Important Dates
- Submissions deadline: 1 November 2026
- Publication: August 2027
Artificial intelligence is rapidly transforming the software engineering discipline. All aspects of the software lifecycle are changing in this AI-native era, from AI proxies for customer needs, to generative coding platforms, to AI-dependent DevOps.
This special issue invites high-quality original research and visionary perspectives that explore how AI reshapes software engineering principles, processes, and organizations. We will examine both opportunities and challenges emerging from this transformation, including implications for reliability, security, ethics, sustainability, education, and human roles in software development.
Contributions should offer novel insights, empirical studies, frameworks, or practical experiences that advance understanding of software engineering in an AI-native world.
Topics of interest include:
Suggested topics include, but are not limited to:
- AI-native software development processes, including requirements, design, coding, testing, deployment, maintenance, and evolution.
- Generative AI for code synthesis, transformation, refactoring, documentation, and repair.
- AI-assisted testing, debugging, verification, validation, and program analysis.
- Reliability, trustworthiness, quality assurance, and evaluation of AI-native software pipelines.
- Benchmarks, metrics, and empirical methods for measuring AI-native software engineering practices.
- Human-AI collaboration in software development, including pair programming, code review, decision-making, and developer experience.
- Agentic software engineering environments, including coding agents, review agents, DevOps agents, and autonomous maintenance workflows.
- Security, privacy, provenance, and software supply-chain risks in AI-based software pipelines.
- Ethics, accountability, governance, licensing, attribution, and intellectual property in AI-assisted development.
- Software engineering for AI systems, including MLOps, data pipelines, model lifecycle management, monitoring, and compliance.
- Architecture, design patterns, technical debt, and maintainability in AI-native systems.
- Evolution of developer roles, skills, education, assessment, and professional practice.
- Open source, community governance, and maintainer practices in AI-native development.
- Case studies from industry, government, open source, education, and large-scale deployments.
- Sustainability, energy use, cost, and environmental impact of AI-native development.
Submission Guidelines:
For author information and guidelines on submission criteria, visit the Author’s Information Page. Please submit papers through the IEEE Author Portal and be sure to select the special issue or special section name. Manuscripts should not be published or currently submitted for publication elsewhere. Please submit only full papers intended for review, not abstracts.
Articles should clearly describe the contribution, methodology, and implications for the future of software engineering. Research papers and experience reports are encouraged. All submissions will undergo peer review consistent with the editorial standards of Computer Magazine.
Guest Editors
- Ron Vetter, University of North Carolina Wilmington, USA
- Lucas Layman, University of North Carolina Wilmington, USA
- George K. Thiruvathukal, Loyola University Chicago, USA
Contact Information
For inquiries regarding this special issue, please contact:
