10 papers
AgenticVulHunter: Bringing Local Agentic Vulnerability Hunting to Your Terminal
Nishant Abhishek, Ping Charoenwet, Kla Tantithamthavorn
Finding vulnerabilities early, before they can affect the production system, is important for reducing the risk of any software attacks. However, detecting vulnerabilities during s…
Documentation Drift in AI-Generated Pull Requests
Will De Michele, Kla Tantithamthavorn
AI coding agents now contribute to software repositories at scale, yet their documentation practices remain uncharacterised. We analyse 29,669 AI-generated pull requests from 2,585…
XAgent: eXecution-guided Agentic AI for Effective Localization and Resolution of GitHub Issues
Hieu Huynh, Patanamon Thongtanunam, Michael Fu +2
Agentic AI has enabled capabilities in leveraging Large Language Models (LLMs) to autonomously resolve repository-level GitHub issues. However, due to the reliance on limited stati…
Requirements-Augmented Generation for Trustworthy Acceptance Testing of LLM-Based Software
Fanyu Wang, Chetan Arora, Zhenping Xie +4
LLM-based software (LBS) integrates large language models as core components to deliver flexible, personalised responses. Unlike traditional software with deterministic outputs, LB…
Towards a Risk Assessment of Malicious Skill Files in Coding Agents
Rui Yang, Michael Fu, Kla Tantithamthavorn +2
Autonomous coding agents are increasingly embedded in enterprise software workflows with delegated authority over connected systems. Central to this architecture is the agent skill…
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…
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…
CodeChat-Eval: Evaluating Large Language Models in Multi-Turn Code Refinement Dialogues
Guoxiang Guo, Kla Tantithamthavorn, Neelofar Neelofar +2
Large Language Models (LLMs) are increasingly used in software engineering to generate and refine code. In practice, developers often continue from an initial code generation reque…
RovoDev Code Reviewer: A Large-Scale Online Evaluation of LLM-based Code Review Automation at Atlassian
Kla Tantithamthavorn, Yaotian Zou, Andy Wong +8
Large Language Models (LLMs)-powered code review automation has the potential to transform code review workflows. Despite the advances of LLM-powered code review comment generation…
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…