1. Hybrid approach for software component classification using computational intelligence
Authors : Pravind Kumar, Pradeep Tomar, Jagdeep Kaur
Pages : 206-211
Keywords : Keywords-Fuzzy C-Means Clustering Algorithm, Fuzzy Subtractive Clustering Algorithm, Software Component Classification. Abstract :
Abstract-Software engineering provides solutions of the existing problems coming from different-different areas. Fuzzy C-Means and Subtractive Clustering Algorithm play a vital role in the Software Engineering for Software Components Classification in their respective Clusters. Fuzzy C-Means Clustering Algorithm has a major disadvantage that the number of Clusters formed, intimate before classification of Software Components. How can intimate the number of Software Components beforehand, it depends on the nature of data points used. This is the main cause to produce local optimal solutions in stead of optimal solution. Fuzzy Subtractive Clustering Algorithm evaluate the number of required Clusters on the base of nature of Software Components. This paper use a Hybrid Approach for Software Components Classifications by using Computational intelligence.The problems associated with Fuzzy C-Means can rectify to use to Fuzzy Subtractive Clustering Algorithm, but Computation time required is high that’s why in this paper use rejection ratio, Recall and Precision to classify Software Components. Selecting a Cluster Center is main task in Clustering process because if selection of Cluster center is good then Computation time to classify Software Components in their respective Clusters is small.
Citing this Journal Article :Pravind Kumar, Pradeep Tomar, Jagdeep Kaur, "Hybrid approach for software component classification using computational intelligence", Volume 6 Issue 4 - March 2016, 206-211
Click here to Submit Copyright Takedown Notice for this article.