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Reseach Article

Automation of Software Cost Estimation using Neural Network Technique

by Gaurav Kumar, Pradeep Kumar Bhatia
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 98 - Number 20
Year of Publication: 2014
Authors: Gaurav Kumar, Pradeep Kumar Bhatia
10.5120/17297-7709

Gaurav Kumar, Pradeep Kumar Bhatia . Automation of Software Cost Estimation using Neural Network Technique. International Journal of Computer Applications. 98, 20 ( July 2014), 11-17. DOI=10.5120/17297-7709

@article{ 10.5120/17297-7709,
author = { Gaurav Kumar, Pradeep Kumar Bhatia },
title = { Automation of Software Cost Estimation using Neural Network Technique },
journal = { International Journal of Computer Applications },
issue_date = { July 2014 },
volume = { 98 },
number = { 20 },
month = { July },
year = { 2014 },
issn = { 0975-8887 },
pages = { 11-17 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume98/number20/17297-7709/ },
doi = { 10.5120/17297-7709 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:26:41.362872+05:30
%A Gaurav Kumar
%A Pradeep Kumar Bhatia
%T Automation of Software Cost Estimation using Neural Network Technique
%J International Journal of Computer Applications
%@ 0975-8887
%V 98
%N 20
%P 11-17
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Software cost estimation is one of the most challenging tasks in software engineering. Over the past years the estimators have used parametric cost estimation models to establish software cost, however the challenges to accurate cost estimation keep evolving with the advancing technology. A detailed review of various cost estimation methods developed so far is presented in this paper. Planned effort and actual effort has been comparison in detail through applying on NASA projects. This paper uses Back-Propagation neural networks for software cost estimation. A model based on Neural Network has been proposed that takes KLOC of the project as input, uses COCOMO model parameters and gives effort as output. Artificial Neural Network represents a complex set of relationship between the effort and the cost drivers and is a potential tool for estimation. The proposed model automates the software cost estimation task and helps project manager to provide fast and realistic estimate for the project effort and development time that in turn gives software cost.

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Index Terms

Computer Science
Information Sciences

Keywords

Back Propagation Neural Network COCOMO Model Software Cost Estimation.