On End-to-End Program Generation from User Intention by Deep Neural Networks [article]

Lili Mou, Rui Men, Ge Li, Lu Zhang, Zhi Jin
2015 arXiv   pre-print
This paper envisions an end-to-end program generation scenario using recurrent neural networks (RNNs): Users can express their intention in natural language; an RNN then automatically generates corresponding code in a characterby-by-character fashion. We demonstrate its feasibility through a case study and empirical analysis. To fully make such technique useful in practice, we also point out several cross-disciplinary challenges, including modeling user intention, providing datasets, improving
more » ... odel architectures, etc. Although much long-term research shall be addressed in this new field, we believe end-to-end program generation would become a reality in future decades, and we are looking forward to its practice.
arXiv:1510.07211v1 fatcat:gmmz2vceybe5liqes5ke5f7zxu