In recent years, the use of automated source code generation utilizing transformer-based
generative models has expanded, and these models can generate functional code …

Prior works have developed transformer-based language learning models to automatically
generate source code for a task without compilation errors. The datasets used to train these …

Automated source code generation is currently a popular machine-learning-based task. It
can be helpful for software developers to write functionally correct code from a given context …

Modern code generation tools use AI models, particularly Large Language Models (LLMs),
to generate functional and complete code. While such tools are becoming popular and …

Code generation models based on the pre-training and fine-tuning paradigm have been
increasingly attempted by both academia and industry, resulting in well-known industrial …

Code generation systems have been extensively developed in recent years to generate
source code based on natural language instructions. However, despite their advancements …

Context: AI-assisted code generation tools have become increasingly prevalent in software
engineering, offering the ability to generate code from natural language prompts or partial …

AI-powered code generation models have been developing rapidly, allowing developers to
expedite code generation and thus improve their productivity. These models are trained on …

Large language models (LLMs) have demonstrated impressive capabilities across various
natural language processing (NLP) tasks, such as machine translation, question answering …

Code generation aims to generate a code snippet automatically from natural language
descriptions. Generally, the mainstream code generation methods rely on a large amount of …