Abstract
Code clone detection is challenging, as sourcecode can be written in different languages, do-mains, and styles. In this paper, we arguethat source code is inherently a graph, not asequence, and that graph-based methods aremore suitable for code clone detection thansequence-based methods. We compare the per-formance of two state-of-the-art models: Code-BERT (Feng et al., 2020), a sequence-basedmodel, and CodeGraph (Yu et al., 2023), agraph-based model, on two benchmark data-sets: BCB (Svajlenko et al., 2014) and PoolC(PoolC, no date). We show that CodeGraphoutperforms CodeBERT on both data-sets, es-pecially on cross-lingual code clones. To thebest of our knowledge, this is the first work todemonstrate the cross-lingual code clone detec-tion showing superiority on graph-based meth-ods over sequence-based methods- Anthology ID:
- 2024.naacl-srw.20
- Volume:
- Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 4: Student Research Workshop)
- Month:
- June
- Year:
- 2024
- Address:
- Mexico City, Mexico
- Editors:
- Yang (Trista) Cao, Isabel Papadimitriou, Anaelia Ovalle
- Venue:
- NAACL
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 168–199
- Language:
- URL:
- https://aclanthology.org/2024.naacl-srw.20
- DOI:
- Cite (ACL):
- Mohammed Rahaman and Julia Ive. 2024. Source Code is a Graph, Not a Sequence: A Cross-Lingual Perspective on Code Clone Detection. In Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 4: Student Research Workshop), pages 168–199, Mexico City, Mexico. Association for Computational Linguistics.
- Cite (Informal):
- Source Code is a Graph, Not a Sequence: A Cross-Lingual Perspective on Code Clone Detection (Rahaman & Ive, NAACL 2024)
- PDF:
- https://preview.aclanthology.org/ingestion-checklist/2024.naacl-srw.20.pdf