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Applying Neuro-fuzzy Approach to build the Reusability Assessment Framework across Software Component Releases - An Empirical Evaluation

by Vijai Kumar, Rajesh Kumar, Arun Sharma
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 70 - Number 15
Year of Publication: 2013
Authors: Vijai Kumar, Rajesh Kumar, Arun Sharma
10.5120/12041-8047

Vijai Kumar, Rajesh Kumar, Arun Sharma . Applying Neuro-fuzzy Approach to build the Reusability Assessment Framework across Software Component Releases - An Empirical Evaluation. International Journal of Computer Applications. 70, 15 ( May 2013), 41-47. DOI=10.5120/12041-8047

@article{ 10.5120/12041-8047,
author = { Vijai Kumar, Rajesh Kumar, Arun Sharma },
title = { Applying Neuro-fuzzy Approach to build the Reusability Assessment Framework across Software Component Releases - An Empirical Evaluation },
journal = { International Journal of Computer Applications },
issue_date = { May 2013 },
volume = { 70 },
number = { 15 },
month = { May },
year = { 2013 },
issn = { 0975-8887 },
pages = { 41-47 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume70/number15/12041-8047/ },
doi = { 10.5120/12041-8047 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:32:58.367863+05:30
%A Vijai Kumar
%A Rajesh Kumar
%A Arun Sharma
%T Applying Neuro-fuzzy Approach to build the Reusability Assessment Framework across Software Component Releases - An Empirical Evaluation
%J International Journal of Computer Applications
%@ 0975-8887
%V 70
%N 15
%P 41-47
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

To reduce the development time, software reuse methodologies have been used across the software industries. Software reuse is a method to assemble the software components from the existing software. To take advantage of reuse concept, it is necessary to measure the software reusability of the existing components. Although there are various statistical methods exists to find the reusability of the components but soft computing has not been explored for component reusability. The aim of this paper is to formulate, build, evaluate, validate and compare neuro-fuzzy approach in prediction of software reusability of software components during the subsequent releases of a software development process. In this research we have applied neuro-fuzzy approaches which yield to better accuracy than the standalone fuzzy and neural approach. We have taken four main dependent factors to estimate the reusability of software components. This proposed approach has also been validated against different releases of open source development. Also we have proposed a framework for component reusability Management in software component intermediate releases using the neuro-fuzzy approach. The analysis and results of the study shows that neuro-fuzzy provides better results as compare to Fuzzy Inference System and neural network but applicability of best approach depends on the data availability and the quantum of data.

