Performance Evaluation of Data Mining Techniques to Enhance the Reusability of Object-Oriented (O-O) Systems
Received: 8 March 2024 | Revised: 1 April 2024, 19 April 2024, and 29 April 2024 | Accepted: 15 May 2024 | Online: 7 June 2024
Corresponding author: Bharti Bisht
Abstract
The software industry is evolving at a rapid pace, making it necessary to optimize efforts and accelerate the software development process. Software can be reused to achieve quality and productivity goals. Reusability is a crucial measure that can be used to increase the overall level of software quality in less time and effort. To better understand the necessity of enhancing the software reusability of Object-Oriented (O-O) systems, this study employed a semi-automated approach to measure the values of class-level software metrics on an input dataset collected from the MAVEN repository. This paper explored several previous studies, data strategies, and tools to predict reusability in O-O software systems. This study compares various data mining techniques to identify the most suitable approach for enhancing the reusability of O-O software systems. The analysis was based on performance parameters such as precision, MSE, and accuracy rates. Due to its higher precision and lower MSE, the SOM technique is considered one of the top data mining approaches to increase the reusability of O-O software systems. However, the results show that the different levels of reusability in O-O software systems are not adequately addressed in current solutions.
Keywords:
O-O (Object-Oriented) system, Data Mining, Reusability Level, Product QualityDownloads
References
A. Alkhalid, M. Alshayeb, and S. A. Mahmoud, "Software refactoring at the class level using clustering techniques," Journal of Research and Practice in Information Technology, vol. 43, no. 4, pp. 285–306, Nov. 2011.
A. Shatnawi and A. D. Seriai, "Mining reusable software components from object-oriented source code of a set of similar software," in 2013 IEEE 14th International Conference on Information Reuse & Integration (IRI), San Francisco, CA, USA, Aug. 2013, pp. 193–200.
G. Maheswari and K. Chitra, "Enhancing Reusability and Measuring Performance Merits of Software Component using Data Mining," International Journal of Innovative Technology and Exploring Engineering, vol. 8, no. 6s4, pp. 1577–1583, Apr. 2019.
A. Kumar, "Measuring Software reusability using SVM based classifier approach," International Journal of Information Technology and Knowledge Management, vol. 5, no. 1, pp. 205–209, 2012.
S. Vodithala and S. Pabboju, "A clustering technique based on the specifications of software components," in 2015 International Conference on Advanced Computing and Communication Systems, Coimbatore, India, 2015, pp. 1–6.
K. Deeba and B. Amutha, "Classification Algorithms of Data Mining," Indian Journal of Science and Technology, vol. 9, no. 39, Oct. 2016.
I. E. Araar and H. Seridi, "Software Features Extraction From Object-Oriented Source Code Using an Overlapping Clustering Approach," Informatica, vol. 40, no. 2, pp. 245–255, 2016.
C. Gupta and M. Rathi, "A Meta Level Data Mining Approach to Predict Software Reusability," International Journal of Information Engineering and Electronic Business, vol. 5, no. 6, pp. 33–39, Dec. 2013.
M. Arifa, N. Mohamed, and K. Archana, "Study of Software Reusability in Software Components," International Journal of Information and Communication Technology, vol. 5, no. 7, pp. 2455-2460, Aug. 2013.
S. Bobde and R. Phalnikar, "Restructuring of Object-Oriented Software System Using Clustering Techniques," in Proceeding of International Conference on Computational Science and Applications, Saint Petersburg, Russia, Jul. 2019, pp. 419–425.
E. E. Miandoab and F. S. Gharehchopogh, "A Novel Hybrid Algorithm for Software Cost Estimation Based on Cuckoo Optimization and K-Nearest Neighbors Algorithms," Engineering, Technology & Applied Science Research, vol. 6, no. 3, pp. 1018–1022, Jun. 2016.
