Abstract
This paper presents a generalized logistic software reliability growth model that integrates time-dependent fault detection rate and imperfect removing rate per fault. We also derive a time-dependent logistic growth model and compare descriptive and predictive ability of a set of “classical” NHPP reliability models with the one we developed based on a software failure data set. The results show that inclusion of both time-dependent imperfect removing and fault-detection rates into a logistic growth function may be worth the extra model complexity and the increased number of parameters required for a better relative fit based on several selection criteria.
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Pham, H. A Generalized Logistic Software Reliability Growth Model. OPSEARCH 42, 322–331 (2005). https://doi.org/10.1007/BF03398744
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DOI: https://doi.org/10.1007/BF03398744