CloneTM: A Code Clone Detection Tool Based on Latent Dirichlet Allocation
Sandeep Reddivari, Mohammed Salman Khan · 2019
A plethora of clone detection techniques have been proposed in the literature to support a variety of programming languages and adopt different clone detection strategies at different levels of complexity. However, despite these major advances, these techniques are still far from achieving optimal accuracy. This requires developers to manually classify and verify the detected candidate clones, a process that is often described as time-consuming and error-prone. This paper describes CloneTM, a code clone detection tool based on Latent Dirichlet Allocation (LDA). We discuss the key features of CloneTM and present our evaluation on two datasets.