Improving effort estimation of software products by augmenting class point approach with regression analysis

Article type: Research Article

Authors: Sahoo, Pulak^{a; *} | Chaudhury, Pamela^a | Mohanty, J.R.^b

Affiliations: [a] Department of Computer Science Engineering, Silicon Institute of Technology, India | [b] School of Computer Engineering, KIIT Deemed to be University, India

Correspondence: [*] Corresponding author: Pulak Sahoo, Department of Computer Science Engineering, Silicon Institute of Technology, India. E-mail: pulak.sahoo@silicon.ac.in.

Abstract: Software products are essential parts of many organizations on-going business up to a large extent. The main factors contributing to the successful delivery of a software product are its timely completion within the allocated budget and its quality compliance. Customer goodwill and profitability are very important for a software organization’s continued business. A large proportion of software products are delivered late or go over-budget causing significant inconvenience to the customers. This work proposes an accurate development effort estimation approach for software products. The Class Point (CP) approach with regression analysis method has been used for estimation of the development effort. This work uses a two step estimation approach. In the first step, an enhanced CP approach is used to evaluate the development effort of the system. In the second step, regression analysis models are utilized to refine the estimated effort accuracy. The results derived by applying the proposed two step approach confirmed the validity and the accuracy of this approach. It was observed that the SVR with RBF kernel is providing the best accuracy compared to other approaches.

Keywords: Class model, CP approach, regression analysis, SVM, SVR, ANN, UCP

DOI: 10.3233/IDT-210110

Journal: Intelligent Decision Technologies, vol. 16, no. 2, pp. 357-367, 2022