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A Software Reliability Model Considering a Scale Parameter of the Uncertainty and a New Criterion

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  • Kwang Yoon Song

    (Department of Computer Science and Statistics, Chosun University, Gwangju 61452, Republic of Korea
    Institute of Well-Aging Medicare & Chosun University LAMP Center, Chosun University, Gwangju 61452, Republic of Korea)

  • Youn Su Kim

    (Department of Computer Science and Statistics, Chosun University, Gwangju 61452, Republic of Korea)

  • Hoang Pham

    (Department of Industrial and Systems Engineering, Rutgers University, Piscataway, NJ 08855-8018, USA)

  • In Hong Chang

    (Department of Computer Science and Statistics, Chosun University, Gwangju 61452, Republic of Korea)

Abstract

It is becoming increasingly common for software to operate in various environments. However, even if the software performs well in the test phase, uncertain operating environments may cause new software failures. Traditional proposed software reliability models under uncertain operating environments suffer from the problem of being well-suited to special cases due to the large number of assumptions involved. To improve these problems, this study proposes a new software reliability model that assumes an uncertain operating environment. The new software reliability model is a model that minimizes assumptions and minimizes the number of parameters that make up the model, so that the model can be applied to general situations better than the traditional proposed software reliability models. In addition, various criteria based on the difference between the predicted and estimated values have been used in the past to demonstrate the superiority of the software reliability models. Also, we propose a new multi-criteria decision method that can simultaneously consider multiple goodness-of-fit criteria. The multi-criteria decision method using ranking is useful for comprehensive evaluation because it does not rely on individual criteria alone by ranking and weighting multiple criteria for the model. Based on this, 21 existing models are compared with the proposed model using two datasets, and the proposed model is found to be superior for both datasets using 15 criteria and the multi-criteria decision method using ranking.

Suggested Citation

  • Kwang Yoon Song & Youn Su Kim & Hoang Pham & In Hong Chang, 2024. "A Software Reliability Model Considering a Scale Parameter of the Uncertainty and a New Criterion," Mathematics, MDPI, vol. 12(11), pages 1-14, May.
    • Handle: RePEc:gam:jmathe:v:12:y:2024:i:11:p:1641-:d:1400579
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    References listed on IDEAS

    as
    1. Lujia Wang & Qingpei Hu & Jian Liu, 2016. "Software reliability growth modeling and analysis with dual fault detection and correction processes," IISE Transactions, Taylor & Francis Journals, vol. 48(4), pages 359-370, April.
    2. Hoang Pham, 2006. "System Software Reliability," Springer Series in Reliability Engineering, Springer, number 978-1-84628-295-9, June.
    3. Armstrong, J. Scott & Collopy, Fred, 1992. "Error measures for generalizing about forecasting methods: Empirical comparisons," International Journal of Forecasting, Elsevier, vol. 8(1), pages 69-80, June.
    4. Dahye Lee & Inhong Chang & Hoang Pham, 2023. "Study of a New Software Reliability Growth Model under Uncertain Operating Environments and Dependent Failures," Mathematics, MDPI, vol. 11(18), pages 1-17, September.
    Full references (including those not matched with items on IDEAS)

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