Recently, machine learning (ML) methods have been used to create powerful language
models for a broad range of natural language processing tasks. An important subset of this …

Researchers have recently achieved significant advances in deep learning techniques,
which in turn has substantially advanced other research disciplines, such as natural …

Large language models (LLMs) have recently been applied in software engineering to
perform tasks such as translating code between programming languages, generating code …

Recently, the ChatGPT LLM has received great attention: it can be used as a bot for
discussing source code, prompting it to suggest changes, provide descriptions or even …

Code comment generation aims at generating natural language descriptions for a code
snippet to facilitate developers' program comprehension activities. Despite being studied for …

Source code documentation is an important artifact for efficient software development. Code
documentation could greatly benefit from automation since manual documentation is often …

Recent years have seen the successful application of large pre-trained models to code
representation learning, resulting in substantial improvements on many code-related …

Source code summarization aims to automatically generate concise summaries of source
code in natural language texts, in order to help developers better understand and maintain …

To support software developers in understanding and maintaining programs, various
automatic code summarization techniques have been proposed to generate a concise …

Context: Test case generation is a critical yet challenging task in software development.
Recently, AthenaTest–a Deep Learning (DL) approach for generating unit test cases has …