Improving code autocompletion with transfer learning
Software language models have achieved promising results predicting code completion
usages, and several industry studies have described successful IDE integration. Recently …
usages, and several industry studies have described successful IDE integration. Recently …
Learning autocompletion from real-world datasets
Code completion is a popular software development tool integrated into all major IDEs.
Many neural language models have achieved promising results in completion suggestion …
Many neural language models have achieved promising results in completion suggestion …
Codefill: Multi-token code completion by jointly learning from structure and naming sequences
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 …
either grammar-based or NLP-based single token completions. Both approaches have …
Language models for code completion: A practical evaluation
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 …
promise so far, yet the evaluation of these models rarely uses real data. This study provides …
On the Generalizability of Deep Learning-based Code Completion Across Programming Language Versions
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 …
predicting the next tokens a developer is likely to write, helping them write code faster and …
A self-attentional neural architecture for code completion with multi-task learning
Code completion, one of the most useful features in the Integrated Development
Environments (IDEs), can accelerate software development by suggesting the libraries …
Environments (IDEs), can accelerate software development by suggesting the libraries …
Source code auto-completion using various deep learning models under limited computing resources
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 …
Among such tasks, source code auto-completion is one of the important areas of research …
Pythia: Ai-assisted code completion system
A Svyatkovskiy, Y Zhao, S Fu… - Proceedings of the 25th …, 2019 - dl.acm.org
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 …
called Pythia. It generates ranked lists of method and API recommendations which can be …
Next syntactic-unit code completion and applications
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 …
Existing code completion approaches focus on completing the current code token, next …
Neural code completion
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 …
for dynamically typed programming languages. In this paper we ex-plore the use of neural …