A defect estimation approach for sequential inspection using a modified capture-recapture model

Abstract

Defect prediction is an important process in the evaluation of software quality. To accurately predict the rate of software defects can not only facilitate software review decisions, but can also improve software quality. In this paper, we have provided a defect estimation approach, which uses defective data from sequential inspections to increase the accuracy of estimating defects. To demonstrate potential improvements, the results of our approach were compared to those of two other popular estimation approaches, the capture-recapture model and the re-inspection model. By using the proposed approach, software organizations may increase the accuracy of their defect predictions and reduce the effort of subsequent inspections.