An alternative reliability evaluation of non‐homogeneous Poisson process models for software reliability

Abstract

Non‐homogeneous Poisson process (NHPP) models, as the stochastic models frequently employed in reliability engineering, have been successfully used in the reliability study of software systems. The software reliability based on NHPP models was proposed by Goel and Okumoto. In general, the software reliability will increase along with the correction of the software errors. This idea gives rise to a hypothesis: extending the time on the software reliability test could result in obtaining a higher reliability. Nevertheless, the scheme was found to be discrepant for some NHPP models, which are utilized in the analysis. As this often occurs in practice, the reliability outcome could differ from its appropriate estimation when the test procedures are intentionally terminated prior to the end of the required testing time span. An “above average software reliability” is proposed in this paper to accomplish the inconsistency. Under the investigation of “average software reliability”, a higher software reliability can be achieved as long as the testing time increases. Also, in this paper, an optimal software release policy is proposed to explore the issue of compromising the expenses on software development and software reliability improvement.

Citation

Chang, Y. (2000), "An alternative reliability evaluation of non‐homogeneous Poisson process models for software reliability", International Journal of Quality & Reliability Management, Vol. 17 No. 7, pp. 800-811. https://doi.org/10.1108/02656710010336352