failures into the reliability models of digital I&C systems, such that their contribution to the risk of the associated NPP can be assessed.

Language

Item Type

Identifier

Unique identifying numbers for this report in the Digital Library or other systems.

  • Report No.: BNL--94047-2010
  • Grant Number: DE-AC02-98CH10886
  • DOI: 10.2172/1013511 | External Link
  • Office of Scientific & Technical Information Report Number: 1013511
  • Archival Resource Key: ark:/67531/metadc840624

Collections

This report is part of the following collection of related materials.

Office of Scientific & Technical Information Technical Reports

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

Office of Scientific and Technical Information (OSTI) is the Department of Energy (DOE) office that collects, preserves, and disseminates DOE-sponsored research and development (R&D) results that are the outcomes of R&D projects or other funded activities at DOE labs and facilities nationwide and grantees at universities and other institutions.

What responsibilities do I have when using this report?

When

Dates and time periods associated with this report.

Creation Date

  • September 17, 2010

Added to The UNT Digital Library

  • May 19, 2016, 3:16 p.m.

Description Last Updated

  • July 21, 2016, 7:04 p.m.

Usage Statistics

When was this report last used?

Yesterday: 0
Past 30 days: 0
Total Uses: 52

Interact With This Report

Here are some suggestions for what to do next.

Start Reading

PDF Version Also Available for Download.

Citations, Rights, Re-Use

Chu, T.L.; Yue, M.; Martinez-Guridi, M. & Lehner, J. Review of Quantitative Software Reliability Methods, report, September 17, 2010; United States. (digital.library.unt.edu/ark:/67531/metadc840624/: accessed December 11, 2017), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.