A modified Gaussian similarity measure for clustering software components and documents
Vangipuram Radhakrishna, Chintakindi Srinivas, C. V. Guru Rao · 2014
An accountable set of dynamic changes are happening on day to day basis in the software industry. So the change is the inevitable and heart of the software industry. Although many software processes and models, tools, standards exist and practices are set, still the industry is facing huge challenge in the design, build and reuse of software components, thereby facing an issue in delivering an effective software product of high quality within a short time meeting customer expectations. Eventually, there is a critical need to throw a light in the direction of understanding related software components and methods to identify similar components so that the components of similar nature may be clustered as a single group. In this paper we propose a novel similarity measure by modifying the Gaussian function. The similarity measure designed is used to cluster the text documents and may be extended to cluster software components and program codes. The similarity measure is efficient as it covers the two sides of the term-axes.