Visualizing the software system towards identifying the topic from source code using semantic clustering

In software re-engineering, domain knowledge are valuable source of information for developers. Here, we describe how the coding standards are helpful for the identification of domain while writing the source code. Internal comments and logical identifier names in source code are the key source to find the concept and domain area for the application. One of the Information retrieval techniques, Latent Semantic Indexing (LSI) uses this linguistic information such as identifier names and comments in source code to map it with the domain name. Based on the linguistic results from LSI engine, a clustering technique used to group source artifacts that use similar vocabulary and a way of representing complex system into simpler components. It works at the source code textual level and making it language independent. Prior research activity correlated the semantics with structural information and applied it at different level of abstraction. Based on the frequency of the domain terms labeling has been provided after discrete characterization of the clusters, using machine learning and visually explored. Visualization makes the concept detection much easier.