Accession Number:

ADA252173

Title:

Fitting and Prediction Uncertainty for a Software Reliability Model

Descriptive Note:

Master's thesis

Corporate Author:

NAVAL POSTGRADUATE SCHOOL MONTEREY CA

Personal Author(s):

Report Date:

1992-03-01

Pagination or Media Count:

70.0

Abstract:

The cost of system operational testing is steadily increasing. It is desirable for the software manager to know if the software is sufficiently well developed or reliable to support such testing. Current software reliability models provide only point estimates of the mean time to next failure or expected number of errors to occur in additional testing time. The goal of this thesis is to take into account prediction uncertainties of a software reliability model. Bootstrapping is used to provide the software manager with confidence limits of the predicted expected number of faults to occur for additional testing time. The results can be particularly useful to a software manager who has to answer a subjective question is the software reliable enough to support system operational testing A range of predicted expected number of faults will be of more use to a software manager, who has to justify the answer to this question, than just a point estimate. Two software fault data sets are analyzed with this techniques emphasizing how a software manager should analyze the results.

Subject Categories:

  • Statistics and Probability
  • Computer Programming and Software

Distribution Statement:

APPROVED FOR PUBLIC RELEASE