Software language models have achieved promising results predicting code completion
usages, and several industry studies have described successful IDE integration. Recently …

Code completion is a popular software development tool integrated into all major IDEs.
Many neural language models have achieved promising results in completion suggestion …

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 …

Transformer-based language models for automatic code completion have shown great
promise so far, yet the evaluation of these models rarely uses real data. This study provides …

Code completion is a key feature of Integrated Development Environments (IDEs), aimed at
predicting the next tokens a developer is likely to write, helping them write code faster and …

Code completion, one of the most useful features in the Integrated Development
Environments (IDEs), can accelerate software development by suggesting the libraries …

Deep learning models have become state of the art in many language modelling tasks.
Among such tasks, source code auto-completion is one of the important areas of research …

In this paper, we propose a novel end-to-end approach for AI-assisted code completion
called Pythia. It generates ranked lists of method and API recommendations which can be …

Code completion is an important feature in an IDE to improve developers' productivity.
Existing code completion approaches focus on completing the current code token, next …

Code completion, an essential part of modern software development, yet can bechallenging
for dynamically typed programming languages. In this paper we ex-plore the use of neural …