collaborators

24 papers

cs.SE2026

AgenticRepair: Multi-Faceted Program Context Engineering for Agentic Vulnerability Repair

Michael Fu, Qiyue Mei, Patanamon Thongtanunam +1

Automated vulnerability repair aims to reduce the time and effort required to patch security flaws from a vulnerability triage report. Recent agentic AI approaches have shown promi…

cs.SE2026

Agentic Code Review in the Terminal: A Trajectory-Level Analysis of Behavior, Cost, and Human-Alignment

Wachiraphan Charoenwet, Kla Tantithamthavorn, Patanamon Thongtanunam +3

Agentic code review in terminal-based environments enables early feedback during local development before pull request creation. However, existing evaluations remain performance-ce…

cs.SE2026

Is Agentic Code Review Helpful? Mining Developers' Feedback to CodeRabbit Reviews in the Wild

Hong Yi Lin, Mingzhao Liang, Kla Tantithamthavorn +1

Agentic code review, where autonomous agents provide code review comments on pull requests, is increasingly integrated into development workflows, yet there is limited empirical ev…

cs.SE2026

HalluJudge: A Reference-Free Hallucination Detection for Context Misalignment in Code Review Automation

Kla Tantithamthavorn, Hong Yi Lin, Patanamon Thongtanunam +3

Large Language models (LLMs) have shown strong capabilities in code review automation, such as review comment generation, yet they suffer from hallucinations -- where the generated…

cs.SE2026

Breaking Changes in Software Ecosystems: A Systematic Literature Review

Juntao Chen, Tingting Bi, Yanlin Wang +1

Modern software systems rely on dependency networks of reusable libraries, where breaking changes propagate and cause downstream consumers to fail. Despite growing research across…

cs.SE2026

AI-Assisted Code Review as a Scaffold for Code Quality and Self-Regulated Learning: An Experience Report

Eduardo Oliveira, Michael Fu, Patanamon Thongtanunam +2

Code review is central to software engineering education but hard to scale in capstone projects due to tight deadlines, uneven peer feedback, and limited prior experience. We inves…