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Requirements Engineering Challenges in Building AI-Based Complex Systems

arXiv 1908.11791 ↗First posted 30 Aug 2019cs.SEcited by 21

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Abstract (arXiv)

This paper identifies and tackles the challenges of the requirements engineering discipline when applied to development of AI-based complex systems. Due to their complex behaviour, there is an immanent need for a tailored development process for such systems. However, there is still no widely used and specifically tailored process in place to effectively and efficiently deal with requirements suitable for specifying a software solution that uses machine learning. By analysing the related work from software engineering and artificial intelligence fields, potential contributions have been recognized from agent-based software engineering and goal-oriented requirements engineering research, as well as examples from large product development companies. The challenges have been discussed, with proposals given how and when to tackle them. RE4AI taxonomy has also been outlined, to inform the tailoring of development process.

Key facts. Cited by 21 papers in the map (data through 7 Oct 2026). First posted on arXiv 30 Aug 2019.

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Citing papers per year: 2021: 3; 2022: 3; 2023: 2; 2024: 5; 2025: 4; 2026: 4.

21 papers.

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  1. 2021Software Engineering for AI-Based Systems: A Surveycited by 68
  2. 2021Characterizing Technical Debt and Antipatterns in AI-Based Systems: A Systematic Mapping Studycited by 21
  3. 2022Management of Machine Learning Lifecycle Artifacts: A Surveycited by 13
  4. 2022Requirements Engineering for Machine Learning: A Review and Reflectioncited by 7
  5. 2023Requirements Engineering Framework for Human-centered Artificial Intelligence Software Systemscited by 7
  6. 2024Artificial Intelligence in Industry 4.0: A Review of Integration Challenges for Industrial Systemscited by 5
  7. 2024How Mature is Requirements Engineering for AI-based Systems? A Systematic Mapping Study on Practices, Challenges, and Future Research Directionscited by 5
  8. 2024A Catalog of Fairness-Aware Practices in Machine Learning Engineeringcited by 4
  9. 2021Pairing Conceptual Modeling with Machine Learningcited by 3
  10. 2022RESAM: Requirements Elicitation and Specification for Deep-Learning Anomaly Models with Applications to UAV Flight Controllerscited by 3
  11. 2023MLOps Spanning Whole Machine Learning Life Cycle: A Surveycited by 3
  12. 2025Engineering the Law-Machine Learning Translation Problem: Developing Legally Aligned Modelscited by 2
9 more
  1. 2024The Impact of Environment Configurations on the Stability of AI-Enabled Systemscited by 0
  2. 2024How to Measure Human-AI Prediction Accuracy in Explainable AI Systemscited by 0
  3. 2025Improving Requirements Classification with SMOTE-Tomek Preprocessingcited by 0
  4. 2025Data Requirement Goal Modeling for Machine Learning Systemscited by 0
  5. 2025Reconsidering Requirements Engineering: Human-AI Collaboration in AI-Native Software Developmentcited by 0
  6. 2026From Goals to Aspects, Revisited: An NFR Pattern Language for Agentic AI Systemscited by 0
  7. 2026Persona-Based Requirements Engineering for Explainable Multi-Agent Educational Systems: A Scenario Simulator for Clinical Reasoning Trainingcited by 0
  8. 2026From AI Technical Debt to Agentic Technical Debt: A Systematic Mapping of Root Causes and Manifestations in Agentic AI Systemscited by 0
  9. 2026Software Engineering for AI-driven Building Operationcited by 0