A Software Repository is a collection of library files and function codes. Programmers and Engineers design develop and build software libraries in a continuous process. Selecting suitable function code from one among many in the repository is quite challenging and cumbersome as we need to analyze semantic issues in function codes or components. Clustering and Mining Software Components for efficient reuse is the current topic of interest among researchers in Software Reuse Engineering and Information Retrieval. A relatively less research work is contributed in this field and has a good scope in the future. In this paper, the main idea is to cluster the software components and form a subset of libraries from the available repository. These clusters thus help in choosing the required component with high cohesion and low coupling quickly and efficiently. We define a similarity function and use the same for the process of clustering the software components and for estimating the cost of new project. The approach carried out is a feature vector based approach.
