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Large language models (LLMs) have demonstrated an impressive ability to generate code for various programming tasks.
Towards a big data curated benchmark of inter-project code clones
Jeffrey Svajlenko, Judith F Islam, Iman Keivanloo, Chanchal K Roy, and Mohammad Mamun Mia · 2014
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Divide-and-conquer approach for multi-phase statistical migration for source code (t)
Anh Tuan Nguyen, Tung Thanh Nguyen, and Tien N Nguyen · 2015
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Convolutional neural networks over tree structures for programming language processing
Lili Mou, Ge Li, Lu Zhang, Tao Wang, and Zhi Jin · 2016
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Antonio Valerio Miceli Barone and Rico Sennrich · 2017
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Execution-guided neural program synthesis
Xinyun Chen, Chang Liu, and Dawn Song · 2018
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Tree-to-tree neural networks for program translation
Xinyun Chen, Chang Liu, and Dawn Song · 2018
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Bert: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova · 2018
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Deep code search
Xiaodong Gu, Hongyu Zhang, and Sunghun Kim · 2018
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When deep learning met code search
Jose Cambronero, Hongyu Li, Seohyun Kim, Koushik Sen, and Satish Chandra · 2019
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Write, execute, assess: Program synthesis with a repl
Kevin Ellis, Maxwell Nye, Yewen Pu, Felix Sosa, Josh Tenenbaum, and Armando Solar-Lezama · 2019
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Codesearchnet challenge: Evaluating the state of semantic code search
Hamel Husain, Ho-Hsiang Wu, Tiferet Gazit, Miltiadis Allamanis, and Marc Brockschmidt · 2019
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Spoc: Search-based pseudocode to code
Sumith Kulal, Panupong Pasupat, Kartik Chandra, Mina Lee, Oded Padon, Alex Aiken, and Percy S Liang · 2019
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Roberta: A robustly optimized bert pretraining approach
Yinhan Liu, Myle Ott, Naman Goyal, Jingfei Du, Mandar Joshi, Danqi Chen, Omer Levy, Mike Lewis, Luke Zettlemoyer, and Veselin Stoyanov · 2019
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Devign: Effective vulnerability identification by learning comprehensive program semantics via graph neural networks
Yaqin Zhou, Shangqing Liu, Jingkai Siow, Xiaoning Du, and Yang Liu · 2019
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Vulnerability prediction from source code using machine learning
Zeki Bilgin, Mehmet Akif Ersoy, Elif Ustundag Soykan, Emrah Tomur, Pinar Çomak, and Leyli Karaçay · 2020
Cited alongside, same era.
Language models are few-shot learners
Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, et al · 2020
Cited alongside, same era.
Electra: Pre-training text encoders as discriminators rather than generators
Kevin Clark, Minh-Thang Luong, Quoc V Le, and Christopher D Manning · 2020
Cited alongside, same era.
Codebert: A pre-trained model for programming and natural languages
Zhangyin Feng, Daya Guo, Duyu Tang, Nan Duan, Xiaocheng Feng, Ming Gong, Linjun Shou, Bing Qin, Ting Liu, Daxin Jiang, et al · 2020
Cited alongside, same era.
Graphcodebert: Pre-training code representations with data flow
Measuring coding challenge competence with apps
Dan Hendrycks, Steven Basart, Saurav Kadavath, Mantas Mazeika, Akul Arora, Ethan Guo, Collin Burns, Samir Puranik, Horace He, Dawn Song, et al · 2021
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Neural program generation modulo static analysis
Rohan Mukherjee, Yeming Wen, Dipak Chaudhari, Thomas Reps, Swarat Chaudhuri, and Christopher Jermaine · 2021
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Show your work: Scratchpads for intermediate computation with language models
Maxwell Nye, Anders Johan Andreassen, Guy Gur-Ari, Henryk Michalewski, Jacob Austin, David Bieber, David Dohan, Aitor Lewkowycz, Maarten Bosma, David Luan, et al · 2021
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Tal Schuster, Ashwin Kalyan, Oleksandr Polozov, and Adam Tauman Kalai · 2021
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Generate & rank: A multi-task framework for math word problems
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Daya Guo, Shuo Ren, Shuai Lu, Zhangyin Feng, Duyu Tang, Shujie Liu, Long Zhou, Nan Duan, Alexey Svyatkovskiy, Shengyu Fu, et al · 2020
Cited alongside, same era.
