The above equations are essentially same as the nonhomogeneous Poisson process (NHPP) based software reliability growth model (SRGM
Instead of proposing a brand new SRGM
for the sake of it, we propose building on the past good work done by researchers [1, 19].
A mean value function (MVF) m(t) is used to express the expected number of accumulated faults by time t, and the general form of the SRGM
based on a nonhomogeneous Poisson process (NHPP) that has Poisson distribution with mean m(t) is described as
In this paper author proposed an imperfect debugging SRGM
during testing and resource allocation is done based on optimizing the effort and reliability.
They have considered two cases of SRGMs
and used average gain as a criterion.
Numerous Software Reliability Growth Models (SRGMs
) have been developed [2-5], which generally agree that the fault debugging process is a Nonhomogeneous Poisson Process (NHPP) under various diverging assumptions: perfect and imperfect debugging phenomenon [6, 7].
Comparison of predictive performance of the SRGM
with other models is given in the next section.
Specifically, for an NHPP-based SRGM
, it is assumed that N(t) follows a Poisson distribution with a mean value function m(t).