AI-assisted coding: Experiments with GPT-4

RA Poldrack, T Lu, G Beguš - arXiv preprint arXiv:2304.13187, 2023 - arxiv.org
Artificial intelligence (AI) tools based on large language models have acheived human-level
performance on some computer programming tasks. We report several experiments using …

Codegeex: A pre-trained model for code generation with multilingual evaluations on humaneval-x

Q Zheng, X Xia, X Zou, Y Dong, S Wang, Y Xue… - arXiv preprint arXiv …, 2023 - arxiv.org
Large pre-trained code generation models, such as OpenAI Codex, can generate syntax-
and function-correct code, making the coding of programmers more productive and our …

What is it like to program with artificial intelligence?

A Sarkar, AD Gordon, C Negreanu, C Poelitz… - arXiv preprint arXiv …, 2022 - arxiv.org
Large language models, such as OpenAI's codex and Deepmind's AlphaCode, can
generate code to solve a variety of problems expressed in natural language. This …

A preliminary analysis on the code generation capabilities of gpt-3.5 and bard ai models for java functions

G Destefanis, S Bartolucci, M Ortu - arXiv preprint arXiv:2305.09402, 2023 - arxiv.org
This paper evaluates the capability of two state-of-the-art artificial intelligence (AI) models,
GPT-3.5 and Bard, in generating Java code given a function description. We sourced the …

Codegeex: A pre-trained model for code generation with multilingual benchmarking on humaneval-x

Q Zheng, X Xia, X Zou, Y Dong, S Wang… - Proceedings of the 29th …, 2023 - dl.acm.org
Large pre-trained code generation models, such as OpenAI Codex, can generate syntax-
and function-correct code, making the coding of programmers more productive. In this paper …

Is your code generated by chatgpt really correct? rigorous evaluation of large language models for code generation

J Liu, CS Xia, Y Wang, L Zhang - Advances in Neural …, 2024 - proceedings.neurips.cc
Program synthesis has been long studied with recent approaches focused on directly using
the power of Large Language Models (LLMs) to generate code. Programming benchmarks …

From copilot to pilot: Towards AI supported software development

R Pudari, NA Ernst - arXiv preprint arXiv:2303.04142, 2023 - arxiv.org
AI-supported programming has arrived, as shown by the introduction and successes of large
language models for code, such as Copilot/Codex (Github/OpenAI) and AlphaCode …

Multipl-e: A scalable and extensible approach to benchmarking neural code generation

F Cassano, J Gouwar, D Nguyen, S Nguyen… - arXiv preprint arXiv …, 2022 - arxiv.org
Large language models have demonstrated the ability to generate both natural language
and programming language text. Such models open up the possibility of multi-language …

Self-edit: Fault-aware code editor for code generation

K Zhang, Z Li, J Li, G Li, Z Jin - arXiv preprint arXiv:2305.04087, 2023 - arxiv.org
Large language models (LLMs) have demonstrated an impressive ability to generate codes
on competitive programming tasks. However, with limited sample numbers, LLMs still suffer …

In-ide code generation from natural language: Promise and challenges

FF Xu, B Vasilescu, G Neubig - ACM Transactions on Software …, 2022 - dl.acm.org
A great part of software development involves conceptualizing or communicating the
underlying procedures and logic that needs to be expressed in programs. One major …