The emergence of Large Language Models (LLMs) has opened new opportunities to automate software engineering activities that traditionally require substantial manual effort. Among these, class diagram generation represents a critical yet resource-intensive phase in software design. This paper investigates the capabilities of state-of-the-art LLMs, including GPT-5, Claude Sonnet 4.0, Gemini 2.5 Flash Thinking, and Llama-3.1-8B-Instruct, to generate UML class diagrams from natural language requirements automatically. To evaluate the effectiveness and reliability of LLM-based model generation, we propose a comprehensive dual-validation framework that integrates an LLM-as-a-Judge methodology with human-in-the-loop assessment. Using eight heterogeneous datasets, we apply chain-of-thought prompting to extract domain entities, attributes, and associations, generating corresponding PlantUML representations. The resulting models are evaluated across five quality dimensions: completeness, correctness, conformance to standards, comprehensibility, and terminological alignment. Two independent LLM judges (Grok and Mistral) perform structured pairwise comparisons, and their judgments are further validated against expert evaluations. Our results demonstrate that LLMs can generate structurally coherent and semantically meaningful UML diagrams, achieving substantial alignment with human evaluators. The consistency observed between LLM-based and human-based assessments highlights the potential of LLMs not only as modeling assistants but also as reliable evaluators in automated requirements engineering workflows, offering practical insights into the capabilities and limitations of LLM-driven UML class diagram automation.
Bridging the Gap between User Intent and LLM: A Requirement Alignment Approach for Code Generation
School of Computer Science, Wuhan University（武汉大学计算机学院）；Nanyang Technological University（南洋理工大学）；Institute of Software, Chinese Academy of Sciences（中国科学院软件研究所）；Key Lab of High Confidence Software Technology, MoE (Peking University)（北京大学 教育部高可信软件技术重点实验室）；The University of Hong Kong（香港大学）；Wuhan University（武汉大学）；Peking University（北京大学）
On the Impact of Requirement Smells in LLM-Based Code Generation
fortiss GmbH（fortiss有限公司）；Netlight Consulting（Netlight咨询公司）；Technical University of Munich（慕尼黑工业大学）；Chalmers University of Technology（查尔姆斯理工大学）；Trinity College Dublin（都柏林三一学院）；University of Duisburg-Essen（杜伊斯堡-埃森大学）；Blekinge Institute of Technology（布莱金厄理工学院）
Requirements-Based Test Generation: A Comprehensive Survey
Macau University of Science and Technology（澳门科技大学）；Zhejiang Polytechnic University of Mechanical and Electrical Engineering（浙江机电职业技术学院）；Macau University of Science and Technology Zhuhai MUST Science and Technology Research Institute（澳门科技大学珠海MUST科技研究院）；University of Cincinnati（辛辛那提大学）；University of Nottingham Ningbo China（诺丁汉大学宁波校区）
GraphCodeAgent: Dual Graph-Guided LLM Agent for Retrieval-Augmented Repo-Level Code Generation
School of Computer Science, Wuhan University（武汉大学计算机学院）；Key Lab of High Confidence Software Technology (PKU), Ministry of Education School of Computer Science, Peking University（北京大学计算机科学与技术系教育部高可信软件技术重点实验室）；The University of Hong Kong（香港大学）；College of AI, Tsinghua University（清华大学人工智能学院）；Beihang University（北京航空航天大学）；Institute of Software Chinese Academy of Sciences（中国科学院软件研究所）；Peking University（北京大学）；Academy of Military Sciences（军事科学院）
Benchmarking Requirement-to-Architecture Generation with Hybrid Evaluation
State Key Laboratory of Complex & Critical Software Environment School of Computer Science and Engineering Beihang University, Beijing, China（北京航空航天大学计算机科学与工程学院复杂与关键软件环境国家重点实验室）
Large Language Models for Requirements Engineering: A Cross-Task Empirical Evaluation
University of Limerick（利默里克大学）；Trinity College Dublin (TCD)（都柏林三一学院）；Consiglio Nazionale delle Ricerche (CNR)（意大利国家研究委员会）；University of Padova（帕多瓦大学）；The Open University（开放大学）
State-Aware Generation of Deployable Websites from Visual Prototypes and Requirements
Peking University（北京大学）；Chongqing University（重庆大学）；University of Science and Technology of China（中国科学技术大学）；Harbin Institute of Technology (Shenzhen)（哈尔滨工业大学（深圳））
Explicating Tacit Regulatory Knowledge from LLMs to Auto-Formalize Requirements for Compliance Test Case Generation
Shanghai Key Laboratory of Trustworthy Computing, ECNU（上海可信计算实验室，华东师范大学）；Dishui Lake International Software Engineering Institute, ECNU（迪希湖国际软件工程研究院，华东师范大学）
Model-Driven Discipline for Multi-Agent LLMs: Requirement-to-Verification Generation of Traceable System Models
Lancaster University（兰卡斯特大学）；Tsinghua University（清华大学）；Harbin Institute of Technology（哈尔滨工业大学）；Dalian University of Technology（大连理工大学）；Southeast University（东南大学）；Loughborough University（拉夫堡大学）
