Pre-trained models for programming languages have recently demonstrated great success
on code intelligence. To support both code-related understanding and generation tasks …

Pre-trained models for programming language have achieved dramatic empirical
improvements on a variety of code-related tasks such as code search, code completion …

We present CodeBERT, a bimodal pre-trained model for programming language (PL) and
nat-ural language (NL). CodeBERT learns general-purpose representations that support …

Evaluation metrics play a vital role in the growth of an area as it defines the standard of
distinguishing between good and bad models. In the area of code synthesis, the commonly …

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

Large-scale pre-trained models such as CodeBERT, GraphCodeBERT have earned
widespread attention from both academia and industry. Attributed to the superior ability in …

Smart contracts with natural economic attributes have been widely and rapidly developed in
various fields. However, the bugs and vulnerabilities in smart contracts have brought huge …

Pre-trained models of code built on the transformer architecture have performed well on
software engineering (SE) tasks such as predictive code generation, code summarization …

Code Generation aims at generating relevant code fragments according to given natural
language descriptions. In the process of software development, there exist a large number of …

Recent work learns contextual representations of source code by reconstructing tokens from
their context. For downstream semantic understanding tasks like summarizing code in …