AI and Agile Software Development: From Frustration to Success -- XP2025 Workshop Summary
- URL: http://arxiv.org/abs/2506.20159v2
- Date: Thu, 03 Jul 2025 18:41:06 GMT
- Title: AI and Agile Software Development: From Frustration to Success -- XP2025 Workshop Summary
- Authors: Tomas Herda, Victoria Pichler, Zheying Zhang, Pekka Abrahamsson, Geir K. Hanssen,
- Abstract summary: The workshop culminated in a research roadmap that pinpoints actionable directions for future work.<n>The key outcome is a structured agenda designed to foster joint industry-academic efforts to move from identified frustrations to successful implementation.
- Score: 2.856781525749652
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: The full-day workshop on AI and Agile at XP 2025 convened a diverse group of researchers and industry practitioners to address the practical challenges and opportunities of integrating Artificial Intelligence into Agile software development. Through interactive sessions, participants identified shared frustrations related to integrating AI into Agile Software Development practices, including challenges with tooling, governance, data quality, and critical skill gaps. These challenges were systematically prioritized and analyzed to uncover root causes. The workshop culminated in the collaborative development of a research roadmap that pinpoints actionable directions for future work, including both immediate solutions and ambitious long-term goals. The key outcome is a structured agenda designed to foster joint industry-academic efforts to move from identified frustrations to successful implementation.
Related papers
- Benchmarking Generalizable Bimanual Manipulation: RoboTwin Dual-Arm Collaboration Challenge at CVPR 2025 MEIS Workshop [120.2806035123366]
RoboTwin Dual-Arm Collaboration Challenge was held at the 2nd MEIS Workshop, CVPR 2025.<n>Competitors totally tackled 17 dual-arm manipulation tasks, covering rigid, deformable, and tactile-based scenarios.<n>Report outlines the competition setup, task design, evaluation methodology, key findings and future direction.
arXiv Detail & Related papers (2025-06-29T17:56:41Z) - Report on NSF Workshop on Science of Safe AI [75.96202715567088]
New advances in machine learning are leading to new opportunities to develop technology-based solutions to societal problems.<n>To fulfill the promise of AI, we must address how to develop AI-based systems that are accurate and performant but also safe and trustworthy.<n>This report is the result of the discussions in the working groups that addressed different aspects of safety at the workshop.
arXiv Detail & Related papers (2025-06-24T18:55:29Z) - Greening AI-enabled Systems with Software Engineering: A Research Agenda for Environmentally Sustainable AI Practices [70.24403396375277]
The "Greening AI with Software Engineering" CECAM-Lorentz workshop was held February 3-7, 2025 in Lausanne, Switzerland.<n>This report presents a research agenda emerging from the workshop.<n>It outlines open research directions and practical recommendations to guide the development of environmentally sustainable AI-enabled systems.
arXiv Detail & Related papers (2025-06-02T15:19:49Z) - Challenges and Paths Towards AI for Software Engineering [55.95365538122656]
We discuss progress in AI for software engineering in threefold manner.<n>First, we provide a structured taxonomy of concrete tasks in AI for software engineering.<n>Second, we outline several key bottlenecks that limit current approaches.
arXiv Detail & Related papers (2025-03-28T17:17:57Z) - Collaborative AI in Sentiment Analysis: System Architecture, Data Prediction and Deployment Strategies [3.3374611485861116]
Large language model (LLM) based artificial intelligence technologies have been a game-changer, particularly in sentiment analysis.
However, integrating diverse AI models for processing complex multimodal data and the associated high costs of feature extraction presents significant challenges.
This study introduces a collaborative AI framework designed to efficiently distribute and resolve tasks across various AI systems.
arXiv Detail & Related papers (2024-10-17T06:14:34Z) - Future of Artificial Intelligence in Agile Software Development [0.0]
AI can assist software development managers, software testers, and other team members by leveraging LLMs, GenAI models, and AI agents.
AI has the potential to increase efficiency and reduce the risks encountered by the project management team.
arXiv Detail & Related papers (2024-08-01T16:49:50Z) - Making Software Development More Diverse and Inclusive: Key Themes, Challenges, and Future Directions [50.545824691484796]
We identify six themes around the theme challenges and opportunities to improve Software Developer Diversity and Inclusion (SDDI)<n>We identify benefits, harms, and future research directions for the four main themes.<n>We discuss the remaining two themes, Artificial Intelligence & SDDI and AI & Computer Science education, which have a cross-cutting effect on the other themes.
arXiv Detail & Related papers (2024-04-10T16:18:11Z) - A Survey of Neural Code Intelligence: Paradigms, Advances and Beyond [84.95530356322621]
This survey presents a systematic review of the advancements in code intelligence.<n>It covers over 50 representative models and their variants, more than 20 categories of tasks, and an extensive coverage of over 680 related works.<n>Building on our examination of the developmental trajectories, we further investigate the emerging synergies between code intelligence and broader machine intelligence.
arXiv Detail & Related papers (2024-03-21T08:54:56Z) - Industrial Challenges in Secure Continuous Development [0.7734726150561089]
The intersection between security and continuous software engineering has been of great interest since the early years of the agile development movement.
This paper summarizes a relevant part of our endeavors in which we validated challenges with several practitioners of different roles.
More than framing a set of challenges, we conclude by presenting four key research directions we identified for practitioners and researchers to delineate future work.
arXiv Detail & Related papers (2024-01-12T12:02:16Z) - Human AI Collaboration in Software Engineering: Lessons Learned from a
Hands On Workshop [1.14603174659129]
The study identifies key themes such as the evolving nature of human AI interaction, the capabilities of AI in software engineering tasks, and the challenges and limitations of integrating AI in this domain.
The findings show that while AI, particularly ChatGPT, improves the efficiency of code generation and optimization, human oversight remains crucial, especially in areas requiring complex problem solving and security considerations.
arXiv Detail & Related papers (2023-12-17T06:31:05Z) - ChatDev: Communicative Agents for Software Development [84.90400377131962]
ChatDev is a chat-powered software development framework in which specialized agents are guided in what to communicate.
These agents actively contribute to the design, coding, and testing phases through unified language-based communication.
arXiv Detail & Related papers (2023-07-16T02:11:34Z) - AI for Agile development: a Meta-Analysis [0.0]
This study explores the benefits and challenges of integrating Artificial Intelligence with Agile software development methodologies.
The review helped identify critical challenges, such as the need for specialised socio-technical expertise.
Further research is needed to better understand its impact on processes and practitioners, and to address the indirect challenges associated with its implementation.
arXiv Detail & Related papers (2023-05-14T08:10:40Z) - Artificial Intelligence for IT Operations (AIOPS) Workshop White Paper [50.25428141435537]
Artificial Intelligence for IT Operations (AIOps) is an emerging interdisciplinary field arising in the intersection between machine learning, big data, streaming analytics, and the management of IT operations.
Main aim of the AIOPS workshop is to bring together researchers from both academia and industry to present their experiences, results, and work in progress in this field.
arXiv Detail & Related papers (2021-01-15T10:43:10Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.