Code clone detection is a crucial task in software development and maintenance. While
deep learning-based methods have been proposed to tackle this problem, most of them
neglect the time and memory consumption issues which can be significant when working
with limited computational resources. Given the inability of recurrent neural networks to train
in a parallel manner, this paper presents a parallel code clone detection model based on
temporal convolutional networks. The proposed method splits the corresponding abstract …