Software patterns are often considered as an important methodology in the process of analysis and design of a software, when the proposed architecture of the software is a complex one. During the process of reverse engineering, design patterns become helpful to analyze the source code. A pattern-based analysis often improves maintainability of the source code. The proposed reverse engineering approach considers software metrics for the development of the datasets. The study is comprises of two phases such as preparation of requisite dataset based on object-oriented software metrics and identification of design patterns. Preparation of dataset is carried out using pattern instances from source code, mapped with software metrics. Analysis of design patterns is accomplished by considering a learning-based method i.e., Artificial Neural Network. In this study, two open source software such as JRefactory and Quaqua have been considered to exploit the idea of reverse engineering. © 2018 IEEE.