Yuka Minamino
Department of Social Management Engineering, Graduate School of Engineering, Tottori University, 4-101, Minami, Koyama-cho, Tottori-shi, Tottori 680-8552, Japan.

Shinji Inoue
Faculty of Informatics, Kansai University, 2-1-1 Ryozenji-cho, Takatsuki-shi, Osaka 569-1095, Japan.

Shigeru Yamada
Department of Social Management Engineering, Graduate School of Engineering, Tottori University, 4-101, Minami, Koyama-cho, Tottori-shi, Tottori 680-8552, Japan.

DOI https://doi.org/10.33889/IJMEMS.2020.5.1.005

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Abstract

Software reliability growth is observed by investing not only the testing-time but also the testing-effort in the testing-phase of software development process. If the testing-time (testing-effort) is reduced to some extent, it is possible to observe the software reliability growth by investing the amount of testing-effort (testing-time) which can compensate the insufficiency of the testing-time (testing-effort). However, most of the existing software reliability growth models (SRGMs) are constructed as univariate models and the substitutability between the testing-time and testing-effort is not considered. Additionally, it is necessary to remove many faults efficiently within the budget. In this paper, we develop bivariate Weibull type SRGMs under budget constraint based on the Cobb-Douglas type and CES (constant elasticity of substitution) type testing-time functions. Simultaneously, we evaluate the substitutability between the testing-time and testing-effort factors which are software reliability growth factors. Finally, we conduct the sensitivity analysis and show numerical examples by using actual data sets.

Keywords- Bivariate Weibull type software reliability growth model, Cobb-Douglas type testing-time function, CES (constant elasticity of substitution) type testing-time function, Budget constraint, Sensitivity analysis.

Citation

Minamino, Y., Inoue, S., & Yamada, S. (2020). Bivariate Software Reliability Growth Models under Budget Constraint for Development Management. International Journal of Mathematical, Engineering and Management Sciences, 5(1), 56-65. https://doi.org/10.33889/IJMEMS.2020.5.1.005.