Software reliability and quality are crucial in several fields. Related studies have focused on software reliability growth models (SRGMs). Herein, we propose a new SRGM that assumes interdependent software failures. We conduct experiments on real-world datasets to compare the goodness-of-fit of the proposed model with the results of previous nonhomogeneous Poisson process SRGMs using several evaluation criteria. In addition, we determine software reliability using Wald’s sequential probability ratio test (SPRT), which is more efficient than the classical hypothesis test (the latter requires substantially more data and time because the test is performed only after data collection is completed). The experimental results demonstrate the superiority of the proposed model and the effectiveness of the SPRT.

中文翻译：

---

具有相关故障和SPRT的软件可靠性模型

软件可靠性和质量在几个领域至关重要。相关研究集中在软件可靠性增长模型（SRGM）。在这里，我们提出了一种新的SRGM，它假定了相互依赖的软件故障。我们在现实世界的数据集上进行实验，以使用几种评估标准将拟议模型的拟合优度与先前的非均匀泊松过程SRGMs的结果进行比较。此外，我们使用Wald的顺序概率比检验（SPRT）来确定软件可靠性，它比经典的假设检验更有效（后者需要大量的数据和时间，因为只有在数据收集完成后才进行测试）。实验结果证明了所提模型的优越性和SPRT的有效性。