Nonhomogeneous Poisson process software reliability model incorporating initial fault diversification and dependent failures

Software with increasingly complex structures plays a vital role in our lives, and our dependence on it continues to grow. As software failures and defects can cause serious problems, it is critical to measure and improve software reliability. Previous software reliability models were derived under the assumption that no failures exist at the initial point in time. However, this study developed a model that predicts software failures by setting the observation point to the initial stage and assuming that a certain number of defects already exist. Various possibilities for this have been proposed. These possibilities can arise in increasingly complex and diverse software. The proposed model assumes that software failures are not only independent it also assumed that software failures occur in a dependent manner. To demonstrate the superiority of the proposed model, we compared it with 15 traditional models across three datasets using nine criteria. The results confirmed the excellence of the proposed model by demonstrating that it achieved the best performance across all datasets. The results of this study contribute to enhancing software reliability by enabling investigation into what causes problems at the beginning of software development and creating software reliability models that are applicable in the real-world.