Researchers have recently achieved significant advances in deep learning techniques,
which in turn has substantially advanced other research disciplines, such as natural …

In the past decade, thanks to the powerfulness of deep-learning techniques, we have
witnessed a whole new era of automated code generation. To sort out developments, we …

General-purpose code generation aims to automatically convert the natural language
description to code snippets in a general-purpose programming language (GPL) such as …

There has been a recent surge of interest in automating software engineering tasks using
deep learning. This article addresses the problem of code generation, in which the goal is to …

Code generation aims to automatically generate code snippets that meet given natural
language requirements and plays an important role in software development. Although …

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 …

Context: Neural code generation aims to automatically generate code snippets guided by
Natural Language Descriptions (NLDs). In recent years, various neural code generation …

Large language models (LLMs) have brought a paradigm shift to the field of code
generation, offering the potential to enhance the software development process. However …

Abstract Knowledge-aided dialogue response generation aims at augmenting chatbots with
relevant external knowledge in the hope of generating more informative responses. The …

Currently, the most dominant neural code generation modelsare often equipped with a tree-
structured LSTM decoder, which outputs a sequence of actions to construct an Abstract …