The number of software failures, software reliability, and failure rates can be measured and predicted by the software reliability growth model (SRGM). SRGM is developed and tested in a controlled environment where the operating environment is different. Many SRGMs have developed, assuming that the working and developing environments are the same. In this paper, we have developed a new SRGM incorporating the imperfect debugging and testing coverage function in the presence of a random environment. The proposed model’s parameters are estimated from two real data sets and compared with some existing SRGMs based on five goodness-of-fit criteria. The results show that the proposed model gives better descriptive and predictive performance than the existing model.
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A new software reliability growth model with testing coverage and uncertainty of operating environments
Published:
29 April 2023
by MDPI
in The 1st International Online Conference on Mathematics and Applications
session Mathematics and Computer Science
Abstract:
Keywords: Non-homogeneous Poisson process; Software reliability growth models; Mean value function; Testing coverage function; Random field environment.
