Automated program repair (APR) aims to fix software bugs automatically and plays a crucial
role in software development and maintenance. With the recent advances in deep learning …

To improve software quality, just-in-time defect prediction (JIT-DP)(identifying defect-
inducing commits) and just-in-time defect localization (JIT-DL)(identifying defect-inducing …

This paper proposes a pipeline for quantitatively evaluating interactive Large Language
Models (LLMs) using publicly available datasets. We carry out an extensive technical …

Though many deep learning (DL)-based vulnerability detection approaches have been
proposed and indeed achieved remarkable performance, they still have limitations in the …

Concept This paper is a living review on automatic program repair 1. Compared to a
traditional survey, a living review evolves over time. I use a concise bullet-list style meant to …

Pre-trained Large Language Models (LLM) have achieved remarkable successes in several
domains. However, code-oriented LLMs are often heavy in computational complexity, and …

Though many deep learning-based models have made great progress in vulnerability
detection, we have no good understanding of these models, which limits the further …

This paper proposes a pipeline for quantitatively evaluating interactive LLMs such as
ChatGPT using publicly available dataset. We carry out an extensive technical evaluation of …

Software defects heavily affect software's functionalities and may cause huge losses.
Recently, many AI-based approaches have been proposed to detect defects, which can be …

Previous studies have been conducted on software vulnerability (SV) assessment at the
code-based level, especially the function level. However, a key limitation of these studies is …