Estimating the probability of failure when testing reveals no failures

Author

Miller, Keith W. ; Morell, Larry J. ; Noonan, Robert E. ; Park, Stephen K. ; Nicol, David M. ; Murrill, Branson W. ; Voas, Jeffrey M.

Author_Institution

Dept. of Comput. Sci., Coll. of William & Mary, Williamsburg, VA, USA

Volume

18

Issue

1

fYear

1992

fDate

1/1/1992 12:00:00 AM

Firstpage

33

Lastpage

43

Abstract

Formulas for estimating the probability of failure when testing reveals no errors are introduced. These formulas incorporate random testing results, information about the input distribution; and prior assumptions about the probability of failure of the software. The formulas are not restricted to equally likely input distributions, and the probability of failure estimate can be adjusted when assumptions about the input distribution change. The formulas are based on a discrete sample space statistical model of software and include Bayesian prior assumptions. Reusable software and software in life-critical applications are particularly appropriate candidates for this type of analysis

Keywords

Bayes methods; probability; program testing; Bayesian prior assumptions; discrete sample space statistical model; failure estimate; failure probability estimation; formulas; input distribution; life-critical applications; prior assumptions; random testing results; Application software; Bayesian methods; Computer errors; Computer science; NASA; Probability density function; Software reliability; Software reusability; Software testing; System testing;

fLanguage

English

Journal_Title

Software Engineering, IEEE Transactions on

Publisher

ieee

ISSN

0098-5589

Type

jour

DOI

10.1109/32.120314

Filename

120314