6 papers
Agent-Callable Feature Coverage: Measuring Software Readiness for AI Agents
Zedong Peng
AI agents already operate graphical software through screenshot-based computer use, so the pressing question is not whether agents can operate software, but how well software suppo…
Evaluating and Improving Pedagogical Fit in LLM-Based AI Tutors with the Pedagogical Suitability Index
Benjamin Barlog, Hudson Craig, Zedong Peng
Large language models (LLMs) are increasingly used as AI tutors, but a correct answer is not always a pedagogically appropriate one. In classroom learning, effective help depends n…
When Post-Anchor Metrics Fail: Stabilization Regimes in AI-Evidence Open-Source Projects
Hudson Craig, Benjamin Barlog, Chenggang Wang +2
Repository mining studies increasingly analyze AI-evidence projects, yet it remains unclear how to measure whether architectural changes create deferred stabilization obligations.…
Cross-Cutting Security Analysis of LLM-Generated Code via Metamorphic Testing and Association Rule Mining
Zedong Peng, Chenggang Wang, Shangyue Zhu
Large language models (LLMs) frequently generate code with security vulnerabilities, yet these weaknesses are rarely isolated: they often span multiple concern areas simultaneously…
Failure-Aware Enhancements for Large Language Model (LLM) Code Generation: An Empirical Study on Decision Framework
Jianru Shen, Zedong Peng, Lucy Owen
Large language models (LLMs) show promise for automating software development by translating requirements into code. However, even advanced prompting workflows like progressive pro…
Advanced Vulnerability Scanning for Open Source Software: Detection and Mitigation of Log4j Vulnerabilities
Victor Wen, Zedong Peng
Automated detection of software vulnerabilities remains a critical challenge in software security. Log4j is an industrial-grade Java logging framework listed as one of the top 100…