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Analyzing Effort Estimation in Multistage based FL-COCOMO II Framework using various Fuzzy Membership Functions

by Kunal Gaurav, Pooja Jha, K. S. Patnaik
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 66 - Number 6
Year of Publication: 2013
Authors: Kunal Gaurav, Pooja Jha, K. S. Patnaik
10.5120/11092-6051

Kunal Gaurav, Pooja Jha, K. S. Patnaik . Analyzing Effort Estimation in Multistage based FL-COCOMO II Framework using various Fuzzy Membership Functions. International Journal of Computer Applications. 66, 6 ( March 2013), 35-39. DOI=10.5120/11092-6051

@article{ 10.5120/11092-6051,
author = { Kunal Gaurav, Pooja Jha, K. S. Patnaik },
title = { Analyzing Effort Estimation in Multistage based FL-COCOMO II Framework using various Fuzzy Membership Functions },
journal = { International Journal of Computer Applications },
issue_date = { March 2013 },
volume = { 66 },
number = { 6 },
month = { March },
year = { 2013 },
issn = { 0975-8887 },
pages = { 35-39 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume66/number6/11092-6051/ },
doi = { 10.5120/11092-6051 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:21:41.080016+05:30
%A Kunal Gaurav
%A Pooja Jha
%A K. S. Patnaik
%T Analyzing Effort Estimation in Multistage based FL-COCOMO II Framework using various Fuzzy Membership Functions
%J International Journal of Computer Applications
%@ 0975-8887
%V 66
%N 6
%P 35-39
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Software development has always been characterized by some metrics. One of the greatest challenges for software developers lies in predicting the development effort for a software system which is based on developer abilities, size, complexity and other metrics. Several algorithmic cost estimation models such as Boehm's COCOMO, Albrecht's' Function Point Analysis, Putnam's SLIM, ESTIMACS etc. are available but every model has its own pros and cons in estimating development cost and effort. Most common reason being project data which is available in the initial stages of project is often incomplete, inconsistent, uncertain and unclear. In this paper, soft computing based technique is explored to overcome the problems of uncertainty and imprecision resulting in improved process of software development effort estimation. The paper considers a multistage software estimation approach using six key cost drivers in COCOMO II model. The selected cost drivers are the inputs to fuzzy expert systems and the effort multiplier is obtained as output.

References
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  4. Iman Attarzadeh, Siew Hock Ow, "Improving Estimation Accuracy of the COCOMO II using an Adaptive Fuzzy Logic Model". 2011 IEEE International Conference on fuzzy Systems, June 27-30, 2011, Taipei, Taiwan.
  5. B. W. Boehm, "Cost models for future software life cycle processes: COCOMO 2. 0," Annals of Software Engineering Special Volume on Software Process and Product Measurement, Science Publisher, Amsterdam, Netherlands, 1(3) , pp. 45 – 60. , 1995.
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  8. A. Lotfi Zadeh, "The future of soft computing," The 9th IFSA World Congress and 20th NAFIPS International Conference, Vancouver, Canada, pp. 217-228, 2001.
  9. A. Idri, A. Abran, and L. Kjiri, "COCOMO cost model using fuzzy logic," in Proceedings of The International Conference on Fuzzy Theory & Technology, 2000.
Index Terms

Computer Science
Information Sciences

Keywords

Software Engineering software cost estimation models COCOMO II soft computing effort estimation

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