Writing tests is a time-consuming yet essential task during software development. We
propose to leverage recent advances in deep learning for text and code generation to assist …

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

Code completion, a highly valuable topic in the software development domain, has been
increasingly promoted for use by recent advances in large language models (LLMs). To …

Software engineering research has always being concerned with the improvement of code
completion approaches, which suggest the next tokens a developer will likely type while …

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

Software testing is an essential part of the software lifecycle and requires a substantial
amount of time and effort. It has been estimated that software developers spend close to …

Code completion aims at speeding up code writing by predicting the next code token (s) the
developer is likely to write. Works in this field focused on improving the accuracy of the …

The task of generating code solutions for a given programming problem can benefit from the
use of pre-trained language models such as Codex, which can produce multiple diverse …

Recently, fine-tuning pre-trained code models such as CodeBERT on downstream tasks has
achieved great success in many software testing and analysis tasks. While effective and …

Software is constantly changing, requiring developers to perform several derived tasks in a
timely manner, such as writing a description for the intention of the code change, or …