A. Rathee and J. K. Chhabra, "Restructuring of Object-Oriented Software Through Cohesion Improvement Using Frequent Usage Patterns," ACM SIGSOFT Software Engineering Notes, vol. 42, no. 3, Sep. 2017.
A. Mateen, S. Kausar, and A. R. Sattar, "A Software Reuse Approach and Its Effect On Software Quality, An Empirical Study for The Software Industry," International Journal of Management, IT & Engineering, vol. 7, no. 2, pp. 266–279, Feb. 2017.
N. Hassan and I. Alsmadi, "Enhance Rule Based Detection for Software Fault Prone Modules," International Journal of Software Engineering and Its Applications, vol. 6, no. 1, pp. 75-86, Jan., 2012.
B. Mehboob, C. Chong, S. Lee, and J. Lim, " Reusability affecting factors and software metrics for reusability: A systematic literature review," Journal of Software: Practice and Experience, vol. 51, no. 6, pp. 1416-1458, Mar. 2021.
C. Gupta, S. Maggo, "An efficient prediction model for software reusability for Java-based object-oriented systems," International Journal of Computer Aided Engineering and Technology, vol. 6, no. 2, pp. 182-199, Jan. 2014.
B. Bisht and P. Gandhi, "Software Reusability of Object-Oriented Systems using Data Mining Techniques," International Journal of Recent Technology and Engineering (IJRTE), vol. 8, no. 6, pp. 2144–2152, Mar. 2020.
P. Divanshi and A. Singh, "A Classification-based Predictive Cost Model for Measuring Reusability Level of Open Source Software," International Journal of Recent Research Aspects, vol. 5, no. 1, pp. 19-23, Jan. 2018.
M. Gupta and S. Singh, "Empirical Evaluation of Software Design Patterns using Classification Algorithms based Design Metrics," International Journal of Applied Engineering Research, vol. 13, no. 15, pp. 11816–11823, 2018.
M. Fokaefs, N. Tsantalis, A. Chatzigeorgiou, and J. Sander, "Decomposing object-oriented class modules using an agglomerative clustering technique," in 2009 IEEE International Conference on Software Maintenance, Edmonton, Canada, Sep. 2009, pp. 93–101.
J. Bhagwan and A. Oberoi, "Software Modules Clustering: An Effective Approach for Reusability," Journal of Information Engineering and Applications, vol. 1, no. 4, 2011.
S. Manhas, R. Vashisht, P. S. Sandhu, and N. Neeru, "Reusability Evaluation Model for Procedure Based Software Systems," International Journal of Computer and Electrical Engineering, pp. 1107–1111, 2010.
P. N. Smyrlis, D. C. Tsouros, and M. G. Tsipouras, "Constrained K-Means Classification," Engineering, Technology & Applied Science Research, vol. 8, no. 4, pp. 3203–3208, Aug. 2018.
W. B. Frakes and K. Kang, "Software reuse research: status and future," IEEE Transactions on Software Engineering, vol. 31, no. 7, pp. 529–536, Jul. 2005.
N. S. Gill, "Importance of software component characterization for better software reusability," ACM SIGSOFT Software Engineering Notes, vol. 31, no. 1, pp. 1–3, Jan. 2006.
R. Keswani, S. Joshi, and A. Jatain, "Software Reuse in Practice," in 2014 Fourth International Conference on Advanced Computing & Communication Technologies, Rohtak, India, Feb. 2014, pp. 159–162.
V. R. Basili, L. C. Briand, and W. L. Melo, "How reuse influences productivity in object-oriented systems," Communications of the ACM, vol. 39, no. 10, pp. 104–116, Oct. 1996.
Downloads
How to Cite
License
Copyright (c) 2024 Bharti Bisht, Parul Gandhi
This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors who publish with this journal agree to the following terms:
- Authors retain the copyright and grant the journal the right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) after its publication in ETASR with an acknowledgement of its initial publication in this journal.
