A software project managers can execute well-prepared research tasks to utilize associated cost-effectively testing resources using software reliability growth models (SRGMs). Over the last four decades, several SRGMs are introduced to estimate reliability growth and applicable particular to software development research. So far, it seems that very few numbers of SRGMs recognize potential adjustments in test-effort consumption. In certain instances, testing-resource allocation practices may be modified with time. Thus, this study integrates the essential principle of multiple change-points with the testing-effort function in proposed models. Two benchmark datasets illustrate the efficiency and applicability of the proposed models. Normalized criteria distance is used to evaluate the models ranking based on four comparison criteria on two failure datasets. Experimental outcomes show that the proposed models offer reasonably better fault predictability compare to other models.