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A software reliability model for operating environments considering exponential distribution
Journal of the Korean Data & Information Science Society 2024;35:297-307
Published online March 31, 2024;
© 2024 Korean Data and Information Science Society.

Kwang Yoon Song1 · In Hong Chang2

12Department of Computer Science and Statistics, Chosun University
Correspondence to: This study was supported by research funds from Chosun University, 2023.
1 Assistant professor, Department of Computer Science and Statistics, Chosun University, Gwangju 61452, Korea.
2 Professor, Department of Computer Science and Statistics, Chosun University, Gwangju 61452, Korea. E-mail:
Received February 8, 2024; Revised March 10, 2024; Accepted March 12, 2024.
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
The software systems used in the field environments are the same as or close to those used in the development-testing environment; base on this, existing software reliability models are applied to software testing data and then used to make predictions on the software failures and reliability in the field. However, the systems may be used in many different locations. The Weibull distribution is often used to estimate the lifespan of a product because it has the flexibility to estimate cases where the probability of failure increases, decreases, or remains constant over time. In this paper, we present a new model with consideration for theWeibull fault detection rate in operating environments considering exponential distribution, and examine the goodness-of-fit of the proposed new model and other models based on two datasets. The results show that the proposed new model fits significantly better than other models.
Keywords : Fault detection rate, non-homogeneous Poisson process, software reliability, Weibull distribution