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For tasks like code synthesis from natural language, code retrieval, and code summarization, data-driven models have shown great promise.
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Dropout: a Simple Way to Prevent Neural Networks from Overfitting
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Natural Language Programming: Styles, Strategies, and Contrasts
Lance A Miller. 1981 · 1981
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Get Another Label? Improving Data Quality and Data Mining using Multiple, Noisy Labelers. In
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Sniff: A Search Engine for Java Using Free-form Queries. In
Shaunak Chatterjee, Sudeep Juvekar, and Koushik Sen. 2009 · 2009
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A Study of the Uniqueness of Source Code. In
Mark Gabel and Zhendong Su. 2010 · 2010
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Statistical Machine Translation
Philipp Koehn. 2010 · 2010
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Dynamic Pooling and Unfolding Recursive Autoencoders for Paraphrase Detection. In
Richard Socher, Eric H Huang, Jeffrey Pennin, Christopher D Manning, and Andrew Y Ng. 2011 · 2011
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Generating Parameter Comments and Integrating with Method Summaries. In
Giriprasad Sridhara, Lori Pollock, and K Vijay-Shanker. 2011 · 2011
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Mining Source Code Descriptions from Developer Communications. In
Sebastiano Panichella, Jairo Aponte, Massimiliano Di Penta, Andrian Marcus, and Gerardo Canfora. 2012 · 2012
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Example overflow: Using Social Media for Code Recommendation. In
Alexey Zagalsky, Ohad Barzilay, and Amiram Yehudai. 2012 · 2012
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Learning Deep Structured Semantic Models for Web Search using Clickthrough Data. In
Po-Sen Huang, Xiaodong He, Jianfeng Gao, Li Deng, Alex Acero, and Larry Heck. 2013 · 2013
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Recurrent Continuous Translation Models. In
Nal Kalchbrenner and Phil Blunsom. 2013 · 2013
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Natural Language Models for Predicting Programming Comments. In
Dana Movshovitz-Attias and William W Cohen. 2013 · 2013
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Lexical Statistical Machine Translation for Language Migration. In
Anh Tuan Nguyen, Tung Thanh Nguyen, and Tien N Nguyen. 2013 · 2013
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AutoComment: Mining question and answer sites for automatic comment generation. In
Edmund Wong, Jinqiu Yang, and Lin Tan. 2013 · 2013
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Adam: A Method for Stochastic Optimization
Diederik P. Kingma and Jimmy Ba. 2014 · 2014
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Statistical Learning Approach for Mining API Usage Mappings for Code Migration. In
Anh Tuan Nguyen, Hoan Anh Nguyen, Tung Thanh Nguyen, and Tien N Nguyen. 2014 · 2014
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Sequence to Sequence Learning with Neural Networks. In
Ilya Sutskever, Oriol Vinyals, and Quoc VV Le. 2014 · 2014
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Suggesting Accurate Method and Class Names. In
Miltiadis Allamanis, Earl T Barr, Christian Bird, and Charles Sutton. 2015 · 2015
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Bimodal Modelling of Source Code and Natural Language. In
Miltiadis Allamanis, Daniel Tarlow, Andrew D Gordon, and Yi Wei. 2015 · 2015
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Neural Machine Translation by Jointly Learning to Align and Translate. In
Program Synthesis using Natural Language. In
Aditya Desai, Sumit Gulwani, Vineet Hingorani, Nidhi Jain, Amey Karkare, Mark Marron, Subhajit Roy, and others. 2016 · 2016
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A Theoretically Grounded Application of Dropout in Recurrent Neural Networks. In
Yarin Gal and Zoubin Ghahramani. 2016 · 2016
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Incorporating Copying Mechanism in Sequence-to-Sequence Learning. In
Jiatao Gu, Zhengdong Lu, Hang Li, and Victor O.K. Li. 2016 · 2016
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On the naturalness of software
Abram Hindle, Earl T Barr, Mark Gabel, Zhendong Su, and Premkumar Devanbu. 2016 · 2016
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Learning to Rank Code Examples for Code Search Engines
Haoran Niu, Iman Keivanloo, and Ying Zou. 2016 · 2016
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From query to usable code: an analysis of Stack Overflow code snippets. In
Di Yang, Aftab Hussain, and Cristina Videira Lopes. 2016 · 2016
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Dzmitry Bahdanau, Kyunghyun Cho, and Yoshua Bengio. 2015 · 2015
Cited alongside, same era.
