Software Reliability Growth Model Based on Half Logistic Distribution

A non-homogeneous Poisson process with its mean value function generated by the cumulative distribution function of half logistic distribution is considered. It is modeled to assess the failure phenomenon of developed software. When the failure data are in the form of the number of failures in a given interval of time, the model parameters are estimated by the maximum likelihood method. The performance of the model is compared with two standard models [Goel, A. L., and Okumoto. K., “A Time Dependent Error Detection Rate Model for Software Reliability and Other Performance Measures,” IEEE Trans. Reliab., Vol. 28(3), 1979, pp. 206–211; Yamada , “S-Shaped Reliability Growth Modeling for Software Error Detection,” IEEE Trans. Reliab., Vol. 32(5), 1983, pp. 475–484] using two data sets. The release time of the software subject to a minimum expected cost is worked out and exemplified through illustrations.