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An Analysis of Software Reliability Estimation Using Fuzzy Logic Function With Cocomo Ii Model

Ritu 1 , Kamna Solanki2 , Amita Dhankhar3 , Sandeep Dalal4

Section:Research Paper, Product Type: Journal Paper
Volume-7 , Issue-6 , Page no. 623-626, Jun-2019

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v7i6.623626

Online published on Jun 30, 2019

Copyright © Ritu, Kamna Solanki, Amita Dhankhar, Sandeep Dalal . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: Ritu, Kamna Solanki, Amita Dhankhar, Sandeep Dalal, “An Analysis of Software Reliability Estimation Using Fuzzy Logic Function With Cocomo Ii Model,” International Journal of Computer Sciences and Engineering, Vol.7, Issue.6, pp.623-626, 2019.

MLA Style Citation: Ritu, Kamna Solanki, Amita Dhankhar, Sandeep Dalal "An Analysis of Software Reliability Estimation Using Fuzzy Logic Function With Cocomo Ii Model." International Journal of Computer Sciences and Engineering 7.6 (2019): 623-626.

APA Style Citation: Ritu, Kamna Solanki, Amita Dhankhar, Sandeep Dalal, (2019). An Analysis of Software Reliability Estimation Using Fuzzy Logic Function With Cocomo Ii Model. International Journal of Computer Sciences and Engineering, 7(6), 623-626.

BibTex Style Citation:
@article{Solanki_2019,
author = {Ritu, Kamna Solanki, Amita Dhankhar, Sandeep Dalal},
title = {An Analysis of Software Reliability Estimation Using Fuzzy Logic Function With Cocomo Ii Model},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {6 2019},
volume = {7},
Issue = {6},
month = {6},
year = {2019},
issn = {2347-2693},
pages = {623-626},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=4603},
doi = {https://doi.org/10.26438/ijcse/v7i6.623626}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v7i6.623626}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=4603
TI - An Analysis of Software Reliability Estimation Using Fuzzy Logic Function With Cocomo Ii Model
T2 - International Journal of Computer Sciences and Engineering
AU - Ritu, Kamna Solanki, Amita Dhankhar, Sandeep Dalal
PY - 2019
DA - 2019/06/30
PB - IJCSE, Indore, INDIA
SP - 623-626
IS - 6
VL - 7
SN - 2347-2693
ER -

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Abstract

Software cost estimation SCE is directly related to quality of software. The paper presents a hybrid approach that is an amalgamation of algorithmic (parametric models) and non-algorithmic (expert estimation) models. Algorithmic model uses COCOMO II while non algorithmic utilizes Neuro-Fuzzy technique that can be further used to estimate accuracy in irregular functions. For generalization of the model, Neuro-fuzzy membership functions have been used and simulated using mathematical tool MATLAB. The main objective of this research is to investigate the role of fuzzy logic technique in improving the effort estimation accuracy using COCOMO II by characterizing inputs parameters using Gaussian, trapezoidal and triangular membership functions and comparing their results. NASA (93) dataset is used in the evaluation of the proposed Fuzzy Logic COCOMO II. After analyzing the results it had been found that effort estimation using Gaussian member function yields better results for maximum criterions when compared with the other methods

Key-Words / Index Term

COCOMO II, Estimation, Neuro-Fuzzy, Reliability, Membership function, Soft Computing, Software Effort Estimation, Gaussian Membership Function

References

[1] J. Gaffney (Jnr) and E. John, "Software Function Source Lines of Code and Development Effort Prediction: A Software Science Validation", IEEE Transactions on Software Engineering, vol. 9, issue-6, pp. 639-647, 1983.
[2] R. Rombach and H. Dieter, "The TAME Project: Towards Improvements Oriented Software Environments”, IEEE Transactions on Software Engineering, vol. 14, issue-6, pp. 758-773, 1988.
[3] Symons and Charles R., "Function Point Analysis: Difficulties and Improvements", IEEE Transactions on Software Engineering, vol. 14, issue-1, pp. 2-10, 1988.
[4] Vahid, Khatibi, Dayang and N. A. Jawawi, “Software Cost Estimation Methods: A Review”, Journal of Emerging Trends in Computing and Information Sciences, vol. 2, issue-1, pp. 21-29, 2010.
[5] Randy K. Smith, Joanne E. Hale and Allen S. Parrish, “An Empirical Study Using Task Assignment Patterns to Improve the Accuracy of Software Effort Estimation”, IEEE Transactions on Software Engineering, vol. 27, issue-3, pp. 264-267, 2011.
[6] Shubhangi Mahesh Potdar, Manimala Puri and Mahesh P. Potdar, “Literature Survey on Algorithmic Methods for Software Development Cost Estimation”, International Journal of Computer Technology & Applications, vol. 5, issue-1, ISSN: 2229-6093, pp. 183-188, 2014.
[7] Chemuturi K.M, “Software Estimation Best Practices, Tools and Techniques: A Complete Guide for Software Project Estimators”, J. Ross Publishing Inc, pp. 49-65, 2009.
[8] Magne Jorgensen, “Practical Guidelines for Expert-Judgment-Based Software Effort Estimation”, Simula Research Laboratory, IEEE, pp.57-63, 2005.
[9] Vahid Khatibi, Dayang N. A. Jawawi “Software Cost Estimation Methods: Review”, Journal of Emerging Trends in Computing and Information Sciences, vol. 2, issue- 1, 2011.
[10] Matson J., Barrett B. and Mellichamp J., “Software Development Cost Estimation Using Function Points”, IEEE Transactions on Software Engineering, vol. 20, issue-4, pp. 275-287,1994.
[11] M. Shepperd and C. Schofield, “Estimating Software Project Effort Using Analogies”, IEEE Transaction on software engineering, vol. 23, pp. 736-743, 1997.
[12] C. S. Reddy and K. Raju, “A Concise Neural Network Model for Estimating Software Effort”, International Journal of Recent Trends in Engineering, vol. 1, pp. 188-193, 2009.
[13] F. J. Heemstra, “Software cost estimation, Information and Software Technology”, vol. 34, pp. 627-639, 1992.
[14] L. Lederer and J. Prasad, “Causes of Inaccurate Software Development Cost Estimates”, Journal of Systems and Software, vol. 31, pp. 125-134, 1995.
[15] Chetan Nagar, “Software efforts estimation using Use Case Point approach by increasing technical complexity and experience factors”, International Journal of Computer Sciences and Engineering, ISSN:0975-3397, vol.3, issue-10, pp. 3337-3345, 2011.
[16] N. Karunanitthi, D. Whitley and Y.K Malaiya, “Using Neural Network in Reliability Prediction”, IEEE Transaction on software engineering, vol. 9, issue-4, pp. 53-59, 1992.
[17] T. J. Mc Cabe, “A complexity measure”, IEEE Transaction on software engineering vol. 2, issue-4, pp. 308-320, 1976.
[18] A.J. Albrecht and J. E. Gaffney, “Software function, source lines of code and development effort prediction: A software science validation”, IEEE Transaction on Software Engineering, vol. 9, issue-6, pp. 639-647, 1983.