https://copilot.github.com/ , 2021
Github copilot: Your ai pair programmer · 2021
Cited alongside, same era.
Unified pre-training for program understanding and generation
Wasi Uddin Ahmad, Saikat Chakraborty, Baishakhi Ray, and Kai-Wei Chang · 2021
Cited alongside, same era.
Program synthesis with large language models
Jacob Austin, Augustus Odena, Maxwell Nye, Maarten Bosma, Henryk Michalewski, David Dohan, Ellen Jiang, Carrie Cai, Michael Terry, Quoc Le, et al · 2021
Cited alongside, same era.
Deep learning based vulnerability detection: Are we there yet
Saikat Chakraborty, Rahul Krishna, Yangruibo Ding, and Baishakhi Ray · 2021
Cited alongside, same era.
Evaluating large language models trained on code
Mark Chen, Jerry Tworek, Heewoo Jun, Qiming Yuan, Henrique Ponde de Oliveira Pinto, Jared Kaplan, Harri Edwards, Yuri Burda, Nicholas Joseph, Greg Brockman, et al · 2021
Cited alongside, same era.
Latent execution for neural program synthesis beyond domain-specific languages
Xinyun Chen, Dawn Song, and Yuandong Tian · 2021
Cited alongside, same era.
Deepwukong: Statically detecting software vulnerabilities using deep graph neural network
Xiao Cheng, Haoyu Wang, Jiayi Hua, Guoai Xu, and Yulei Sui · 2021
Cited alongside, same era.
Jianhao Shen, Yichun Yin, Lin Li, Lifeng Shang, Xin Jiang, Ming Zhang, and Qun Liu · 2021
Later among the works it cites.
Yue Wang, Weishi Wang, Shafiq Joty, and Steven CH Hoi · 2021
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Gpt-neox-20b: An open-source autoregressive language model
Sid Black, Stella Biderman, Eric Hallahan, Quentin Anthony, Leo Gao, Laurence Golding, Horace He, Connor Leahy, Kyle McDonell, Jason Phang, et al · 2022
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Training and evaluating a jupyter notebook data science assistant
Shubham Chandel, Colin B Clement, Guillermo Serrato, and Neel Sundaresan · 2022
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Palm: Scaling language modeling with pathways
Aakanksha Chowdhery, Sharan Narang, Jacob Devlin, Maarten Bosma, Gaurav Mishra, Adam Roberts, Paul Barham, Hyung Won Chung, Charles Sutton, Sebastian Gehrmann, et al · 2022
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Incoder: A generative model for code infilling and synthesis
Daniel Fried, Armen Aghajanyan, Jessy Lin, Sida Wang, Eric Wallace, Freda Shi, Ruiqi Zhong, Wen-tau Yih, Luke Zettlemoyer, and Mike Lewis · 2022
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Competition-level code generation with alphacode
Yujia Li, David Choi, Junyoung Chung, Nate Kushman, Julian Schrittwieser, Rémi Leblond, Tom Eccles, James Keeling, Felix Gimeno, Agustin Dal Lago, et al · 2022
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A conversational paradigm for program synthesis
Erik Nijkamp, Bo Pang, Hiroaki Hayashi, Lifu Tu, Huan Wang, Yingbo Zhou, Silvio Savarese, and Caiming Xiong · 2022
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A systematic evaluation of large language models of code
Frank F Xu, Uri Alon, Graham Neubig, and Vincent J Hellendoorn · 2022
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