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In this study, the performance of reliability is analyzed by applying the Logistic distribution property to the finite-fault NHPP reliability model. For this, software failure time data was used, parametric estimation was applied to the maximum likelihood estimation method (MLE), and nonlinear equations were calculated using the bisection method. As a result, in the analysis of the intensity function, the Log-Logistic model is efficient because the failure occurring rate decreases with the failure time and the mean square error (MSE) is small. In the analysis of the mean value function, all the proposed models showed a slightly underestimated value compared to the true value, but the Log-Logistic model showed the smallest error value to the true value along with the Goel-Okumoto model. As a result of evaluating the software reliability after putting the mission time in the future, the Log-Logistic model shows a higher reliability trend than the other models in which the reliability decreases with the mission time. In conclusion, we found that the Log-Logistic model is an efficient model with the best performance among the proposed models. In this study, the reliability performance of the Logistic type distribution model without the existing research case was newly analyzed, and it is expected that it can be used as a basic guideline for the software developers to search the optimal software reliability model.

A Comparative Study on the Performance Attributes of Finite Failure NHPP Software Reliability Model with Logistic Distribution Property