Software defects estimation using metrics of early phases of software development life cycle

Abstract

An estimation of software defects can be obtained in the later phase of software testing. However, with the aim of cost-effectiveness and timely management of resources, the software defects estimation in the early phases of software development life cycle (SDLC) is one of the major research areas. In this paper, a software defect estimation model is proposed using Bayesian belief network (BBN) and reliability relevant metrics of early phases of SDLC (e.g., requirement analysis, design and coding phases). The causal relationship of software metrics is modeled using BBN. The qualitative value of software metrics and expert assessment of software defects is used for developing the proposed model. The defects estimation accuracy of the proposed model is examined using qualitative data set of ten real software projects. The defects estimation results are compared with the existing model and found more accurate.