Work

Intelligent token-based code clone detection system for large scale source code

Year: 2019

Type: conference-paper

Abstract: A code clone refers to code fragments in the source code that are identical or similar to each other. Code clones lead difficulties in software maintenance, bug fixing, present poor design and increase the system size. Code clone detection techniques and tools have been proposed by many researchers, however, there is a lack of clone detection techniques especially for large scale repositories. In this paper, we present a token-based clone detector called Intelligent Clone Detection Tool (ICDT) that can detect both exact and near-miss clones from large repositories using a standard workstation environment. In order to evaluate the scalability and the efficiency of ICDT, we use the most recent benchmark which is a big benchmark of real clones, BigCloneBench. In addition, we compare ICDT to four publicly available and state-of-the-art tools.

Source: ACM Conference on Research in Adaptive and Convergent Systems (RACS)

DOI: 10.1145/3338840.3355654

Authors: Abdulrahman Abu Elkhail, Jan Svacina, Tomas Cerny

Institution: Baylor University

Language: English

Topic: Software Engineering Research

Subfield: Information Systems

Field: Computer Science

Domain: Physical Sciences

Open Access status: bronze

Funder: National Science Foundation

Award: IRES Track I: U.S.-Czech Student Research Experience on Software Test Automation and Quality Assurance