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Software reliability models (SRMs) are very important for estimating and predicting software
reliability in the testing/debugging phase. The contributions of this paper are as follows. First, a
historical review of the Gompertz SRM is given. Based on several software failure data, the
parameters of the Gompertz software reliability model are estimated using two estimation
methods, the traditional maximum likelihood and the least square. The methods of estimation are
evaluated using the MSE and Rsquared criteria. The results show that the least square
estimation is an attractive method in term of predictive performance and can be used when the
maximum likelihood method fails to give good prediction results.
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