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.
Highlights
Enormous testing-effort, such as CPU time, execution time, man-hour, test coverage, and executed test case, is invested in the actual testing-phase. It seems that existing univariate software reliability growth models (SRGMs) (Pham, 2000; Yamada, 2014) cannot reflect the actual testing-phase because they assume that the reliability growth depends only on the testing-time
We apply the Cobb-Douglas type and CES type production functions (Minamino et al, 2017, 2019) as testing-time functions and develop the bivariate Weibull type SRGMs based on these testing-time functions
From Eq (5), we provide the following bivariate Weibull type SRGMs based on the Cobb-Douglas type and CES type testing-time functions, respectively
Summary
Enormous testing-effort, such as CPU time, execution time, man-hour, test coverage, and executed test case, is invested in the actual testing-phase It seems that existing univariate SRGMs (Pham, 2000; Yamada, 2014) cannot reflect the actual testing-phase because they assume that the reliability growth depends only on the testing-time. We need to develop bivariate SRGMs which can consider multiple software reliability growth factors under budget constraint, and understand the quantitative substitutability between software reliability growth factors. We apply the Cobb-Douglas type and CES type production functions (Minamino et al, 2017, 2019) as testing-time functions and develop the bivariate Weibull type SRGMs based on these testing-time functions. 0 0 where H(s, u) and h(s, u) represent the mean value function and the intensity function of NHPP, respectively (Inoue and Yamada, 2008)
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