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 …

The advancements in machine learning techniques have encouraged researchers to apply
these techniques to a myriad of software engineering tasks that use source code analysis …

In this work we present Vul4J, a Java vulnerability dataset where each vulnerability is
associated to a patch and, most importantly, to a Proof of Vulnerability (PoV) test case. We …

Previous studies have demonstrated the usefulness of employing automated static analysis
tools (ASAT) and techniques to detect security bugs in software systems. However, these …

Security vulnerability fixes could be a promising research avenue for Automated Program
Repair (APR) techniques. In recent years, APR tools have been thoroughly developed for …

Repairing software bugs with automated solutions is a long-standing goal of researchers.
Some of the latest automated program repair (APR) tools leverage natural language …

Recent work in automated program repair (APR) proposes the use of reasoning and patch
validation feedback to reduce the semantic gap between the LLMs and the code under …

Automating the repair of vulnerabilities is emerging in the field of software security. Previous
efforts have leveraged Automated Program Repair (APR) for the task. Reproducible …

Most vulnerability detection studies focus on datasets of vulnerabilities in C/C++ code,
offering limited language diversity. Thus, the effectiveness of deep learning methods …

Recent advances in Large Language Models (LLMs) have shown significant potential in
enhancing cybersecurity defenses against sophisticated threats. LLM-based penetration …