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@article{agentic_ai1,
author = {Murugesan, S.},
title = {The Rise of Agentic AI: Implications, Concerns, and the Path Forward},
journal = {IEEE Intelligent Systems},
volume = {40},
number = {2},
pages = {8--14},
month = {March-April},
year = {2025},
doi = {10.1109/MIS.2025.3544940},
keywords = {Industries; Learning (artificial intelligence); Stakeholders; Intelligent systems; Business; Artificial intelligence; Autonomous systems; Decision making}
}
@misc{agentic_ai2,
title = {The Rise of AI Teammates in Software Engineering (SE) 3.0: How Autonomous Coding Agents Are Reshaping Software Engineering},
author = {Hao Li, Haoxiang Zhang, Ahmed E. Hassan},
year = {2025},
eprint = {2507.15003},
archivePrefix = {arXiv},
primaryClass = {cs.SE},
doi = {10.48550/arXiv.2507.15003},
}
@misc{issue-commit-llm,
title = {Back to the Basics: Rethinking Issue-Commit Linking with LLM-Assisted Retrieval},
author = {Huihui Huang and Ratnadira Widyasari and Ting Zhang and Ivana Clairine Irsan and Jieke Shi and Han Wei Ang and Frank Liauw and Eng Lieh Ouh and Lwin Khin Shar and Hong Jin Kang and David Lo},
year = {2025},
eprint = {2507.09199},
archivePrefix = {arXiv},
primaryClass = {cs.SE},
doi = {10.48550/arXiv.2507.09199},
}
@misc{r89,
title = {AI Agentic Programming: A Survey of Techniques, Challenges, and Opportunities},
author = {Wang, Huanting and Gong, Jingzhi and Zhang, Huawei and Xu, Jie and Wang, Zheng},
year = {2025},
eprint = {2508.11126},
archivePrefix = {arXiv},
primaryClass = {cs.SE},
doi = {10.48550/arXiv.2508.11126},
}
@inproceedings{r90,
title = {Coding Agents: A Comprehensive Survey of Automated Bug Fixing Systems and Benchmarks},
author = {Puvvadi, M. and Arava, S. K. and Santoria, A. and Chennupati, S. S. P. and Puvvadi, H. V.},
booktitle = {2025 IEEE 14th International Conference on Communication Systems and Network Technologies (CSNT)},
year = {2025},
address = {Bhopal, India},
pages = {680--686},
doi = {10.1109/CSNT64827.2025.10968728},
keywords = {Surveys;Large language models;Scalability;Semantics;Debugging;Maintenance engineering;Benchmark testing;Software;Software engineering;Context modeling;Agent-Based Models;Automated Program Repair;Large Language Models;Multi-Agent Systems;Context-Aware Debugging;Software Engineering Automation;Debugging Benchmarks;AI in Software Development}
}
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title = {MAGIS: LLM-Based Multi-Agent Framework for GitHub Issue Resolution},
author = {Tao, Wei and Zhou, Yucheng and Wang, Yanlin and Zhang, Wenqiang and Zhang, Hongyu and Cheng, Yu},
booktitle = {Advances in Neural Information Processing Systems 37 (NeurIPS 2024) -- Main Conference Track},
year = {2024},
note = {NeurIPS 2024}
}
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year={2005},
publisher={IEEE}
}
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title={The product backlog},
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title={Version Control with Git: Powerful tools and techniques for collaborative software development},
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title={Populating a release history database from version control and bug tracking systems},
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pages={23--32},
year={2003},
organization={IEEE}
}
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title={When do changes induce fixes?},
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year={2005},
publisher={ACM New York, NY, USA}
}
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title={Software process data quality and characteristics: a historical view on open and closed source projects},
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pages={119--128},
year={2009}
}
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title={The missing links: bugs and bug-fix commits},
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title={Software process data quality and characteristics: a historical view on open and closed source projects},
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}
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}
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}
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pages={121--130},
year={2009}
}
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pages={369--370},
year={2010}
}
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