13 papers
Balancing Usefulness and Naturalness: An LLM-based Curation Pipeline for Code Review Comments
Oussama Ben Sghaier, Martin Weyssow, Houari Sahraoui
Code review is a cornerstone of software development, where reviewers provide feedback through written comments to ensure code quality, maintainability, and correctness. The effect…
Artificial Intelligence for Software Architecture: Literature Review and the Road Ahead
Alessio Bucaioni, Martin Weyssow, Junda He +2
Artificial intelligence is increasingly applied across software engineering, yet its explicit role in software architecture remains insufficiently understood. Architectural practic…
Out of Distribution, Out of Luck: How Well Can LLMs Trained on Vulnerability Datasets Detect Top 25 CWE Weaknesses?
Yikun Li, Ngoc Tan Bui, Ting Zhang +16
Automated vulnerability detection research has made substantial progress, yet its real-world impact remains limited. Prior work found that current vulnerability datasets suffer fro…
Let the Trial Begin: A Mock-Court Approach to Vulnerability Detection using LLM-Based Agents
Ratnadira Widyasari, Martin Weyssow, Ivana Clairine Irsan +6
Detecting vulnerabilities in source code remains a critical yet challenging task, especially when benign and vulnerable functions share significant similarities. In this work, we i…
An LLM-as-Judge Metric for Bridging the Gap with Human Evaluation in SE Tasks
Xin Zhou, Kisub Kim, Ting Zhang +6
Large Language Models (LLMs) and other automated techniques have been increasingly used to support software developers by generating software artifacts such as code snippets, patch…
CleanVul: Automatic Function-Level Vulnerability Detection in Code Commits Using LLM Heuristics
Yikun Li, Ting Zhang, Ratnadira Widyasari +13
Accurate identification of software vulnerabilities is crucial for system integrity. Vulnerability datasets, often derived from the National Vulnerability Database (NVD) or directl…