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cs.SE2026
CAM: A Causality-based Analysis Framework for Multi-Agent Code Generation Systems
Zongyi Lyu, Zhenlan Ji, Songqiang Chen +4
Despite the remarkable success that Multi-Agent Code Generation Systems (MACGS) have achieved, the inherent complexity of multi-agent architectures produces substantial volumes of…
cs.SE2025
Understanding and Bridging the Planner-Coder Gap: A Systematic Study on the Robustness of Multi-Agent Systems for Code Generation
Zongyi Lyu, Songqiang Chen, Zhenlan Ji +5
Multi-agent systems (MASs) have emerged as a promising paradigm for automated code generation, demonstrating impressive performance on established benchmarks. Despite their prosper…
cs.SE2024
How Multi-Modal LLMs Reshape Visual Deep Learning Testing? A Comprehensive Study Through the Lens of Image Mutation
Liwen Wang, Yuanyuan Yuan, Ao Sun +4
Visual deep learning (VDL) systems have shown significant success in real-world applications like image recognition, object detection, and autonomous driving. To evaluate the relia…