We apologize for a recent technical issue with our email system, which temporarily affected account activations. Accounts have now been activated. Authors may proceed with paper submissions. PhDFocusTM
CFP last date
20 December 2024
Call for Paper
January Edition
IJCA solicits high quality original research papers for the upcoming January edition of the journal. The last date of research paper submission is 20 December 2024

Submit your paper
Know more
The week's pick
Responsive image
Improved Shuffled Frog Leaping Algorithm with Self-Adaptive Shuffling for Fuzzy Logic PD+G Controller Optimization in Robotic Manipulators

Duc Hoang Nguyen
Random Articles
Reseach Article

Software Maintainability Modeling using Fuzzy Systems: Early Stage Perspective

by Syed Wajahat Abbas Rizvi
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 182 - Number 49
Year of Publication: 2019
Authors: Syed Wajahat Abbas Rizvi
10.5120/ijca2019918747

Syed Wajahat Abbas Rizvi . Software Maintainability Modeling using Fuzzy Systems: Early Stage Perspective. International Journal of Computer Applications. 182, 49 ( Apr 2019), 7-12. DOI=10.5120/ijca2019918747

@article{ 10.5120/ijca2019918747,
author = { Syed Wajahat Abbas Rizvi },
title = { Software Maintainability Modeling using Fuzzy Systems: Early Stage Perspective },
journal = { International Journal of Computer Applications },
issue_date = { Apr 2019 },
volume = { 182 },
number = { 49 },
month = { Apr },
year = { 2019 },
issn = { 0975-8887 },
pages = { 7-12 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume182/number49/30526-2019918747/ },
doi = { 10.5120/ijca2019918747 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T01:14:45.644409+05:30
%A Syed Wajahat Abbas Rizvi
%T Software Maintainability Modeling using Fuzzy Systems: Early Stage Perspective
%J International Journal of Computer Applications
%@ 0975-8887
%V 182
%N 49
%P 7-12
%D 2019
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Maintainability has been a big challenge for the information technology industry. Every stakeholder in the context of software application needs a maintainable software. The basis of this concern is the cost that the software maintenance consumes. In continuation with this crucial issue, this paper has developed a Maintainability prediction model that quantifies the software Maintainability through fuzzy techniques in the early phase of software development life cycle. The focus of the paper is the Maintainability quantification prior to the coding phase so that the personnel involved in developing the software should be able to take suitable and timely measure. If they get any input before the start of coding, then definitely they will do the correction in a cost-effective manner. This study identified product based object-oriented design measure and integrated them with fuzzy inference system. The developed model has also validated, along with appropriate predictive accuracy results.

