Non-Homogeneous Poisson Process Software Reliability Model and Multi-Criteria Decision for Operating Environment Uncertainty and Dependent Faults

The importance of software has increased significantly over time, and software failures have become a critical concern. As software systems have diversified in functionality, their structure has become more complex, and the types of failures that can occur in software have also diversified, stimulating the development of diverse software reliability models. In this study, we make certain assumptions regarding complex software, thereby proposing a new type of non-homogeneous Poisson process (NHPP) software reliability model that considers both dependent cases of software failure and cases that originate from the differences between the developed and actual operating environments. In addition, a new multi-criteria decision method (MCDM) that uses the maximum value for a comprehensive evaluation was proposed to demonstrate the effectiveness of the developed model. This improves the judgment of model excellence through multiple criteria and is suitable for multiple interpretations. To demonstrate the effectiveness of the proposed model, 15 NHPP software reliability models were compared using 13 evaluation criteria and three MCDM methods across two datasets. The results showed that one dataset performed well for all the criteria, whereas the other dataset performed well for the newly proposed a multi-criteria decision method using maximum (MCDMM). The sensitivity analysis also showed a change in the mean value function with a change in the parameters. These results demonstrate that an extended structure for complex software can lead to improved software reliability.