Fitting and prediction uncertainty for a software reliability model
Loading...
Authors
Dennison, Thomas E.
Subjects
Software
Reliability
Bootstrap
Prediction analysis
Software reliability models
Bayesian methodology
Reliability
Bootstrap
Prediction analysis
Software reliability models
Bayesian methodology
Advisors
Gaver, Donald P.
Date of Issue
1992-03
Date
March 1992
Publisher
Monterey, California. Naval Postgraduate School
Language
en_US
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 estimates of the mean time to next failure or expected numbers 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 numbers of faults to occur for additional testing time. the result can be particularly useful for a software manager who has to answer a subjective question: is the software reliable enough to support system operational testing?. A range of predicted 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 technique emphasizing how a software manager should analyze the results.
Type
Thesis
Description
Series/Report No
Department
Department of Operations Analysis
Organization
Naval Postgraduate School (U.S.)
Identifiers
NPS Report Number
Sponsors
Funder
Format
63 p.
Citation
Distribution Statement
Approved for public release; distribution is unlimited.
Rights
This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.