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Reseach Article

A Survey:A Multiple Comparisons Algorithm based Ranking and Clustering of COCOMO and Putnam�s Software Cost Estimation Models

Published on December 2014 by Chetana D. Patil, Tareek M. Pattewar
National Conference on Emerging Trends in Computer Technology
Foundation of Computer Science USA
NCETCT - Number 1
December 2014
Authors: Chetana D. Patil, Tareek M. Pattewar
32c57e91-ecf3-4666-bdb5-b8a9556003e2

Chetana D. Patil, Tareek M. Pattewar . A Survey:A Multiple Comparisons Algorithm based Ranking and Clustering of COCOMO and Putnam�s Software Cost Estimation Models. National Conference on Emerging Trends in Computer Technology. NCETCT, 1 (December 2014), 10-13.

@article{
author = { Chetana D. Patil, Tareek M. Pattewar },
title = { A Survey:A Multiple Comparisons Algorithm based Ranking and Clustering of COCOMO and Putnam�s Software Cost Estimation Models },
journal = { National Conference on Emerging Trends in Computer Technology },
issue_date = { December 2014 },
volume = { NCETCT },
number = { 1 },
month = { December },
year = { 2014 },
issn = 0975-8887,
pages = { 10-13 },
numpages = 4,
url = { /proceedings/ncetct/number1/19078-4007/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 National Conference on Emerging Trends in Computer Technology
%A Chetana D. Patil
%A Tareek M. Pattewar
%T A Survey:A Multiple Comparisons Algorithm based Ranking and Clustering of COCOMO and Putnam�s Software Cost Estimation Models
%J National Conference on Emerging Trends in Computer Technology
%@ 0975-8887
%V NCETCT
%N 1
%P 10-13
%D 2014
%I International Journal of Computer Applications
Abstract

Software project can be completely predicting the most realistic effort using Software Cost Estimation. There are variety of methods and models trying to improve the estimation procedure of Software project development and application. From the variety of methods emerged the need for comparisons to determine the best model. Here, we propose a statistical framework based on a multiple comparisons algorithm in order to rank several cost estimation models, identifying those which have significant differences in accuracy, and clustering them in non overlapping groups. The proposed framework is applied in a large scale setup of comparing prediction models over datasets.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Project Estimation Effort Estimation Cost Models.