Are Infinite-Failure NHPP-Based Software Reliability Models Useful?

In the literature, infinite-failure software reliability models (SRMs), such as Musa-Okumoto SRM (1984), have been demonstrated to be effective in quantitatively characterizing testing processes and assessing reliability. This paper primarily focuses on (type-II) non-homogeneous Poisson process (NHPP)-based SRMs evaluates performances of these comprehensively by comparing with existing finite-failure (type-I) NHPP-based SRMs. more specific terms, describe fault-detection time distribution, we postulate 11 representative probability distribution functions that can categorized into generalized exponential family extreme-value family. Then, compare goodness-of-fit predictive associated type-I type-II numerical experiments, analyze fault-count data, collected from 16 actual development projects, which are commonly known industry time-domain data time-interval (group data). The maximum likelihood method is utilized estimate model parameters both a comparison type-II, it shown could exhibit better performance than SRMs, especially early stage testing.