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Programming languages are emerging as a challenging and interesting domain for machine learning.
Long short-term memory
Sepp Hochreiter and Jürgen Schmidhuber · 1997
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Predicting source code changes by mining change history
Annie TT Ying, Gail C Murphy, Raymond Ng, and Mark C Chu-Carroll · 2004
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Mining version histories to guide software changes
Thomas Zimmermann, Andreas Zeller, Peter Weissgerber, and Stephan Diehl · 2005
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Latent variable models for predicting file dependencies in large-scale software development
Diane Hu, Laurens Maaten, Youngmin Cho, Sorin Lerner, and Lawrence K Saul · 2010
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On the naturalness of software
Abram Hindle, Earl T. Barr, Zhendong Su, Mark Gabel, and Premkumar Devanbu · 2012
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Mining source code repositories at massive scale using language modeling
Miltiadis Allamanis and Charles Sutton · 2013
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Mining idioms from source code
Miltiadis Allamanis and Charles Sutton · 2014
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Structured generative models of natural source code
Chris Maddison and Daniel Tarlow · 2014
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Code completion with statistical language models
Veselin Raychev, Martin Vechev, and Eran Yahav · 2014
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Programming by example using least general generalizations
Mohammad Raza, Sumit Gulwani, and Natasa Milic-Frayling · 2014
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Sequence to sequence learning with neural networks
Ilya Sutskever, Oriol Vinyals, and Quoc V Le · 2014
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Neural machine translation by jointly learning to align and translate
Dzmitry Bahdanau, Kyunghyun Cho, and Yoshua Bengio · 2015
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Deep generative image models using a laplacian pyramid of adversarial networks
Emily L Denton, Soumith Chintala, Arthur Szlam, and Rob Fergus · 2015
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DRAW: A recurrent neural network for image generation
Karol Gregor, Ivo Danihelka, Alex Graves, Danilo Rezende, and Daan Wierstra · 2015
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Pointer networks
Oriol Vinyals, Meire Fortunato, and Navdeep Jaitly · 2015
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Toward deep learning software repositories
Martin White, Christopher Vendome, Mario Linares-Vásquez, and Denys Poshyvanyk · 2015
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Learning python code suggestion with a sparse pointer network
Avishkar Bhoopchand, Tim Rocktäschel, Earl Barr, and Sebastian Riedel · 2016
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PHOG: probabilistic model for code
Pavol Bielik, Veselin Raychev, and Martin Vechev · 2016
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Building end-to-end dialogue systems using generative hierarchical neural network models
Iulian Vlad Serban, Alessandro Sordoni, Yoshua Bengio, Aaron C Courville, and Joelle Pineau · 2016
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A survey of machine learning for big code and naturalness
Miltiadis Allamanis, Earl T. Barr, Premkumar Devanbu, and Charles Sutton · 2017
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Deepfix: Fixing common c language errors by deep learning
Rahul Gupta, Soham Pal, Aditya Kanade, and Shirish Shevade · 2017
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Are deep neural networks the best choice for modeling source code?
Vincent J Hellendoorn and Premkumar Devanbu · 2017
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Enhanced neural machine translation by learning from draft
Aodong Li, Shiyue Zhang, Dong Wang, and Thomas Fang Zheng · 2017
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Wang Ling, Edward Grefenstette, Karl Moritz Hermann, Tomáš Kočiskỳ, Andrew Senior, Fumin Wang, and Phil Blunsom · 2016
Cited alongside, same era.
Api code recommendation using statistical learning from fine-grained changes
Anh Tuan Nguyen, Michael Hilton, Mihai Codoban, Hoan Anh Nguyen, Lily Mast, Eli Rademacher, Tien N Nguyen, and Danny Dig · 2016
Cited alongside, same era.
Pre-translation for neural machine translation
Jan Niehues, Eunah Cho, Thanh-Le Ha, and Alexander H. Waibel · 2016
Cited alongside, same era.
Iterative refinement for machine translation
Roman Novak, Michael Auli, and David Grangier · 2016
Cited alongside, same era.
Why google stores billions of lines of code in a single repository
Rachel Potvin and Josh Levenberg · 2016
Cited alongside, same era.
Probabilistic model for code with decision trees
Veselin Raychev, Pavol Bielik, and Martin Vechev · 2016
Cited alongside, same era.
Reasoning about entailment with neural attention
Tim Rocktäschel, Edward Grefenstette, Karl Moritz Hermann, Tomas Kocisky, and Phil Blunsom · 2016
Cited alongside, same era.
Adapting sequence models for sentence correction
Allen Schmaltz, Yoon Kim, Alexander Rush, and Stuart Shieber · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin · 2017
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A syntactic neural model for general-purpose code generation
Pengcheng Yin and Graham Neubig · 2017
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Progressive growing of gans for improved quality, stability, and variation
Tero Karras, Timo Aila, Samuli Laine, and Jaakko Lehtinen · 2018
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Deterministic non-autoregressive neural sequence modeling by iterative refinement
Jason Lee, Elman Mansimov, and Kyunghyun Cho · 2018
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Inferring crypto api rules from code changes
Rumen Paletov, Petar Tsankov, Veselin Raychev, and Martin Vechev · 2018
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Towards specification-directed program repair
Richard Shin, Dawn Song, and Illia Polosukhin · 2018
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