The papers to read for this session are  and 
 M. Allamanis, M. Brockschmidt, and M. Khademi, “Learning to represent programs with graphs,” arXiv preprint arXiv:1711.00740, 2017.
 P. Yin, G. Neubig, M. Allamanis, M. Brockschmidt, and A. L. Gaunt, “Learning to Represent Edits,” ArXiv e-prints, Oct. 2018.
 H. Z. Jian Zhang Xu Wang and X. Liu, “A novel neural source code representation based on abstract syntax tree,” in ICSE 2019, 2019.
 M. Tufano, C. Watson, G. Bavota, M. Di Penta, M. White, and D. Poshyvanyk, “Deep learning similarities from different representations of source code,” in 2018 ieee/acm 15th international conference on mining software repositories (msr), 2018, pp. 542–553.