Abstract

A number of NHPP based SRGM have been discussed in the previous chapters. These models treat the event of software fault detection/removal in the testing and operational phase as a counting process in discrete state space. If the size of software system is large, the number of software faults detected during the testing phase becomes large, and the change in the number of faults, which are detected and removed through debugging activities, becomes sufficiently small compared with the initial fault content at the beginning of the testing phase. Therefore, in such a situation, the software fault detection process can be well described by a stochastic process with a continuous state space. This chapter focuses on the development of stochastic differential equation based software reliability growth models to describe the stochastic process with continuous state space. Before developing any model we introduce the readers with the theoretical and mathematical background of stochastic differential equations.

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