Design Pattern Detection by normalized cross correlation

Abstract

Design Pattern Detection has been documented so far in the literature. The knowledge of design Pattern existence in the program improves the program understanding and software maintenance. Design pattern is a technology for design reuse. Experts store their experiences in the form of design patterns. Reengineering done by novice users will be successful if a reliable design pattern mining exists. There are 23 design patterns defined by experts. Here we are taking the UML diagrams corresponding to design pattern and corresponding to source code. Our main aim is to find out whether a particular design pattern exists in system design (source code) or not. For this we have extracted the relationship graphs (consisting of nodes and edges), and then tried to detect the design pattern. In this paper we have applied normalized cross correlation and taking design pattern as a template tried to find out its existence in system design. Normalized cross correlation (NCC) has been used extensively for many machine vision applications. Normalized cross correlation has been commonly used to evaluate the degree of similarity or dissimilarity between two images.