References
  1. Sivanandam, S. N. , Sumathi, S. , Deepa, S. N. , 2007. Introduction to fuzzy logic using MATLAB, Springer.
  2. Zadeh, L. A. , 2002. From Computing with numbers to computing with words-from manipulation of measurements to manipulation of perceptions, International Journal of Applied Mathematics and Computer Science, Vol. 12, Issue 3, pp: 307-324.
  3. Musilek, P. , Pedrycz, W. , Succi, G. , Reformat, M. , 2000. Software Cost Estimation with Fuzzy Models, ACM SIGAPP Applied Computing Review, Vol. 8, pp: 24-29.
  4. MacDonell, S. G. , Gray, A. R. , Calvert, J. M. , 1999. FLSOME: Fuzzy Logic for Software Metric Practitioners and Researchers, In the Proceedings of the 6th International Conference on Neural Information Processing ICONIP'99, Perth, pp: 308-313.
  5. Ryder, J. , 1998. Fuzzy Modeling of Software Effort Prediction, Proceedings of IEEE Information Technology Conference, Syracuse, New York, pp: 53-56.
  6. Sailu, M. O. , Ahmed, M. , and AlGhamdi, J. , 2004. Towards Adaptive Softcomputing Based Software Effort Prediction, Fuzzy Information, Processing NAFIPS' 04, pp: 16-21.
  7. Zadeh, L. A. , 1965. Fuzzy Sets, Journal of Information and Control, Vol. 8, 1965, pp: 338–353.
  8. Acharya, S. and Sadananda, R. (1997) "Promoting Reuse Using Self-Organizing Maps", Neural Processing Letters, Issue 5, , pp: 219-226.
  9. Boetticher, G. and Eichmann, D. (1993), A Neuro-Fuzzy Based Software Reusability Evaluation System with Optimized Rule Selection, Austrelian Conference on Software Metrics (ACOSM, 93), , pp-1-11.
  10. Boxall M. A. S. and Araban S. (2004), Interface Metrics for Reusability Analysis of Components, Australian Software Engineering Conference (ASWEC'2004), Melbourne, Australia, , pp: 40-46.
  11. Cho, E. S. , Kim, M. S. And Kim, S. D. (2001), Component Metrics to Measure Component Quality, 8th Asia-Pacific Software Engineering Conference, Macau, , pp: 419-426.
  12. Dumke, R. and Schmietendorf, A. (2000) Possibilities of the Description and Evaluation of software Components, Metrics News, , Volume 5, Issue 1, pp: 13-26.
  13. Gill, N. S. (2003), Reusability Issues in Component-based Development, ACM SIGSOFT Software Engineering Notes, Volume 28, Issue 6, pp: 30-36.
  14. Kumar, V. , Sharma A. and Kumar. R. (2013), Applying Soft Computing Approaches to Predict Defect Density in Software Product Releases: An Empirical Study, COMPUTING AND INFORMATICS, volume 32, No. 1, pp: 203-224.
  15. Kumar, V. , Sharma, A. , Kumar, R. and Grover, P. S. (2012), Quality aspects for component-based systems: A metrics based approach, Software: Practices and Experience, John Wiley & Sons, December, Vol 42, Issue 12, pp: 1531-1548 .
  16. Mili, H. , Mili, F. and Mili, A. (1995) "Reusing Software: Issues and Research Directions", IEEE Transaction on Software Engineering, Volume 21, Issue 6, , pp: 528-561.
  17. Poulin, J. , Caruso, J. and Hancock, D. (1993), The Business Case for Software Reuse, IBM Systems Journal, Volume 32, Issue 40, , pp: 567-594.
  18. Rotaru, O. P. , Dobre, M. , Petrescu, M. (2005), Reusability Metrics for Software Components, IEEE International Conference on Computer Systems and Applications (AICCSA-05), Cairo, Egypt, , pp: 24-29.
  19. Sagar, S. , Nerurkar N. W. , Sharma A. , 2010. A soft computing based approach to estimate reusability of software components, ACM SIGSOFT Software Engineering Notes, Volume 35 Issue 5, September pp:1-5
  20. Sharma A. , Kumar, R. , and Grover, P. S. (2009), Reusability assessment for software components, ACM SIGSOFT Software Engineering Notes,Volume 34 Issue 2, March, pp: 1-6.
  21. Shatnawi, R. and Ziad, A. (2012), A guided oversampling technique to improve the prediction of software fault-proneness for imbalanced data , Int. J. of Knowledge Engineering and Data Mining, Vol. 2, No. 2/3, pp. 200 - 214
  22. Sindre, G. , Conradi, R. and Karlsson, E. A. (1995), The REBOOT Approach to Software Reuse, Journal of Systems and Software, Vol. 30, no. 3, , 201-212.
  23. Singh, Y. And Saha, A (2012), Prediction of testability using the design metrics for object-oriented software, Int. J. of Computer Applications in Technology, Vol. 44, No. 1, pp. 12 – 22.
  24. Washizaki, H. , Hirokazu, Y. , Yoshiaki, F. (2003), A Metrics Suite for Measuring Reusability of Software Components, Proceedings of the 9th International Symposium on Software Metric, , pp: 211-223.
  25. Sharma, A. , Kumar, R. , Grover, P. S. , 2008. Empirical Evaluation of Complexity for Software Components, International Journal of Software Engineering and Knowledge Engineering (IJSEKE), Vol. 18, Issue 5, pp: 519-530.
Index Terms

Computer Science
Information Sciences

Keywords

Components Component based system neuro-fuzzy reusability Software Metrics Prediction

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