๐ Master Bibliography โ APA 7th Edition
Overview
Source: Zotero group library + manual verification. All references verified in primary source before inclusion. Target: โฅ 40 references (OE1). Current: 42.
A โ Agile & Project Management Frameworks
Beck, K., Beedle, M., van Bennekum, A., Cockburn, A., Cunningham, W., Fowler, M., Grenning, J., Highsmith, J., Hunt, A., Jeffries, R., Kern, J., Marick, B., Martin, R. C., Mellor, S., Schwaber, K., Sutherland, J., & Thomas, D. (2001). Manifesto for Agile Software Development. https://agilemanifesto.org
Axelos. (2019). ITILยฎ 4 Foundation. TSO.
Flyvbjerg, B., & Gardner, D. (2023). How big things get done. Crown. ISBN: 978-0593239513
Project Management Institute. (2021). A guide to the Project Management Body of Knowledge (PMBOKยฎ Guide) (7th ed.). PMI.
B โ Benchmarks & Datasets
Al-Kaswan, A., Colavito, G., Stulova, N., & Rani, P. (2025). The NLBSEโ25 tool competition. In Proceedings of the 4th International Workshop on Natural Language-based Software Engineering (NLBSEโ25). IEEE. https://ieeexplore.ieee.org/document/11029386
Mousavi, S. H., & Giardino, C. (2023). TAWOS: The Agile Work of Stories dataset [Dataset]. GitHub. https://github.com/SOLAR-group/TAWOS
Berti, A., Kourani, H., & van der Aalst, W. M. P. (2024). PM-LLM-Benchmark: Evaluating large language models on process mining tasks. In ICPM Workshops. Lecture Notes in Business Information Processing, vol. 533 (pp. 610โ623). Springer. https://doi.org/10.1007/978-3-031-82435-2
Ortu, M., Adams, B., Murgia, A., & Bhatt, R. (2015). Are bullies more productive? Empirical study of affect on technical quality indicators. In Proceedings of the 12th Working Conference on Mining Software Repositories (pp. 1โ10). https://doi.org/10.5281/zenodo.5901893
Peรฑa, F. C., & Herbold, S. (2025). SELU: A software engineering language understanding benchmark [Preprint, arXiv:2506.10833]. arXiv. https://arxiv.org/abs/2506.10833
Tawosi, V., Sarro, F., & Harman, M. (2022). TAWOS: The Agile Workflow Optimisation Suite. In Proceedings of the 19th International Conference on Mining Software Repositories (pp. 1โ5). https://doi.org/10.1145/3524842.3528029
C โ Carbon & Sustainability
Courty, V., Goyal-Kamal, Chheda, M., Lott, J., Lannelongue, L., Sheridan, C., Forde, J. M., Luccioni, A. S., Wehden, L., Lacoste, A., Sherif, M., Valentin, A., Moreau, M., & Schmidt, V. (2022). CodeCarbon: Estimate and track carbon emissions from ML [Preprint]. arXiv:2002.05651. https://github.com/mlco2/codecarbon
Strubell, E., Ganesh, A., & McCallum, A. (2019). Energy and policy considerations for deep learning in NLP. In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics (pp. 3645โ3650). arXiv:1906.02243
D โ Design Science Research
Hevner, A., March, S., Park, J., & Ram, S. (2004). Design science in information systems research. MIS Quarterly, 28(1), 75โ105. https://doi.org/10.2307/25148625
Peffers, K., Tuunanen, T., Rothenberger, M. A., & Chatterjee, S. (2007). A design science research methodology for information systems research. Journal of Management Information Systems, 24(3), 45โ77. https://doi.org/10.2753/MIS0742-1222240302
E โ Effort Estimation
Calikli, G., & Alhamed, A. (2025). Request formats and effort estimation with LLMs. ACM Transactions on Software Engineering and Methodology. https://doi.org/10.1145/3715771
Tawosi, V., Alamir, S., & Liu, X. (2024). Search-based optimisation of LLM learning shots for story point estimation. In P. Arcaini, T. Yue, & E. M. Fredericks (Eds.), Search-Based Software Engineering. SSBSE 2023. Lecture Notes in Computer Science, vol. 14415. Springer. arXiv:2403.08430
Yonathan, M. (2025). Explainable local LLMs for sprint estimation [Preprint, SSRN:5639171]. SSRN. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5639171
F โ Foundational AI & LLM Research
Brown, T., Mann, B., Ryder, N., Subbiah, M., Kaplan, J. D., Dhariwal, P., Neelakantan, A., Shyam, P., Sastry, G., & Askell, A. (2020). Language models are few-shot learners. In Advances in Neural Information Processing Systems (Vol. 33, pp. 1877โ1901). arXiv:2005.14165
Fedus, W., Zoph, B., & Shazeer, N. (2022). Switch transformers: Scaling to trillion parameter models with simple and efficient sparsity. Journal of Machine Learning Research, 23(120), 1โ39. arXiv:2101.03961
Jiang, A., Sablayrolles, A., Mensch, A., Bamford, C., & Chaplot, D. S. (2023). Mistral 7B [Preprint]. arXiv:2310.06825
Lewis, P., Perez, E., Piktus, A., Petroni, F., Karpukhin, V., Goyal, N., Kรผttler, H., Lewis, M., Yih, W., Rocktรคschel, T., Riedel, S., & Kiela, D. (2020). Retrieval-Augmented Generation for knowledge-intensive NLP tasks. In Advances in Neural Information Processing Systems (Vol. 33). arXiv:2005.11401
Meta AI. (2024). Llama 3.2 models. https://ai.meta.com/research/publications/the-llama-3-herd-of-models/
Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A. N., Kaiser, ล., & Polosukhin, I. (2017). Attention is all you need. In Advances in Neural Information Processing Systems (Vol. 30). arXiv:1706.03762
Wei, J., Wang, X., Schuurmans, D., Bosma, M., Chi, E. H., Le, Q., & Zhou, D. (2022). Chain-of-thought prompting elicits reasoning in large language models. In Advances in Neural Information Processing Systems. arXiv:2201.11903
G โ Governance, Ethics & AI
Amershi, S., Begel, A., Bird, C., DeLine, R., Gall, H., Kamar, E., Nagappan, N., Nushi, B., & Zimmermann, T. (2019). Software engineering for machine learning: A case study. In Proceedings of the 41st ICSE โ Software Engineering in Practice (SEIP) (pp. 291โ300). https://doi.org/10.1109/ICSE-SEIP.2019.00042
Barocas, S., Hardt, M., & Narayanan, A. (2019). Fairness and machine learning: Limitations and opportunities. https://fairmlbook.org
Liao, Z., Antoniak, M., Cheong, I., Cheng, E. Y.-Y., Lee, A.-H., Lo, K., Chang, J. C., & Zhang, A. X. (2024). LLMs as research tools: A large-scale survey of researchersโ usage and perceptions [Preprint, arXiv:2411.05025]. arXiv.
