Software Cost Estimation using Enhanced Artificial Bee Colony Algorithm

Abstract

Cost estimation is very important in software development progress so that resource and time planning can be successfully performed. Accurate estimation of cost is directly related to the decision making mechanism in the software development process. The underestimated cost might lead to fewer resources and budget problems; in contrast, customer satisfaction might diminish due to waste of resources. This study represents an estimation model for the effort required for the development of software projects using a variant of artificial bee colony (ABC) algorithm. The proposed model is performed over a dataset consisting of NASA software projects and has better performance than the previous studies.