Estimating the parameters of a non-homogeneous Poisson-process model for software reliability

Author

Hossain, Syed A. ; Dahiya, Ram C.

Author_Institution

Middle Tennessee State Univ., Murfreesboro, TN, USA

Volume

42

Issue

4

fYear

1993

fDate

12/1/1993 12:00:00 AM

Firstpage

604

Lastpage

612

Abstract

A stochastic model (G-O) for the software failure phenomenon based on a nonhomogeneous Poisson process (NHPP) was suggested by Goel and Okumoto (1979). This model has been widely used but some important work remains undone on estimating the parameters. The authors present a necessary and sufficient condition for the likelihood estimates to be finite, positive, and unique. A modification of the G-O model is suggested. The performance measures and parametric inferences of the new model are discussed. The results of the new model are applied to real software failure data and compared with G-O and Jelinski-Moranda models

Keywords

parameter estimation; probability; software reliability; stochastic processes; G-O model; inferences; likelihood estimates; nonhomogeneous Poisson process; parameter estimation; performance; software failure; software reliability; stochastic model; Maximum likelihood estimation; Nonlinear equations; Parameter estimation; Probability distribution; Software measurement; Software performance; Software reliability; State estimation; Stochastic processes; Sufficient conditions;

fLanguage

English

Journal_Title

Reliability, IEEE Transactions on

Publisher

ieee

ISSN

0018-9529

Type

jour

DOI

10.1109/24.273589

Filename

273589