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 …

Finetuning large language models (LLMs) on instructions leads to vast performance
improvements on natural language tasks. We apply instruction tuning using code …

Source code summarization refers to the natural language description of the source code's
function. It can help developers easily understand the semantics of the source code. We can …

Automatic program understanding and generation techniques could significantly advance
the productivity of programmers and have been widely studied by academia and industry …

Very large language models (LLMs), such as GPT-3 and Codex have achieved state-of-the-
art performance on several natural-language tasks, and show great promise also for code. A …

Modern language models (LMs) have been successfully employed in source code
generation and understanding, leading to a significant increase in research focused on …

Incident management for cloud services is a complex process involving several steps and
has a huge impact on both service health and developer productivity. On-call engineers …

Well-trained machine-learning models, which leverage large amounts of open-source
software data, have now become an interesting approach to automating many software …

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 …

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