New Initiative: the Naturalness of Software. In
Premkumar Devanbu. 2015 · 2015
Cited alongside, same era.
CACHECA: A Cache Language Model based Code Suggestion Tool. In
Christine Franks, Zhaopeng Tu, Premkumar Devanbu, and Vincent Hellendoorn. 2015 · 2015
Cited alongside, same era.
Effective Approaches to Attention-based Neural Machine Translation. In
Thang Luong, Hieu Pham, and Christopher D. Manning. 2015 · 2015
Cited alongside, same era.
Learning to Generate Pseudo-Code from Source Code Using Statistical Machine Translation. In
Yusuke Oda, Hiroyuki Fudaba, Graham Neubig, Hideaki Hata, Sakriani Sakti, Tomoki Toda, and Satoshi Nakamura. 2015 · 2015
Cited alongside, same era.
Language to Code: Learning Semantic Parsers for If-This-Then-That Recipes. In
Chris Quirk, Raymond Mooney, and Michel Galley. 2015 · 2015
Cited alongside, same era.
Predicting Program Properties from “Big Code”. In
Veselin Raychev, Martin Vechev, and Andreas Krause. 2015 · 2015
Cited alongside, same era.
Later among the works it cites.
Antonio Valerio Miceli Barone and Rico Sennrich. 2017 · 2017
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Neural Machine Translation and Sequence-to-Sequence Models: A Tutorial
Graham Neubig. 2017 · 2017
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DyNet: The Dynamic Neural Network Toolkit
Graham Neubig, Chris Dyer, Yoav Goldberg, Austin Matthews, Waleed Ammar, Antonios Anastasopoulos, Miguel Ballesteros, David Chiang, Daniel Clothiaux, Trevor Cohn, Kevin Duh, Manaal Faruqui, Cynthia Gan, Dan Garrette, Yangfeng Ji, Lingpeng Kong, Adhiguna Kuncoro, Gaurav Kumar, Chaitanya Malaviya, Paul Michel, Yusuke Oda, Matthew Richardson, Naomi Saphra, Swabha Swayamdipta, and Pengcheng Yin. 2017 · 2017
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Abstract Syntax Networks for Code Generation and Semantic Parsing. In
Maxim Rabinovich, Mitchell Stern, and Dan Klein. 2017 · 2017
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Recovering Clear, Natural Identifiers from Obfuscated JavaScript Names. In
Bogdan Vasilescu, Casey Casalnuovo, and Premkumar Devanbu. 2017 · 2017
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A Syntactic Neural Model for General-Purpose Code Generation. In
Pengcheng Yin and Graham Neubig. 2017 · 2017
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Meaningful Variable Names for Decompiled Code: A Machine Translation Approach. In
Alan Jaffe, Jeremy Lacomis, Edward J. Schwartz, Claire Le Goues, and Bogdan Vasilescu. 2018 · 2018
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NL2Bash: A Corpus and Semantic Parser for Natural Language Interface to the Linux Operating System
Xi Victoria Lin, Chenglong Wang, Luke Zettlemoyer, and Michael D Ernst. 2018 · 2018
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StaQC: A Systematically Mined Question-Code Dataset from Stack Overflow. In
Ziyu Yao, Daniel S. Weld, Wei-Peng Chen, and Huan Sun. 2018 · 2018
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Summarizing Source Code using a Neural Attention Model. In
Srinivasan Iyer, Ioannis Konstas, Alvin Cheung, and Luke Zettlemoyer. 2016 · 2083
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