Next Syntactic-Unit Code Completion and Applications

Author:

Nguyen Anh Tuan1,Yadavally Aashish2,Nguyen Tien N.2

Affiliation:

1. Axon, Vietnam

2. Computer Science, University of Texas at Dallas, United States of America

Funder

National Science Foundation

National Security Agency

Publisher

ACM

Reference19 articles.

1. Learning from examples to improve code completion systems

2. Mark Chen Jerry Tworek Heewoo Jun Qiming Yuan Henrique Ponde de Oliveira Pinto Jared Kaplan Harri Edwards Yuri Burda Nicholas Joseph Greg Brockman Alex Ray Raul Puri Gretchen Krueger Michael Petrov Heidy Khlaaf Girish Sastry Pamela Mishkin Brooke Chan Scott Gray Nick Ryder Mikhail Pavlov Alethea Power Lukasz Kaiser Mohammad Bavarian Clemens Winter Philippe Tillet Felipe Petroski Such Dave Cummings Matthias Plappert Fotios Chantzis Elizabeth Barnes Ariel Herbert-Voss William Hebgen Guss Alex Nichol Alex Paino Nikolas Tezak Jie Tang Igor Babuschkin Suchir Balaji Shantanu Jain William Saunders Christopher Hesse Andrew N. Carr Jan Leike Josh Achiam Vedant Misra Evan Morikawa Alec Radford Matthew Knight Miles Brundage Mira Murati Katie Mayer Peter Welinder Bob McGrew Dario Amodei Sam McCandlish Ilya Sutskever and Wojciech Zaremba. 2021. Evaluating Large Language Models Trained on Code. arxiv:2107.03374 [cs.LG] Mark Chen Jerry Tworek Heewoo Jun Qiming Yuan Henrique Ponde de Oliveira Pinto Jared Kaplan Harri Edwards Yuri Burda Nicholas Joseph Greg Brockman Alex Ray Raul Puri Gretchen Krueger Michael Petrov Heidy Khlaaf Girish Sastry Pamela Mishkin Brooke Chan Scott Gray Nick Ryder Mikhail Pavlov Alethea Power Lukasz Kaiser Mohammad Bavarian Clemens Winter Philippe Tillet Felipe Petroski Such Dave Cummings Matthias Plappert Fotios Chantzis Elizabeth Barnes Ariel Herbert-Voss William Hebgen Guss Alex Nichol Alex Paino Nikolas Tezak Jie Tang Igor Babuschkin Suchir Balaji Shantanu Jain William Saunders Christopher Hesse Andrew N. Carr Jan Leike Josh Achiam Vedant Misra Evan Morikawa Alec Radford Matthew Knight Miles Brundage Mira Murati Katie Mayer Peter Welinder Bob McGrew Dario Amodei Sam McCandlish Ilya Sutskever and Wojciech Zaremba. 2021. Evaluating Large Language Models Trained on Code. arxiv:2107.03374 [cs.LG]

3. M. Ciniselli , N. Cooper , L. Pascarella , A. Mastropaolo , E. Aghajani , D. Poshyvanyk , M.  Di Penta , and G. Bavota . 5555. An Empirical Study on the Usage of Transformer Models for Code Completion . IEEE Transactions on Software Engineering 01 (nov 5555), 1–1. https://doi.org/10.1109/TSE. 2021 .3128234 10.1109/TSE.2021.3128234 M. Ciniselli, N. Cooper, L. Pascarella, A. Mastropaolo, E. Aghajani, D. Poshyvanyk, M. Di Penta, and G. Bavota. 5555. An Empirical Study on the Usage of Transformer Models for Code Completion. IEEE Transactions on Software Engineering01 (nov 5555), 1–1. https://doi.org/10.1109/TSE.2021.3128234

4. Copilot [n.d.]. Copilot. https://copilot.github.com/. Copilot [n.d.]. Copilot. https://copilot.github.com/.

5. Synthesizing Java expressions from free-form queries

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1. Large language models for code completion: A systematic literature review;Computer Standards & Interfaces;2025-03

2. How Practitioners Expect Code Completion?;Proceedings of the 31st ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering;2023-11-30

3. The Metric for Automatic Code Generation Based on Dynamic Abstract Syntax Tree;International Journal of Digital Crime and Forensics;2023-06-27

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