"Emerging Trends and Challenges Toward LLM Agents in Static Analysis," by Hoang-Quoc-Bao Hua and Dr. Xuan-Bach Le, was published at IEA/AIE 2026 in Kuala Lumpur, Malaysia, July 2026, and nominated for the Best Paper Award. Static analysis remains central to software reliability and security, but it keeps running into the same three problems: too many false positives, rigid rule sets, and limited ability to reason about semantic context. LLM-based agents look promising as a complement, bringing autonomous reasoning and verification into the analysis pipeline. The paper introduces a taxonomy that organises these agents along four dimensions: architecture, integration patterns, grounding mechanisms, and application domains. The framework captures how agents are structured, where they intervene in existing workflows, how they validate their own output, and which tasks they address — from defect detection and code maintenance through to security auditing. The authors also examine current evaluation practice and surface the major limitations around reliability and scalability. Paper: https://lexuanbach.github.io/publication/IEA2026c.pdf Slides: https://lexuanbach.github.io/slides/IEA2026c_slides.pdf DOI: https://doi.org/10.1007/978-981-92-2885-0_9