References
  1. Rizvi, S. W. A., and Khan, R. A. 2010. Maintainability Estimation Model for Object-Oriented Software in Design Phase (MEMOOD). Journal of Computing, 2(4), 26-32.
  2. Mamdani, E. H. 1977. Applications of fuzzy logic to approximate reasoning using linguistic synthesis. IEEE Transaction on Computers, 26(12), 1182–1191.
  3. Li W., and Henry, S. 1993. Object-Oriented Metrics that Predict Maintainability. Journal of Systems and Software, 23(2), 111 – 122.
  4. Schneidewind, N. F. 1992. Methodology for Validating Software Metrics. IEEE Trans. on Software Engineering, 18(5), 410 - 422
  5. Rizvi, S. W. A., and Khan, R. A. 2009. A Critical Review on Software Maintainability Models. Proceedings of the Conference on Cutting Edge Computer and Electronics Technologies, 144-148.
  6. Bansiya, J., and Devis, C. 1997. Automated Metrics for Object-Oriented Development. Dr. Dobb’s Journal, 272(12), 42-48.
  7. Bansiya, J., and Devis, C. 2002. A Hierarchical Model for Object-Oriented Design Quality Assessment. IEEE Transactions on Software Engineering, 28(1), 4-17.
  8. Rizvi, S.W.A. and Khan, R.A. 2013. Improving Software Requirements through Formal Methods. International Journal of Information and Computation Technology, 3(11), 1217-1223.
  9. Antonellis, P., Antoniou, D., Kanellopoulos, Y., Makris, C., Theodoridis, E., Tjortjis, C., and Tsirakis, N. 2007. A Data Mining Methodology for Evaluating Maintainability According to ISO/IEC-9126 Software Engineering Product Quality Standard. Proc. 11th IEEE Conference on Software Maintenance and Reengineering (CSMR2007), 21 – 23 Mar. 2007, Amsterdam, Netherlands.
  10. Oman, P. W. and Hagemeister, J. R. 1994. Construction and Testing of Polynomials Predicting Software Maintainability. Journal of Systems and Software, 24(3), 251 – 266.
  11. Welker, K. D. and Oman, P. W. 1995. Software Maintainability Metrics Models in Practice. Journal of Defense Software Engineering, 8(11), 19 – 23.
  12. Hayes, J. H., Patel, S. C. and Zhao, L. 2004. A Metrics-Based Software Maintenance Effort Model. Proc. 8th European Conference on Software Maintenance and Reengineering (CSMR'04) IEEE Socity, 24 – 26 Mar. 2004, 254 – 258.
  13. Polo, M., Piattini, M., and Ruiz, F. 2001. Using Code Metrics to Predict Maintenance of Legacy Programs: A Case Study. Proc. of International Conference on Software Maintenance, IEEE Computer Society, Florence Italy, ICSM 2001, 202-208.
  14. Hayes, J. H., and Zhao, L. 2005. Maintainability Prediction: A Regression Analysis of Measures of Evolving Systems. Proc. 21st IEEE International Conference on Software Maintenance, 26 - 29 Sept. 2005, 601 - 604.
  15. Muthanna, S., Kontogiannis, K., Ponnambalam, K., and Stacey, B. 2000. A Maintainability Model for Industrial Software Systems Using Design Level Metrics. Proc. 7th Working Conference on Reverse Engineering (WCRE’00), 23 - 25 Nov., 2000, Brisbane, Australia, 248 – 256.
  16. Genero, M., Manso, E., and Cantone, G. 2003. Building UML Class Diagram Maintainability Prediction Models Based on Early Metrics. Proc. 9th International Symposium on Software Metrics (METRICS'03), 3 - 5 Sept., 2003, 263 – 275.
  17. Kiewkanya, M., Jindasawat, N., and Muenchaisri, P. 2004. A Methodology for Constructing Maintainability Model of Object-Oriented Design. Proc. 4th International Conference on Quality Software, IEEE Computer Society 8 - 9 Sept., 2004, 206 - 213.
  18. Rizvi, S.W.A., Singh, V.K. and Khan, R.A. 2016. Software Reliability Prediction using Fuzzy Inference System: Early Stage Perspective, International Journal of Computer Applications, 145(10), 16-23.
  19. Zadeh, L.A. 1989. Knowledge representation in fuzzy logic. IEEE Transactions on Knowledge and Data Engineering, 1(1), 89–100.
  20. Hitz, M., and Montazeria, B. 1996. Chidamber and Kemerer’s Metrics Suite: A Measurement Theory Perspective. IEEE Transactions on Software Engineering, 22(4), 267 – 271.
  21. Rizvi, S.W.A., Singh, V. K., and Khan, R. A. 2016. Fuzzy Logic based Software Reliability Quantification Framework: Early Stage Perspective (FLSRQF), Elsevier Procedia-Computer Science, 89, 359-368
  22. Abreu B. F., and Carapuca, R. 1993. Candidate Metrics for Object-Oriented Software within a Taxonomy Framework. Journal of Systems and Software, Elsevier-Science, 23(1), 87 – 96.
  23. Genero, M., Manso, E., Visaggio, A., and Piattini, M. 2007. Building Measure-Based Prediction Models for UML Class Diagram Maintainability. Journal of Empirical Software Engineering, 12(5), 517 – 549.
  24. Rizvi, S. W. A., Singh, V. K., and Khan, R. A. 2016. The State of the Art in Software Reliability Prediction: Software Metrics and Fuzzy Logic Perspective. Advances in Intelligent Systems and Computing, Springer, 433, 629-637.
  25. Elish, M. O., and Elish, K. O. 2009. Application of TreeNet in Predicting Object-Oriented Software Maintainability: A Comparative Study. Proc. of European Conference on Software Maintenance and Reengineering (CSMR’09), 24 - 27 Mar., 2009, 69 - 78.
  26. Rizvi, S.W.A., Khan, R.A., and Singh, V.K. (2017). Early Stage Software Reliability Modeling using Requirements and Object-Oriented Design Metrics: Fuzzy Logic Perspective. International Journal of Computer Applications, 162(2), 44-59.
  27. Bruntink M., and Deursen, A. 2004. Predicting Class Testability using Object-Oriented Metrics. Proc. 4th IEEE International Workshop on Source Code Analysis and Manipulation SCAM'04, 15 - 16 Sept., 2004, 136 – 145.
  28. Olague, H.M., Etzkorn, L. H., Messimer, S.L., and Delugach, H.S. 2008. An Empirical Validation of Object-Oriented Class Complexity Metrics and their Ability to Predict Error-prone Classes in Highly Iterative, or Agile Software: a Case Study,” Journal of Software Maintenance, vol. 20(3), 171 – 197.
  29. S. W. A. Rizvi, V. K. Singh, R. A. Khan: “Revisiting Software Reliability Engineering with Fuzzy Techniques”, IEEE Xplore, 10th INDIACom, organized by BVICAM, New Delhi, March, 2016. ISBN:978-93-80544-19-9, ISSN:0973- 7529, pp. 1037-1042.
  30. Ross, T. J. 2010. Fuzzy Logic with Engineering Applications. 3rd Edition, John Wiley and sons.
  31. Dromey, R.G. 1995. A Model for Software Product Quality. IEEE Transactions on Software Engineering, 21(2), 146-162
  32. S. W. A. Rizvi, V. K. Singh, R. A. Khan,: “Application of Fuzzy Logic in Early Stage Software Reliability Prediction”, International Journal of Information Processing, Vol. 10, Issue 3, November 2016, pp. 61-77.
  33. Walkerden, F., and Jeffery, R. 1999. Analogy, Regression and Other Methods for Estimating Effort and Software Quality Attributes. Proceeding of European Conference Optimizing Software Development and Maintenance, 37-46
  34. Conte, S. D., Dunsmore, H. F., and Shen, V. Y. 1986. Software Engineering Metrics and Models. ISBN: 0805321624, Benjamin Cummings Publishing Co., Inc., Redwood city, CA, USA.
Index Terms

Computer Science
Information Sciences

Keywords

Software Maintainability Early Stage Prediction Fuzzy Logic Software Defects Software Metrics Software Maintainability Model Object-Oriented Design UML Class Diagrams.

Powered by PhDFocusTM