The papers to read for this session are [1] and [2]

References

[1] V. Saini, F. Farmahinifarahani, Y. Lu, P. Baldi, and C. V. Lopes, “Oreo: Detection of clones in the twilight zone,” in Proceedings of the 2018 26th acm joint meeting on european software engineering conference and symposium on the foundations of software engineering, 2018, pp. 354–365.

[2] A. Zorin and V. Itsykson, “Recurrent neural network for code clone detection,” Software Engineering and Infomation Management, p. 47, 2018.

[3] S. Luan, D. Yang, K. Sen, and S. Chandra, “Aroma: Code recommendation via structural code search,” arXiv preprint arXiv:1812.01158, 2018.

[4] L. Büch and A. Andrzejak, “Learning-based recursive aggregation of abstract syntax trees for code clone detection,” in 2019 ieee 26th international conference on software analysis, evolution and reengineering (saner), 2019, pp. 95–104.

[5] L. Jiang, G. Misherghi, Z. Su, and S. Glondu, “Deckard: Scalable and accurate tree-based detection of code clones,” in Proceedings of the 29th international conference on software engineering, 2007, pp. 96–105.

[6] M. Allamanis and C. Sutton, “Mining idioms from source code,” in Proceedings of the 22nd acm sigsoft international symposium on foundations of software engineering, 2014, pp. 472–483.

[7] M. White, M. Tufano, C. Vendome, and D. Poshyvanyk, “Deep learning code fragments for code clone detection,” in Proceedings of the 31st ieee/acm international conference on automated software engineering, 2016, pp. 87–98.