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Proposing Effort Estimation of COCOMO II through Perceptron Learning Rule

by Saoud Sarwar, Monika Gupta
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 70 - Number 1
Year of Publication: 2013
Authors: Saoud Sarwar, Monika Gupta
10.5120/11929-7707

Saoud Sarwar, Monika Gupta . Proposing Effort Estimation of COCOMO II through Perceptron Learning Rule. International Journal of Computer Applications. 70, 1 ( May 2013), 29-32. DOI=10.5120/11929-7707

@article{ 10.5120/11929-7707,
author = { Saoud Sarwar, Monika Gupta },
title = { Proposing Effort Estimation of COCOMO II through Perceptron Learning Rule },
journal = { International Journal of Computer Applications },
issue_date = { May 2013 },
volume = { 70 },
number = { 1 },
month = { May },
year = { 2013 },
issn = { 0975-8887 },
pages = { 29-32 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume70/number1/11929-7707/ },
doi = { 10.5120/11929-7707 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:31:44.487989+05:30
%A Saoud Sarwar
%A Monika Gupta
%T Proposing Effort Estimation of COCOMO II through Perceptron Learning Rule
%J International Journal of Computer Applications
%@ 0975-8887
%V 70
%N 1
%P 29-32
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The software cost estimation is now one of centre of attention for computer software industries. As software industry runs many projects simultaneously they have to prioritize different processes based on time, cost, and number of staff, sequentially. With the increasing complexity of software, the cost of the software development is also increasing. So it is required to rely on the effective techniques for estimating software costs. Accurate cost estimation is needed because it can help to prioritize and classify development projects. In this paper, the most popular software cost estimation model, COCOMO II (post architecture model of COCOMO), is discussed. The estimation of COCOMO II is enhanced through neural network. The network is trained trough perceptron learning rule. The company's previous projects dataset of estimation and actual cost can be used to train the network. The cost estimation result of COCOMO II is compared with trained network.

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Index Terms

Computer Science
Information Sciences

Keywords

Software cost estimation neural network COCOMO II perceptron learning

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