Software Effort Estimation Using Neural Network Ensemble

Department

Mechatronics Engineering

Document Type

Article

Publication Date

12-10-2015

Abstract

Accurate software effort estimation is crucial for software consulting organizations to stay competitive in their software development costs and retain customers. Artificial Neural Network (ANN) is an effective tool to obtain accurate effort estimates. In this paper, software effort estimation models using Artificial Neural Network (ANN) ensembles and regression analysis are developed based on data collected from 163 software development projects. The main emphasis of the paper is in developing an effective experimental design to achieve superior effort estimation results. In addition, we compare the software effort estimation of ANNs and multiple regression analysis. We found two interesting results. First, variables other than size (function points) are not especially helpful in predicting software development effort. Second, a properly designed ANN ensemble significantly outperforms estimation using regression analysis and can achieve better effort estimate predictions.

Journal Title

Journal of Computer Information Systems

Journal ISSN

2380-2057

Volume

53

Issue

4

First Page

49

Last Page

58

Digital Object Identifier (DOI)

10.1080/08874417.2013.11645650

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