A survey of machine learning for big code and naturalness

M Allamanis, ET Barr, P Devanbu… - ACM Computing Surveys …, 2018 - dl.acm.org
Research at the intersection of machine learning, programming languages, and software
engineering has recently taken important steps in proposing learnable probabilistic models …

A review of chatgpt applications in education, marketing, software engineering, and healthcare: Benefits, drawbacks, and research directions

M Fraiwan, N Khasawneh - arXiv preprint arXiv:2305.00237, 2023 - arxiv.org
ChatGPT is a type of artificial intelligence language model that uses deep learning
algorithms to generate human-like responses to text-based prompts. The introduction of the …

Repocoder: Repository-level code completion through iterative retrieval and generation

F Zhang, B Chen, Y Zhang, J Keung, J Liu… - arXiv preprint arXiv …, 2023 - arxiv.org
The task of repository-level code completion is to continue writing the unfinished code based
on a broader context of the repository. While for automated code completion tools, it is …

Few-shot training LLMs for project-specific code-summarization

T Ahmed, P Devanbu - Proceedings of the 37th IEEE/ACM International …, 2022 - dl.acm.org
Very large language models (LLMs), such as GPT-3 and Codex have achieved state-of-the-
art performance on several natural-language tasks, and show great promise also for code. A …

On the robustness of code generation techniques: An empirical study on github copilot

A Mastropaolo, L Pascarella… - 2023 IEEE/ACM 45th …, 2023 - ieeexplore.ieee.org
Software engineering research has always being concerned with the improvement of code
completion approaches, which suggest the next tokens a developer will likely type while …

Multi-task learning based pre-trained language model for code completion

F Liu, G Li, Y Zhao, Z Jin - Proceedings of the 35th IEEE/ACM …, 2020 - dl.acm.org
Code completion is one of the most useful features in the Integrated Development
Environments (IDEs), which can accelerate software development by suggesting the next …

Reacc: A retrieval-augmented code completion framework

S Lu, N Duan, H Han, D Guo, S Hwang… - arXiv preprint arXiv …, 2022 - arxiv.org
Code completion, which aims to predict the following code token (s) according to the code
context, can improve the productivity of software development. Recent work has proved that …

Big code!= big vocabulary: Open-vocabulary models for source code

RM Karampatsis, H Babii, R Robbes, C Sutton… - Proceedings of the …, 2020 - dl.acm.org
Statistical language modeling techniques have successfully been applied to large source
code corpora, yielding a variety of new software development tools, such as tools for code …

Codefill: Multi-token code completion by jointly learning from structure and naming sequences

M Izadi, R Gismondi, G Gousios - Proceedings of the 44th International …, 2022 - dl.acm.org
Code completion is an essential feature of IDEs, yet current auto-completers are restricted to
either grammar-based or NLP-based single token completions. Both approaches have …

Deep learning code fragments for code clone detection

M White, M Tufano, C Vendome… - Proceedings of the 31st …, 2016 - dl.acm.org
Code clone detection is an important problem for software maintenance and evolution. Many
approaches consider either structure or identifiers, but none of the existing detection …