SDI-homework/references.bib

% references.bib — JC3506 Individual Study
% Topic: Software System Design with Agentic AI
% Cite in text with \cite{key}
%
% 13 primary papers organised by theme:
%   Theme 1 — Foundations & Architectures        (4 papers)
%   Theme 2 — Multi-Agent Systems & Frameworks   (3 papers)
%   Theme 3 — Software Engineering Applications  (3 papers)
%   Theme 4 — Planning, Reasoning & Tool Use     (3 papers)

% -------------------------------------------------------
% THEME 1: Foundations & Architectures of Agentic AI
% -------------------------------------------------------

% Comprehensive 2024 survey — good opening citation for the introduction
@misc{schmidgall2024agentic,
  author        = {Schmidgall, Samuel and others},
  title         = {Agentic AI: A Comprehensive Survey of Architectures, Applications, and Future Directions},
  year          = {2024},
  eprint        = {2510.25445},
  archivePrefix = {arXiv},
  primaryClass  = {cs.AI}
}

% Widely cited foundational survey on LLM-based autonomous agents
@article{wang2024survey,
  author  = {Wang, Lei and Ma, Chen and Feng, Xueyang and Zhang, Zeyu and Yang, Hao and Zhang, Jingsen and Chen, Zhiyuan and Tang, Jiakai and Chen, Xu and Lin, Yankai and Zhao, Wayne Xin and Wei, Zhewei and Wen, Ji-Rong},
  title   = {A Survey on Large Language Model based Autonomous Agents},
  journal = {Frontiers of Computer Science},
  volume  = {18},
  number  = {6},
  pages   = {186345},
  year    = {2024},
  doi     = {10.1007/s11704-024-40231-1}
}

% Taxonomy of agent architectures: Perception, Brain, Planning, Action, Tools
@misc{sun2026architectures,
  author        = {Sun, Yifan and others},
  title         = {Agentic Artificial Intelligence: Architectures, Taxonomies, and Evaluation of Large Language Model Agents},
  year          = {2026},
  eprint        = {2601.12560},
  archivePrefix = {arXiv},
  primaryClass  = {cs.AI}
}

% Covers CrewAI, LangGraph, AutoGen, MetaGPT framework comparison
@misc{sun2025frameworks,
  author        = {Sun, Yifan and others},
  title         = {Agentic AI Frameworks: Architectures, Protocols, and Design Challenges},
  year          = {2025},
  eprint        = {2508.10146},
  archivePrefix = {arXiv},
  primaryClass  = {cs.MA}
}

% -------------------------------------------------------
% THEME 2: Multi-Agent Systems & Coordination
% -------------------------------------------------------

% ACM TOSEM — literature review on LLM multi-agent SE systems (peer-reviewed journal)
@article{ishibashi2024multiagent,
  author  = {Ishibashi, Yoichi and Nishimura, Yoshimasa},
  title   = {{LLM}-Based Multi-Agent Systems for Software Engineering: Literature Review, Vision and the Road Ahead},
  journal = {ACM Transactions on Software Engineering and Methodology},
  year    = {2024},
  doi     = {10.1145/3712003}
}

% IEEE conference — multi-agent LLM environment for software design and refactoring
@INPROCEEDINGS{ieee2025multiagent,
  author={Rajendran, Vasanth and Besiahgari, Dinesh and Patil, Sachin C. and Chandrashekaraiah, Manjunath and Challagulla, Vishnu},
  booktitle={SoutheastCon 2025}, 
  title={A Multi-Agent LLM Environment for Software Design and Refactoring: A Conceptual Framework}, 
  year={2025},
  volume={},
  number={},
  pages={488-493},
  keywords={Software design;Codes;Large language models;Scalability;Software quality;Software systems;Security;Optimization;Software engineering;Software development management;Multi-agent systems;Large Language Models;Software refactoring;Agent specialization;Consensus protocols;Auction mechanisms;Code quality},
  doi={10.1109/SoutheastCon56624.2025.10971563}
}

% IEEE conference — software architecture for LLM-based multi-agent systems (SALLMA)
@INPROCEEDINGS{sallma2025,
  author={Becattini, Marco and Verdecchia, Roberto and Vicario, Enrico},
  booktitle={2025 IEEE/ACM International Workshop New Trends in Software Architecture (SATrends)}, 
  title={SALLMA: A Software Architecture for LLM-Based Multi-Agent Systems}, 
  year={2025},
  volume={},
  number={},
  pages={5-8},
  keywords={Structured Query Language;Software architecture;NoSQL databases;Pressing;Market research;Software;Real-time systems;Faces;Multi-agent systems;Python;software architecture;se4ai;llm},
  doi={10.1109/SATrends66715.2025.00006}
}


% -------------------------------------------------------
% THEME 3: Software Engineering Applications
% -------------------------------------------------------

% Survey of LLM agents across SE tasks: requirements, code gen, design, testing, maintenance
@misc{liu2024llmagents,
  author        = {Liu, Junwei and others},
  title         = {From {LLMs} to {LLM}-based Agents for Software Engineering: A Survey of Current, Challenges and Future},
  year          = {2024},
  eprint        = {2408.02479},
  archivePrefix = {arXiv},
  primaryClass  = {cs.SE}
}

% 124-paper survey from both SE and agent perspectives
@misc{yang2024llmse,
  author        = {Yang, Junwei and others},
  title         = {Large Language Model-Based Agents for Software Engineering: A Survey},
  year          = {2024},
  eprint        = {2409.02977},
  archivePrefix = {arXiv},
  primaryClass  = {cs.SE}
}

% SWE-bench — seminal benchmark for evaluating agents on real GitHub issues
@misc{jimenez2024swebench,
  author        = {Jimenez, Carlos E. and Yang, John and Wettig, Alexander and Yao, Shunyu and Pei, Kexin and Press, Ofir and Narasimhan, Karthik},
  title         = {{SWE}-bench: Can Language Models Resolve Real-World {GitHub} Issues?},
  year          = {2024},
  eprint        = {2310.06770},
  archivePrefix = {arXiv},
  primaryClass  = {cs.SE}
}

% -------------------------------------------------------
% THEME 4: Planning, Reasoning & Tool Use
% -------------------------------------------------------

% Surveys reasoning, planning, tool-calling patterns across agent architectures
@misc{masterman2024landscape,
  author        = {Masterman, Tula and Besen, Sandi and Sawtell, Mason and Chao, Alex},
  title         = {The Landscape of Emerging AI Agent Architectures for Reasoning, Planning, and Tool Calling: A Survey},
  year          = {2024},
  eprint        = {2404.11584},
  archivePrefix = {arXiv},
  primaryClass  = {cs.AI}
}

% Generative agents — foundational simulation of autonomous agent behaviour (UIST 2023)
@inproceedings{park2023generative,
  author    = {Park, Joon Sung and O'Brien, Joseph C. and Cai, Carrie J. and Morris, Meredith Ringel and Liang, Percy and Bernstein, Michael S.},
  title     = {Generative Agents: Interactive Simulacra of Human Behavior},
  booktitle = {Proceedings of the 36th Annual ACM Symposium on User Interface Software and Technology (UIST '23)},
  year      = {2023},
  doi       = {10.1145/3586183.3606763}
}

% AI agentic programming: planning, memory, tool integration, execution monitoring
@misc{chen2025agentic,
  author        = {Chen, Jiannan and others},
  title         = {AI Agentic Programming: A Survey of Techniques, Challenges, and Opportunities},
  year          = {2025},
  eprint        = {2508.11126},
  archivePrefix = {arXiv},
  primaryClass  = {cs.SE}
}