This paper provides a comprehensive review of the literature concerning the utilization of
Natural Language Processing (NLP) techniques, with a particular focus on transformer …

While a large number of pre-trained models of source code have been successfully
developed and applied to a variety of software engineering (SE) tasks in recent years, our …

In this work, we evaluate 10 open-source instructed LLMs on four representative code
comprehension and generation tasks. We have the following main findings. First, for the zero …

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 …

Neural Code Intelligence--leveraging deep learning to understand, generate, and optimize
code--holds immense potential for transformative impacts on the whole society. Bridging the …

Recommending APIs is a practical and essential feature of IDEs. Improving the accuracy of
API recommendations is an effective way to improve coding efficiency. With the success of …

Large language models of code have shown remarkable effectiveness across various
software engineering tasks. Despite the availability of many cloud services built upon these …

Code pre-trained models (CodePTMs) have recently demonstrated significant success in
code intelligence. To interpret these models, some probing methods have been applied …

Despite the recent advances showing that a model pre-trained on large-scale source code
data is able to gain appreciable generalization capability, it still requires a sizeable amount …

The use of modern Natural Language Processing (NLP) techniques has shown to be
beneficial for software engineering tasks, such as vulnerability detection and type inference …