Analyzing Source Code Using Neural Networks: A Case Study

Code smells indicate the presence of quality issues in source code. An excessive number of smells make a software system hard to evolve and maintain. In this article, we apply deep learning models based on CNN and RNN to detect code smells without extensive feature engineering, just by feeding the source code in tokenized form.

This article is derived from our paper “On the Feasibility of Transfer-learning Code Smells using Deep Learning” by Tushar Sharma, Vasiliki Efstathiou, Panos Louridas, and Diomidis Spinellis.