International Research Journal of Innovations in Engineering and Technology - IRJIET International Open Access, Monthly, Peer Reviewed, Reputed Journal ISSN (online): 2581-3048

Impact Factor (2025): 6.9

DOI Prefix: 10.47001/IRJIET

Software Maintenance Potential Prediction Based on Machine Learning

Mazin Mohammed IsmaelM.Sc. Student, Dept. of Software, College of Computer & Math., University of Mosul, IraqIbrahim Ahmed SalehProfessor, Dept. of Software, College of Computer & Math., University of Mosul, Iraq

Vol 6 No 10 (2022): Volume 6, Issue 10, October 2022 | Pages: 56-62

International Research Journal of Innovations in Engineering and Technology

OPEN ACCESS | Research Article | Published Date: 01-11-2022

doi Logo doi.org/10.47001/IRJIET/2022.610009

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Abstract

Software maintenance (SM) is one of important environment in software engineering field more complex. Therefore maintains critical to extend an environment for sharing and sustaining knowledge. In this paper introduce presents a survey reviews published materials of predication software engineering maintenance Based on several algorithms form field of artificial intelligence. This survey is useful as researchers that work for objective of software maintenance Based on algorithms of Artificial intelligence and will understand and gain the current landscape of the research and the insights gathered.

Keywords

Machine learning; software maintainability; software predicate; object-oriented metrics; fuzzy-logic; Artificial intelligence


Citation of this Article

Mazin Mohammed Ismael, Ibrahim Ahmed Saleh, “Software Maintenance Potential Prediction Based on Machine Learning” Published in International Research Journal of Innovations in Engineering and Technology - IRJIET, Volume 6, Issue 10, pp 56-62, October 2022. Article DOI https://doi.org/10.47001/IRJIET/2022.610009  

Licence Copyright (c) 2026 International Research Journal of Innovations in Engineering and Technology creative common licence This work is licensed under Creative common Attribution Non Commercial 4.0 Internation Licence
References
  1. "IEEE Standard for Software Maintenance," IEEE Std 1219-1993, 1993.
  2. Ahmed M. A. and Al-JamimiH. A., “Machine learning approaches for predicting software maintainability: a fuzzy-based transparent model,” IET Softw., vol. 7, no. 6, pp. 317–326, 2013.
  3. IEEE Std. 610.12-1990. Standard Glossary of Software Engineering Terminology, IEEE Computer Society Press, Los Alamitos, CA, 1993.
  4. Oman P. and Hagemeister J., “Construction and Testing of Polynomials Predicting Software Maintainability”, Journal of Systems and Software 24.3 (1994): 251-266.
  5. Dash Y., Dubey S.K. and Rana A., “Maintainability Measurement in Object Oriented Paradigm”, International Journal of Advanced Research in Computer Science (IJARCS), Vol.3, no.2, April 2012, pp. 207-213.
  6. DeMarco T., Controlling software projects: Management, measurement, and estimates. Prentice Hall PTR Upper Saddle River, NJ, USA, 1986.
  7. Chikako V. K. and Gray A. R., "An application of Bayesian network for predicting object-oriented software maintainability." Information and Software Technology 48.1 (2006): 59-67.
  8. Yuming Z. and Leung H., "Predicting object-oriented software maintainability using multivariate adaptive regression splines." Journal of systems and software 80.8 (2007): 1349-1361.
  9. WANG L., HU X., NING Z. andKe W., "Predicting object-oriented software maintainability using projection pursuit regression." 2009 First International Conference on Information Science and Engineering. IEEE, 2009.
  10. Mahmoud O. E. and Karim O. E.,"Application of tree net in predicting object-oriented software maintainability: A comparative study." 2009 13th European Conference on Software Maintenance and Reengineering. IEEE, 2009.
  11. KaurandA., Kaur K. and Malhotra R., "Soft computing approaches for prediction of software maintenance effort." International Journal of Computer Applications 1.16 (2010): 69-75.
  12. Jin C. and Liu J. A., "Applications of support vector machine and unsupervised learning for predicting maintainability using object-oriented metrics." 2010 Second International Conference on Multimedia and Information Technology. Vol. 1. IEEE, 2010.
  13. Malhotra R. and Chug A., “Software Maintainability Prediction using Machine Learning Algorithms,” Softw. Eng. an Int. J., vol. 2, no. 2, pp. 19–36, 2012.
  14. Yadav V.K. and Kumar S. and Mittal M., "Prediction of Software Maintenance Effort of Object Oriented Metrics Based Commercial Systems." African Journal of Computing & ICT 8.1 (2015): 163-172.
  15. Kumar L.and RathS. K., “Hybrid functional link artificial neural network approach for predicting maintainability of object-oriented software,” J. Syst. Softw., vol. 121, pp. 170–190, 2016.
  16. Jain A., Tarwani S. and Chug A., "An empirical investigation of evolutionary algorithm for software maintainability prediction." 2016 IEEE Students' Conference on Electrical, Electronics and Computer Science (SCEECS). IEEE, 2016.
  17. Kumar L. and RathS. K., “Software maintainability prediction using hybrid neural network and fuzzy logic approach with parallel computing concept,” Int. J. Syst. Assur. Eng. Manag., vol. 8, no. 2, pp.1487–1502, 2017.
  18. BaskarN. and Chandrasekar C., "Optimized Neuro-PSO-based Software Maintainability Prediction Using Relief Features Selection Method." International Journal of Pure and Applied Mathematics 119.18 (2018): 1-15.
  19. Wang X., Gegov A., Farzad A., Chen Y. and Hu Q., "Fuzzy network based framework for software maintainability prediction." International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 27.05 (2019): 841-862.
  20. Gupta S. and Chug A., "Software maintainability prediction using an enhanced random forest algorithm." Journal of Discrete Mathematical Sciences and Cryptography 23.2 (2020): 441-449.
  21. Olatunji S. O., Rasheed Z., Sattar K. A., Al- Mana A. M., Alshayeb M. and El-Sebakhy E. A., “Extreme Learning Machine as Maintainability Prediction Model for Object-Oriented Software Systems”, Journal of Computing, vol. 2, no. 8, pp. 49-56, 2010.
  22. Li W. and Henry S., "Object-Oriented Metrics that Predict Maintainability," Journal of Systems and Software, vol. 23, pp. 111-122, 1993.
  23. Chidamber S. R. and Kemerer C. F., "A Metrics Suite for Object Oriented Design," IEEE Transactions on Software Engineering, vol. 20, no. 6, pp. 476-493, 1994.

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