A novel method for software effort estimation: Estimating with boundaries

Abstract

Software effort estimation is a crucial phase in software project management. Accuracy of estimation directly affects project success or failure. Managers try to estimate proper effort resources and this is a challenging issue for management. Having a set of tools and methodologies, estimation process can be made better. COCOMO is one of the most used model which has a parametric form. Also, artificial neural networks (ANN) are combined with COCOMO and these methods increased overall performance. However, effort estimation process generally produces one output; estimation value. It is a well-known issue that a project manager must keep in the mind that any estimation must have some upper and lower limits, boundaries. In this paper, a novel method, combining COCOMO used ANN with K-Means is used to estimate effort and possible boundaries. ANN output is used as input to K-Means sets and proper set value is calculated, including possible lower and upper effort estimation value. Experimental results are shown that proposed method has acceptable results over ANN and COCOMO.