TraceLLM: Leveraging Large Language Models with Prompt Engineering for Enhanced Requirements Traceability
KFUPM（国王法赫德石油矿物大学）；Imam Abdulrahman Bin Faisal University（伊玛目阿卜杜勒拉赫曼·本·费萨尔大学）；SDAIA–KFUPM Joint Research Center of Artificial Intelligence, KFUPM（沙特数据与人工智能中心-国王法赫德石油矿物大学人工智能联合研究中心）；University of Quebec in Montreal（蒙特利尔魁北克大学）
Requirements traceability, the process of establishing and maintaining relationships between requirements and various software development artifacts, is paramount for ensuring system integrity and fulfilling requirements throughout the Software Development Life Cycle (SDLC). Traditional methods, including manual and information retrieval models, are labor-intensive, error-prone, and limited by low precision. Recently, Large Language Models (LLMs) have demonstrated potential for supporting software engineering tasks through advanced language comprehension. However, a substantial gap exists in the systematic design and evaluation of prompts tailored to extract accurate trace links. This paper introduces TraceLLM, a systematic framework for enhancing requirements traceability through prompt engineering and demonstration selection. Our approach incorporates rigorous dataset splitting, iterative prompt refinement, enrichment with contextual roles and domain knowledge, and evaluation across zero- and few-shot settings. We assess prompt generalization and robustness using eight state-of-the-art LLMs on four benchmark datasets representing diverse domains (aerospace, healthcare) and artifact types (requirements, design elements, test cases, regulations). TraceLLM achieves state-of-the-art F2 scores, outperforming traditional IR baselines, fine-tuned models, and prior LLM-based methods. We also explore the impact of demonstration selection strategies, identifying label-aware, diversity-based sampling as particularly effective. Overall, our findings highlight that traceability performance depends not only on model capacity but also critically on the quality of prompt engineering. In addition, the achieved performance suggests that TraceLLM can support semi-automated traceability workflows in which candidate links are reviewed and validated by human analysts.
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）
An Empirical Study on the Impact of Normalized Use-Case Specifications on Traceability
College of Computer Science and Technology, National University of Defense Technology（国防科技大学计算机学院）；State Key Laboratory of Complex & Critical Software Environment（复杂与关键软件环境国家重点实验室）
ModelWriter: Text & Model-Synchronized Document Engineering Platform
Wageningen University and Research Centre（瓦赫宁根大学及研究中心）；CNRS（法国国家科学研究中心）；Airbus Group Innovations（空客集团创新中心）；UNIT Information Technologies R&D Ltd.（UNIT信息技术研发有限公司）；Ege University（埃杰大学）；KoçSistem Information and Communication Services Inc.（科克系统信息通信服务公司）；OBEO（奥比欧公司）
Classifier or Prompt: A Case Study on Legal Requirements Traceability
University of Ottawa（渥太华大学）；University of Luxembourg（卢森堡大学）；Monash University（蒙纳士大学）；Lero Research Ireland centre for Software Research（Lero爱尔兰软件研究中心）；University of Limerick（利默里克大学）
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）
From Prompting to Engineering: A Research Agenda for Prompt Engineering in Software Engineering
Universitat Politècnica de Catalunya（加泰罗尼亚理工大学）；CNR（意大利国家研究委员会）；Pegaso University（佩加索大学）；University of Gothenburg and Chalmers University of Technology（哥德堡大学与查尔姆斯理工大学）；Politecnico di Torino（都灵理工大学）；University of Glasgow（格拉斯哥大学）；Tampere University（坦佩雷大学）
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）
ROS-related Robotic Systems Development with V-model-based Application of MeROS Metamodel
Warsaw University of Technology, Institute of Control（华沙技术大学控制学院）；Warsaw University of Technology, Institute of Computer Science（华沙技术大学计算机科学学院）；Industrial Research Institute for Automation（自动化与测量工业研究院）；Ukrainian Catholic University, Applied Science Faculty（乌克兰天主教大学应用科学学院）
