Completely monotone regression estimates of software failure rates

Authors:
Douglas R. Miller;Ariela Sofer
Affiliations:
Department of Operations Research, George Washington University, Washington, D.C.;Department of Systems Engineering, George Mason University, Fairfax, Virginia
Venue:
ICSE '85 Proceedings of the 8th international conference on Software engineering
Year:
1985

Citing 2
Cited 1

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Abstract

A new method for estimating the present failure rate of a program is presented. A crude nonparametric estimate of the failure rate function is obtained from past failure times. This estimate is then smoothed by fitting a completely monotonic function, which is the solution of a quadratic programming problem. The value of the smoothed function at present time is used as the estimate of present failure rate. A Monte Carlo study gives an indication of how well this method works.