Document: NUREG-0800
Document ID: debf22b1-f3aa-4c75-a43c-f162d22de1c8
Document Type: srp
Title: of the plant safety analysis report (SAR).  Although the NRC did not endorse the annexes of
Source: NUREG-0800
Source URL: https://www.nrc.gov/docs/ML1515/ML15159A491.pdf
Revision Date: 2023-06
Chapter: 7
Section ID: 7.6
CFR Part: 
CFR Title: 

Content:
or failure of the activities and tasks defined in the planning document. The use of software quality metrics should be considered throughout the software life-cycle to assess whether software quality requirements are being met. When software quality metrics are used, the following life-cycle phase characteristics should be considered: • Correctness/Completeness (requirements phase) • Compliance with requirements (design phase) • Compliance with design (implementation phase) • Functional compliance with requirements (test and integration phase) • On-site functional compliance with requirements (installation and checkout phase) • Performance history (operation and maintenance phase) The basis for the metrics selected to evaluate software quality characteristics should be included in the software development documentation. IEEE Std 1061-1998, “IEEE Standard for Appendix 7.1-D-9 Draft Revision 2 – August 2015 a Software Quality Metrics Methodology,” discusses the software quality metrics methodology and methods by which various metrics systems can be evaluated. Reviewers should be careful when reviewing the results of any software metric to evaluate what that metric actually measures, and what conclusion can be reached based on these measurements. The metric may, for example, be useful to the software vendor to show diminishing returns on continued testing, but unless the quality and thoroughness of the testing program is evaluated, it may not be sufficient to demonstrate that the software is of high quality. Quality becomes more visible through a well-conceived and effectively implemented software metrics program. A metrics methodology that uses a diversity of software measures and that appropriately aggregates the measurement data could provide quantitative data that would give the staff insight into the rigor of the safety software development process and the resulting quality of the life-cycle outputs. 5.3.2 Software Tools (IEEE Std 7-4.3.2,