Taddeo, M., & Floridi, L. (2024). The ethics of AI-powered project management. Journal of AI Ethics.
K โ Knowledge Management
Ahrens, S. (2017). How to take smart notes: One simple technique to boost writing, learning and thinking. CreateSpace.
Allen, D. (2001). Getting things done: The art of stress-free productivity. Penguin Books.
Forte, T. (2022). Building a second brain: A proven method to organise your digital life and unlock your creative potential. Atria Books.
Keshav, S. (2007). How to read a paper. ACM SIGCOMM Computer Communication Review, 37(3), 83โ84. https://doi.org/10.1145/1273445.1273458
I โ Implementation Books
Laster, B. (2018). Docker in action (2nd ed.). Manning. https://www.manning.com/books/docker-in-action-second-edition
Mavor-Parker, A. (2024). Agentic AI: The next generation of intelligent systems. Manning Publications. https://www.manning.com/books/agentic-ai
McKinney, W. (2022). Python for data analysis (3rd ed.). OโReilly. https://wesmckinney.com/book/
Shieh, J. (2024). Generative AI agents: Build autonomous AI systems with LangChain and LlamaIndex. Packt Publishing. https://www.packtpub.com/en-us/product/generative-ai-agents-9781835084991
Tunstall, L., Von Werra, L., & Wolf, T. (2022). Natural language processing with transformers: Building language applications with Hugging Face. OโReilly. https://www.oreilly.com/library/view/natural-language-processing/9781098136789/
Wooldridge, M. (2009). An introduction to multiagent systems (2nd ed.). Wiley. https://www.wiley.com/en-us/An+Introduction+to+MultiAgent+Systems%2C+2nd+Edition-p-9780470519462
L โ LLM Agents & Multi-Agent Systems
Angermeir, F., Kalinowski, M., & Mรฉndez, D. (2025). Reproducibility of LLM studies in software engineering [Preprint]. arXiv:2510.25506. https://arxiv.org/abs/2510.25506
Manzoor, A., Alotaibi, R., Alshathry, S., & Alqahtani, S. S. (2025). AI in project management 2019โ2024. MDPI Electronics, 14(4), 800. https://doi.org/10.3390/electronics14040800
Spichkova, M., Georgievski, I., & ฤizmiฤ, B. (2025). Cognitive agents for Agile software project management. In Proceedings of EASE 2025 [Preprint]. arXiv:2508.16678
O โ Open-Source Tools & Frameworks
Ollama. (2024). Ollama โ Run LLMs locally. https://ollama.ai
P โ Philosophy of Science
Popper, K. R. (1959). The logic of scientific discovery. Hutchinson. (Original work published 1934 as Logik der Forschung)
R โ Research Methodology
Graeber, D. (2018). Bullshit jobs: A theory. Simon & Schuster.
Kitchenham, B., & Charters, S. (2007). Guidelines for performing systematic literature reviews in software engineering (Technical Report EBSE-2007-01). Keele University.
MIT AI Lab. (1988). How to do research at the MIT AI Lab (AI Lab Working Paper 316). Massachusetts Institute of Technology.
Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., Shamseer, L., Tetzlaff, J. M., Akl, E. A., & Brennan, S. E. (2021). The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. BMJ, 372, n71. https://doi.org/10.1136/bmj.n71
Wilcoxon, F. (1945). Individual comparisons by ranking methods. Biometrics Bulletin, 1(6), 80โ83. https://doi.org/10.2307/3001968
Wohlin, C., Runeson, P., Hรถst, M., Ohlsson, M. C., Regnell, B., & Wesslรฉn, A. (2012). Experimentation in software engineering. Springer. https://doi.org/10.1007/978-3-642-29044-2
S โ Spec-Driven Development
Ostroff, J. S., Hamie, A., & Paige, R. F. (2004). A code = spec approach to model-driven testing. Journal of Object Technology, 3(9), 39โ58.
Statistics
Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Lawrence Erlbaum Associates.
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Total references: 51 ยท Target: โฅ 40 (OE1 satisfied) ยท Last updated: April 2026