A software reliability growth model with two types of learning and a negligence factor

Reliability attribute of dynamic software systems is a key to the normal operational behavior of such systems. Although the acquisition of perfect(cent percent) level of reliability for software may be practically very difficult but achieving near-perfect reliability growth levels is very much possible using reliability engineering study. Many SRGMs have been proposed including some based on Non-Homogeneous Poisson Process (NHPP). The realistic characteristics about human learning and experiential gains of new skills for better detection and correction of faults on software are being incorporated in such models. This paper incorporates two types of learning effects and a negligence factor into the SRGM with learning effect proposed by Chiu, Huang and Lee, taking advantage of the improvement proposed by Chiu, in terms of introduction of a negligent factor, in Chiu, Huang and Lee SRGM. In this paper, we simultaneously incorporate learning effect that exists in two forms: one is autonomous learning and the other is acquired learning as well as a negligence factor. The resultant model equations are subjected to the statistical analysis and the results are satisfactory.