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Authors: Jan Svacina ; Vincent Bushong ; Dipta Das and Tomas Cerny

Affiliation: Computer Science, Baylor University, One Bear Pl, Waco, TX, U.S.A.

Keyword(s): Source Code Analysis, Code Clone Detection, Semantic Clone, Enterprise Applications, Code Smells.

Abstract: Conventional approaches to code clone detection consider systems from elementary construct perspectives, making it difficult to detect semantic clones. This paper argues that semantic clone detection could be improved for enterprise systems since they typically use well-established architectures and standards. Semantic clone detection is crucial for enterprises where software’s codebase grows and evolves and maintenance costs rise significantly. While researchers have proposed many code clone detection techniques, there is a lack of solutions targeted explicitly toward enterprise systems and even fewer solutions dedicated to semantic clones. Semantic clones exhibit the same behavior between clone pairs but differ in the syntactic structure. This paper proposes a novel approach to detect semantic clones for enterprise frameworks. The driving idea is to transform a particular enterprise application into a control-flow graph representation. Next, various proprietary similarity functions are applied to compare targeted enterprise metadata for each pair of the control-flow graph fragment. As a result, we achieve to detect semantic clones with high accuracy and reasonable time complexity. (More)

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Paper citation in several formats:
Svacina, J.; Bushong, V.; Das, D. and Cerny, T. (2022). Semantic Code Clone Detection Method for Distributed Enterprise Systems. In Proceedings of the 12th International Conference on Cloud Computing and Services Science - CLOSER; ISBN 978-989-758-570-8; ISSN 2184-5042, SciTePress, pages 27-37. DOI: 10.5220/0011032200003200

@conference{closer22,
author={Jan Svacina. and Vincent Bushong. and Dipta Das. and Tomas Cerny.},
title={Semantic Code Clone Detection Method for Distributed Enterprise Systems},
booktitle={Proceedings of the 12th International Conference on Cloud Computing and Services Science - CLOSER},
year={2022},
pages={27-37},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011032200003200},
isbn={978-989-758-570-8},
issn={2184-5042},
}

TY - CONF

JO - Proceedings of the 12th International Conference on Cloud Computing and Services Science - CLOSER
TI - Semantic Code Clone Detection Method for Distributed Enterprise Systems
SN - 978-989-758-570-8
IS - 2184-5042
AU - Svacina, J.
AU - Bushong, V.
AU - Das, D.
AU - Cerny, T.
PY - 2022
SP - 27
EP - 37
DO - 10.5220/0011032200003200
PB - SciTePress

- Science and Technology Publications, Lda.
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