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Understanding How Enterprises Adopt the Model Context Protocol for LLM-Driven Software Engineering
Kehui Chen, Yicheng Sun, Jacky Keung +2
Large Language Models (LLMs) are increasingly used in AI-based software engineering, but their limitations in complex task execution and multi-tool coordination have driven growing…
R2Code: A Self-Reflective LLM Framework for Requirements-to-Code Traceability
Yifei Wang, Jacky Keung, Xiaoxue Ma +3
Accurate requirement-to-code traceability is crucial for software maintenance. However, existing IR- and embedding-based methods are heavily dependent on lexical similarity, often…
FedLAD: A Modular and Adaptive Testbed for Federated Log Anomaly Detection
Yihan Liao, Jacky Keung, Zhenyu Mao +2
Log-based anomaly detection (LAD) is critical for ensuring the reliability of large-scale distributed systems. However, most existing LAD approaches assume centralized training, wh…
Chart2Code-MoLA: Efficient Multi-Modal Code Generation via Adaptive Expert Routing
Yifei Wang, Jacky Keung, Zhenyu Mao +2
Chart-to-code generation is a critical task in automated data visualization, translating complex chart structures into executable programs. While recent Multi-modal Large Language…
Towards Requirements Engineering for GenAI-Enabled Software: Bridging Responsibility Gaps through Human Oversight Requirements
Zhenyu Mao, Jacky Keung, Yicheng Sun +3
Context: Responsibility gaps, long-recognized challenges in socio-technical systems where accountability becomes diffuse or ambiguous, have become increasingly pronounced in GenAI-…
Towards Engineering Multi-Agent LLMs: A Protocol-Driven Approach
Zhenyu Mao, Jacky Keung, Fengji Zhang +3
The increasing demand for software development has driven interest in automating software engineering (SE) tasks using Large Language Models (LLMs). Recent efforts extend LLMs into…