Estimation of software defects fix effort using neural networks

Abstract

Software defects fix effort is an important software development process metric that plays a critical role in software quality assurance. People usually like to apply parametric effort estimation techniques using historical lines of code and function points data to estimate effort of defects fixes. However, these techniques are neither efficient nor effective for a new different kind of project's fixing defects when code will be written within the context of a different project or organization. In this paper, we present a solution for estimating software defect fix effort using self-organizing neural networks.