TY - JOUR
T1 - A Survey of Software Clone Detection from Security Perspective
AU - Zhang, Haibo
AU - Sakurai, Kouichi
N1 - Publisher Copyright:
© 2013 IEEE.
PY - 2021
Y1 - 2021
N2 - For software engineering, if two code fragments are closely similar with minor modifications or even identical due to a copy-paste behavior, that is called software/code clone. Code clones can cause trouble in software maintenance and debugging process because identifying all copied compromised code fragments in other locations is time-consuming. Researchers have been working on code clone detection issues for a long time, and the discussion mainly focuses on software engineering management and system maintenance. Another considerable issue is that code cloning provides an easy way to attackers for malicious code injection. A thorough survey work of code clone identification/detection from the security perspective is indispensable for providing a comprehensive review of existing related works and proposing future potential research directions. This paper can satisfy above requirements. We review and introduce existing security-related works following three different classifications and various comparison criteria. We then discuss three further research directions, (i) deep learning-based code clone vulnerability detection, (ii) vulnerable code clone detection for 5G-Internet of Things devices, and (iii) real-time detection methods for more efficiently detecting clone attacks. These methods are more advanced and adaptive to technological development than current technologies, and still have enough research space for future studies.
AB - For software engineering, if two code fragments are closely similar with minor modifications or even identical due to a copy-paste behavior, that is called software/code clone. Code clones can cause trouble in software maintenance and debugging process because identifying all copied compromised code fragments in other locations is time-consuming. Researchers have been working on code clone detection issues for a long time, and the discussion mainly focuses on software engineering management and system maintenance. Another considerable issue is that code cloning provides an easy way to attackers for malicious code injection. A thorough survey work of code clone identification/detection from the security perspective is indispensable for providing a comprehensive review of existing related works and proposing future potential research directions. This paper can satisfy above requirements. We review and introduce existing security-related works following three different classifications and various comparison criteria. We then discuss three further research directions, (i) deep learning-based code clone vulnerability detection, (ii) vulnerable code clone detection for 5G-Internet of Things devices, and (iii) real-time detection methods for more efficiently detecting clone attacks. These methods are more advanced and adaptive to technological development than current technologies, and still have enough research space for future studies.
UR - http://www.scopus.com/inward/record.url?scp=85103168898&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85103168898&partnerID=8YFLogxK
U2 - 10.1109/ACCESS.2021.3065872
DO - 10.1109/ACCESS.2021.3065872
M3 - Review article
AN - SCOPUS:85103168898
SN - 2169-3536
VL - 9
SP - 48157
EP - 48173
JO - IEEE Access
JF - IEEE Access
M1 - 9378511
ER -