A Mixed Method Approach for Efficient Component Retrieval from a Component Repository
Jasmine Kalathipparambil Sudhakaran, Ramaswamy Vasantha
DOI: 10.4236/jsea.2011.47051   PDF    HTML     3,761 Downloads   7,425 Views   Citations


A continuing challenge for software designers is to develop efficient and cost-effective software implementations. Many see software reuse as a potential solution; however, the cost of reuse tends to outweigh the potential benefits. The costs of software reuse include establishing and maintaining a library of reusable components, searching for applicable components to be reused in a design, as well as adapting components toward a proper implementation. In this context, a new method is suggested here for component classification and retrieval which consists of K-nearest Neighbor (KNN) algorithm and Vector space Model Approach. We found that this new approach gives a higher accuracy and precision in component selection and retrieval process compared to the existing formal approaches.

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J. Sudhakaran and R. Vasantha, "A Mixed Method Approach for Efficient Component Retrieval from a Component Repository," Journal of Software Engineering and Applications, Vol. 4 No. 7, 2011, pp. 442-445. doi: 10.4236/jsea.2011.47051.

Conflicts of Interest

The authors declare no conflicts of interest.


[1] W. S. Sarma and V. Rao, “A Rough–Fuzzy Approach for Retrieval off Candidate Components for Software Reuse,” Pattern Recognition Letters, Vol. 24, No. 6, 2003, pp. 875-886. doi:10.1016/S0167-8655(02)00199-X
[2] P. A. González-Calero, “Applying Knowledge Modeling and Case-Based Reasoning to Software Reuse,” IEE Proceedings – Software, Vol. 147, No. 5, October 2000, pp. 169-177.
[3] D. Lucrédio, et al., “Component Retrieval Using Metric Indexing,” IEEE International Conference on Information Reuse and Integration, Las Vegas, 8-10 November 2004, pp. 79-84.
[4] D. Lucrédio, et al., “A Survey on Software Components Search and Retrieval,” 30th IEEE Euromicro Conference, Rennes, 31 August-3 September 2004, pp. 152-159.
[5] HHG. SaltonHH, A. Wong and C. S. Yang, “A Vector Space Model for Automatic Indexing,” Communications of the ACM, Vol. 18, No. 11, 1975, pp. 613-620. doi:10.1145/361219.361220
[6] L. S. Sorumgard, G. Sindre and F. Stokke, “Experiences from Application of a Faceted Classification Scheme,” Advances in Software Reuse, Selected Papers from the 2nd International Workshop on Software Reusability, Lucca, 24-26 March 1993, pp. 116-124.
[7] J. B. Lovins, “Development of a Stemming Algorithm,” Mechanical Translation and Computational Linguistics, Vol. 11, No. 1-2, 1968, pp. 22-31.
[8] D. Blair and M. E. Maron, “An Evaluation of Retrieval Effectiveness for a Full-Text, Document-Retrieval System,” Communications of the ACM, Vol. 35, No. 4, March 1985, pp. 289-299. doi:10.1145/3166.3197
[9] Y. Yang and X. Liu, “A Re-examination of Text Categorization Methods,” Proceedings of ACM SIGIR Conference on Research and Development in Information Retrieval, Berkley, 15-19 August 1999, pp. 42-49.
[10] W. B. Frakes and B. A. Nejmeh, “An Information System for Software Reuse, Software Reuse: Emerging Technology,” CS Press, Sheffield, 1990, pp.142-151.
[11] Y. Yang and J. O. Pedersen, “A Comparative Study on Feature Selection in Text Categorization,” Proceedings of the 14th International Conference on Machine Learning, Nashville, 8-12 July 1997, pp. 412-420.
[12] N. Ishii, T. Murai, et al., “Text Classification by Combining Grouping, LSA and kNN,” 5th IEEE/ACIS International Conference on Computer and Information Science, Honolulu, 10-12 July 2006, pp. 148-154.
[13] Y. S. Yoelle S. Maarek, D. M. Berry and G. E. Kaiser, “An Information Retrieval Approaches for Automatically Constructing Software Libraries,” IEEE Transactions on Software Engineering, Vol. 17, No. 8, 1991, pp. 800-813. doi:10.1109/32.83915

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