Implementing Clustering Based Approach for Evaluation of Success of Software Reuse using K-means algorithm
Journal: INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY (Vol.4, No. 3)Publication Date: 2013-01-01
Authors : Jagmeet Kaur; Dheerendra Singh;
Page : 807-812
Keywords : Kmeans; Reuse and Machine learning.;
Abstract
A great deal of research over the past several years has been devoted to the development of methodologies to create reusable software components and component libraries. But the issue of how to find the contribution of the factor towards the successfulness of the reuse program is still in the naïve stage and very less work is done on the modeling of the success of the reuse. The success and failure factors are the key factors that predict the successful reuse of software. An algorithm has been proposed in which the inputs can be given to K-Means Clustering system in form of tuned values of the Data Factors and the developed model shows the high precision results , which describe the success of software reuse.
Other Latest Articles
- STUDENTS LEARNING PATHS AS ‘DYNAMIC ENCEPHALOGRAPHS’ OF THEIR COGNITIVE DEVELOPMENT
- Steganography: Securing Message in wireless network
- ANALYSIS OF HUMAN FACE RECOGNITION ALGORITHM USING PCA+FDIT IN IMAGE DATABASE FOR CRIME INVESTIGATION
- Dynamic Energy Aware Gur Game based Algorithms for Self Optimizing Wireless Sensor Networks
- Fault Tolerant Heterogeneous Limited Duplication Scheduling algorithm for Decentralized Grid
Last modified: 2016-06-30 13:49:18