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In this paper, a scheme for constructing software reliability growth model based on Non-Homogeneous Poisson Process is proposed. Here, we consider the software reliability growth model that incorporates with imperfect debugging, change point and testing effort. However, most researchers assume a constant detection rate per fault in deriving their software reliability models. They suppose that all faults have equal probability of being detected during the software testing process, and the rate remains constant over the intervals between fault occurrences. In reality, the fault detection rate strongly depends on the skill of test teams, program size, and software testability. Also in most realistic situations, fault repair has associated with a fault re-introduction rate due to imperfect debugging phenomenon. In this case, the fault detection rate and fault introduction rate will be changed during the software development process. Therefore, here we incorporate both generalized logistic testing-effort function, change-point parameter into software reliability modelling. The Least Square Estimation approach is used to estimate the unknown parameters of the new model. So in our new proposed model we collect software testing data from real application and utilize it to illustrate the proposed model. Experimental results show that the proposed framework to incorporate both testing-effort and change-point for Imperfect-Debugging SRGM has a fairly accurate prediction capability.