Abstract
We have been attempting to evaluate software quality and improve its reliability. Therefore, research on a software reliability model was part of the effort. Currently, software is used in various fields and environments; hence, one must provide quantitative confidence standards when using software. Therefore, we consider the testing coverage and uncertainty or randomness of an operating environment. In this paper, we propose a new testing coverage model based on NHPP software reliability with the uncertainty of operating environments, and we provide a sensitivity analysis to study the impact of each parameter of the proposed model. We examine the goodness-of-fit of a new testing coverage model based on NHPP software reliability and other existing models based on two datasets. The comparative results for the goodness-of-fit show that the proposed model does significantly better than the existing models. In addition, the results for the sensitivity analysis show that the parameters of the proposed model affect the mean value function.
Highlights
Software combines technologies such as artificial intelligence (AI), Internet of Things (IOT), and big data, which are important elements in the fourth industrial revolution, to create new forms of value.Software is a very important factor in the fourth industrial revolution [1]
Most non-homogeneous Poisson process (NHPP) software reliability models were developed based on the assumption that faults detected in the testing phase were removed immediately with no debugging time delay, no new faults were introduced, and software systems used in the field environments were the same as or close to those used in the development-testing environment [7,8,9,10]
We discuss a new testing coverage model based on NHPP software reliability with the uncertainty of operating environments and sensitivity analysis in order to study the impact of each parameter of the proposed model
Summary
Software combines technologies such as artificial intelligence (AI), Internet of Things (IOT), and big data, which are important elements in the fourth industrial revolution, to create new forms of value. Most NHPP software reliability models were developed based on the assumption that faults detected in the testing phase were removed immediately with no debugging time delay, no new faults were introduced, and software systems used in the field environments were the same as or close to those used in the development-testing environment [7,8,9,10]. An NHPP software reliability model considering the uncertainty of the software operating environment has been proposed [14,15,16,17,18,19]. We discuss a new testing coverage model based on NHPP software reliability with the uncertainty of operating environments and sensitivity analysis in order to study the impact of each parameter of the proposed model.
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