Automated Program Repair: A Comparison of Token Based and Tree Based Approaches The PreProcessed data to perform fair comparison for CODIT and SEQUENCER.
@article{chen2018sequencer, title={SequenceR: Sequence-to-Sequence Learning for End-to-End Program Repair}, author={Chen, Zimin and Kommrusch, Steve and Tufano, Michele and Pouchet, Louis-No{"e}l and Poshyvanyk, Denys and Monperrus, Martin}, journal={IEEE Transaction on Software Engineering}, year={2019} }
@article{chakraborty2020codit, title={Codit: Code editing with tree-based neural models}, author={Chakraborty, Saikat and Ding, Yangruibo and Allamanis, Miltiadis and Ray, Baishakhi}, journal={IEEE Transactions on Software Engineering}, volume={48}, number={4}, pages={1385--1399}, year={2020}, publisher={IEEE} }