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A Bayesian Estimation Method for the Failure Rate of a Possibly Correct Program
November 1990 (vol. 16 no. 11)
pp. 1307-1310

An extension of software reliability modeling is introduced to account for the possibility of programs which, after some debugging, contain no more errors. This is achieved by a repetitive application of the Bayes law, each time taking the posterior of the last step as a prior for the next one. A class of conjugate priors considerably facilitates this modeling. The resulting model includes an estimator for the probability that a program still contains errors, which is an upper bound for the failure probability.

[1] Z. Jelinski and P. B. Moranda, "Application of a probability based model to a code reading experiment," inProc. IEEE Symp. Computer Software Reliability, 1973.
[2] B. Littlewood, "A Bayesian reliability growth model for Computer Software," inProc. IEEE Symp. Computer Software Reliability, 1973.
[3] G. J. Schick and R. W. Wolverton, "An analysis of computing software reliability models,"IEEE Trans. Software Eng., vol. SE-4, pp. 104-120, 1978.
[4] B. Littlewood, "How to measure software reliability and how not to,"IEEE Trans. Rel., vol. R-28, pp. 103-110, 1979.
[5] H. F. Martz and R. A. Waller,Bayesian Reliability Analysis. New York: Wiley, 1982.

Index Terms:
prior step; Bayesian estimation method; failure rate; possibly correct program; software reliability modeling; Bayes law; posterior; last step; conjugate priors; estimator; upper bound; failure probability; Bayes methods; probability; software reliability
Citation:
G. Becker, L. Camarinopoulos, "A Bayesian Estimation Method for the Failure Rate of a Possibly Correct Program," IEEE Transactions on Software Engineering, vol. 16, no. 11, pp. 1307-1310, Nov. 1990, doi:10.1109/32.60318
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