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On Learning Meaningful Code Changes via Neural Machine Translation
[article]
2019
arXiv
pre-print
Recent years have seen the rise of Deep Learning (DL) techniques applied to source code. Researchers have exploited DL to automate several development and maintenance tasks, such as writing commit messages, generating comments and detecting vulnerabilities among others. One of the long lasting dreams of applying DL to source code is the possibility to automate non-trivial coding activities. While some steps in this direction have been taken (e.g., learning how to fix bugs), there is still a
arXiv:1901.09102v1
fatcat:6eac2mbu4zcvzhev6jt46ki63i