AI for Agile development: a Meta-Analysis
Not on the map. Why?
Abstract (arXiv)
This study explores the benefits and challenges of integrating Artificial Intelligence with Agile software development methodologies, focusing on improving continuous integration and delivery. A systematic literature review and longitudinal meta-analysis of the retrieved studies was conducted to analyse the role of Artificial Intelligence and it's future applications within Agile software development. The review helped identify critical challenges, such as the need for specialised socio-technical expertise. While Artificial Intelligence holds promise for improved software development practices, further research is needed to better understand its impact on processes and practitioners, and to address the indirect challenges associated with its implementation.
Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 8 of its 39 references that are in the map. First posted on arXiv 14 May 2023.
Builds on
8 of 39 references.
References · 8
- 2021On the Opportunities and Risks of Foundation Modelscited by 3,961
- 2018Safely Entering the Deep: A Review of Verification and Validation for Machine Learning and a Challenge Elicitation in the Automotive Industrycited by 38
- 2021Who Needs MLOps: What Data Scientists Seek to Accomplish and How Can MLOps Help?cited by 37
- 2023Towards Human-Bot Collaborative Software Architecting with ChatGPTcited by 31
- 2022A Survey on Machine Learning-based Misbehavior Detection Systems for 5G and Beyond Vehicular Networkscited by 11
- 2021MLOps Challenges in Multi-Organization Setup: Experiences from Two Real-World Casescited by 10
- 2018Predictive Test Selectioncited by 8
- 2022DASP: A Framework for Driving the Adoption of Software Security Practicescited by 2
Built on by
Citing papers per year: 2025: 1.
1 paper.