Abstract

Objectives: In this study, the comparative problem of reliability model by means of the Weibull extension distribution and power law pattern that completed out productivity of the software trustworthiness was proposed Methods/Statistical Analysis: In addition, the model choice founded on the mean rectangular error and measurement of fortitude for the proficient model were offered. Examination of the failure period influenced by the Weibull extension distribution and power law model was working for the recommending reliability model. The Laplace tendency test was offered for insurance about the failure period. Findings: In the deviation for the between of the predicted values with the actual observations, the shaping parameter from Weibull extension model regard as the best model and in terms of the prognostic power of the variance for the between the forecast values, the shaping parameter from Weibull extension model can be the efficacy model. From judgment of reliability, the situation of the reliability for the conditional work time shows that the case of the shaping parameter from Weibull extension model than shaping parameter from Weibull extension model, the shaping parameter from Weibull extension model, and power low model was revealed high reliability. Namely, the property of the reliability was reflected to subtle about the mission time. The resulting decisions were gained. In terms of deviation for between of the predicted values with the actual observations, the higher shaping model of Weibull extension model regard as the best model. The result of mean value functions has the tendency of non-decreasing form. The result of an intensity functions has the tendency non-increasing form. The case of the higher shaping model of Weibull extension model was judged more reliable model in reliability ground. Improvements/Applications: The software testing for the debugging to reduce cost in terms of the reliability from software is essential problem. From a research, the software developers must be considered for the growth model by the prior knowledge of the software to identify failure modes which can be able to help.

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