Notification: Our email services are now fully restored after a brief, temporary outage caused by a denial-of-service (DoS) attack. If you sent an email on Dec 6 and haven't received a response, please resend your email.
CFP last date
20 December 2024
Reseach Article

A Bee Colony Optimization Algorithm Approach for Software Cost Estimation

by Zahra Ashegi Dizaji, Reza Ahmadi, Hojjat Gholizadeh, Farhad Soleimanian Gharehchopogh
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 104 - Number 12
Year of Publication: 2014
Authors: Zahra Ashegi Dizaji, Reza Ahmadi, Hojjat Gholizadeh, Farhad Soleimanian Gharehchopogh
10.5120/18258-9444

Zahra Ashegi Dizaji, Reza Ahmadi, Hojjat Gholizadeh, Farhad Soleimanian Gharehchopogh . A Bee Colony Optimization Algorithm Approach for Software Cost Estimation. International Journal of Computer Applications. 104, 12 ( October 2014), 41-44. DOI=10.5120/18258-9444

@article{ 10.5120/18258-9444,
author = { Zahra Ashegi Dizaji, Reza Ahmadi, Hojjat Gholizadeh, Farhad Soleimanian Gharehchopogh },
title = { A Bee Colony Optimization Algorithm Approach for Software Cost Estimation },
journal = { International Journal of Computer Applications },
issue_date = { October 2014 },
volume = { 104 },
number = { 12 },
month = { October },
year = { 2014 },
issn = { 0975-8887 },
pages = { 41-44 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume104/number12/18258-9444/ },
doi = { 10.5120/18258-9444 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:36:01.172962+05:30
%A Zahra Ashegi Dizaji
%A Reza Ahmadi
%A Hojjat Gholizadeh
%A Farhad Soleimanian Gharehchopogh
%T A Bee Colony Optimization Algorithm Approach for Software Cost Estimation
%J International Journal of Computer Applications
%@ 0975-8887
%V 104
%N 12
%P 41-44
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The Software Cost Estimation (SCE) is one of the most important stages of the production cycle of a system. Therefore, the managers need to accurately determine the requirements of the project to have accurate estimations. But given the fact that the SCE is done at the beginning of the system development, it can be problematic due to lack of accurate information about the project. To solve this problem, researchers have proposed several methods to estimate the cost of software projects but haven't been successful in estimating the costs with 100% accuracy. In this paper, we intend to improve the accuracy of the cost estimation by using Bee Colony Optimization algorithm. It should be mentioned that the proposed method is compared with the intermediate COCOMO. The results indicate that the proposed method have reduced the mean absolute relative error to 0. 1619.

References
  1. J. Caper, "Estimating Software Costs (English) 2nd Edition", Tata McGraw - Hill Education, 2007.
  2. Z. A. Khalifelu, F. S. Gharehchopogh, "A New Approach in Software Cost Estimation Using Regression Based Classifier ", AWER Procedia Information Technology & Computer Science, Vol:2, pp. 252-256, December 2012.
  3. H. Park, S. Baek, "An Empirical Validation of a Neural Network Model for Software Effort Estimation", Expert Systems with Applications, Vol. 35, pp. 929-937, 2008.
  4. Z. A. Khalifelu, F. S. Gharehchopogh, "Comparison and Evaluation Data Mining Techniques with Algorithmic Models in Software Cost Estimation", Elsevier Press, Procedia-Technology Journal, ISSN: 2212-0173, Vol: 1, pp. 65-71, 2012.
  5. L. H. Putnam, "A general empirical solution to the macro software sizing and estimating problem", IEEE Trans. Soft. Eng, pp. 345-361, 1978.
  6. B. W. Boehm, "Software engineering economics", Englewood Cliffs, NJ: Prentice-Hall, 1981.
  7. B. Boehm, W. Royce , "Ada COCOMO and the Ada Process Model", Proceedings, Fifth COCOMO Users Group Meeting, Software Engineering Institute, Pittsburgh, , 1989
  8. B. Clark, E. Horowitz, R. Madachy, R. Shelby, Ch. Westland, "The COCOMO® 2. 0 Software Cost Estimation Model", International Society of Parametric Analysts, 1995.
  9. A. F. Sheta, "Estimation of the COCOMO Model Parameters Using Genetic Algorithms for NASA Software Projects", Journal of Computer Science, vol. 2, pp. 118-123, 2006
  10. T. R. Benala, S. Dehuri, S. Ch. Satapathy, S. Madhurakshara, "Genetic Algorithm for Optimizing Functional Link Artificial Neural Network Based Software Cost Estimation", Springer-Verlag Berlin Heidelberg , pp: 75–82,2012.
  11. Z. A. Dizaji , K. Khalilpour, "Particle Swarm Optimization Ana Chaos Theory Based Approach for Software Cost Estimation", International Journal of Academic Research, Vol. 6, No. 3,pp. 130-135, 2014
  12. F. S. Gharehchopogh, L. Ebrahimi, I. Maleki and S. J. Gourabi, "A Novel PSO based Approach with Hybrid of Fuzzy C-Means and Learning Automata in Software Cost Estimation", Indian Journal of Science and Technology, Vol 7(6), pp. 795–803, 2014
  13. F. S. Gharehchopogh, "Neural Networks Application in Software Cost Estimation: A Case Study", 2011 International Symposium on Innovations in Intelligent Systems and Applications (INISTA 2011), pp. 69-73, IEEE, Istanbul, Turkey, 15-18 June 2011.
  14. T. Menzies, D. Port, Z. Chen, J. Hihn, Sh. Stukes, "Validation Methods for Calibrating Software Effort Models", International Conference on Software Engineering, St Louis Missouri, USA, 15-21 May, 2005.
  15. P. Lucic, D . Teodorovic, "Computing with bees: attacking complex transportation engineering problems" , International Journal on Artificial Intelligence Tools , vol:12, pp:375–94 , 2003
  16. M . Nikolic, D. Teodorovic, "Empirical study of the Bee Colony Optimization (BCO) algorithm", Expert Systems with Applications 40, pp: 4609–4620, , 2013
Index Terms

Computer Science
Information Sciences

Keywords

Software Cost Estimation bee colony optimization algorithm intermediate COCOMO.