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


[1] M. Tufano, C. Watson, G. Bavota, M. Di Penta, M. White, and D. Poshyvanyk, “An empirical investigation into learning bug-fixing patches in the wild via neural machine translation.” in ASE, 2018, pp. 832–837.

[2] K. Liu et al., “Learning to spot and refactor inconsistent method names,” in Proceedings of the 41st international conference on software engineering, 2019, pp. 1–12.

[3] C. Le Goues, M. Pradel, and A. Roychoudhury, “Automated program repair,” Commun. ACM, 2019.

[4] Z. Chen, S. Kommrusch, M. Tufano, L.-N. Pouchet, D. Poshyvanyk, and M. Monperrus, “Sequencer: Sequence-to-sequence learning for end-to-end program repair,” arXiv preprint arXiv:1901.01808, 2018.

[5] M. Vasic, A. Kanade, P. Maniatis, D. Bieber, and R. singh, “Neural program repair by jointly learning to localize and repair,” in International conference on learning representations, 2019.