The 1st Workshop on Generative AI and Variability (GAIV 2026) invites high-quality contributions from researchers and practitioners in software engineering, artificial intelligence, and related disciplines, focusing on the intersection of generative AI (GenAI) and variability-intensive systems.
As configurable systems and GenAI technologies rapidly evolve, their interaction raises new opportunities and challenges: GenAI can automate variability engineering tasks, while variability introduces complexity in AI pipelines, prompts, and generated artifacts. GAIV provides a dedicated forum to explore this emerging research space and foster collaboration between the variability and AI-in-SE communities.
Feature model extraction, completion, and synthesis
LLM-assisted configuration and decision support
Automated SPL migration and reengineering
GenAI-supported testing, analysis, and debugging
Documentation and traceability generation
Domain modeling and ontology extraction
Variability in prompts, parameters, and outputs
Product line techniques for AI pipelines and model families
Reuse of AI components across variants
Consistency and traceability of generated artifacts
Feature modeling for AI configuration spaces
Testing and quality assurance of AI-based systems
Empirical studies and evaluations
Human–AI collaboration
Industrial experience reports
Ethical, legal, and quality aspects
The important dates for the workshop align with the general workshop due dates for VARIABILITY 2026.
Workshop papers submission: Mon., Jun 15th 2026 Tue., June 30th 2026
Workshop papers notifications: Tue., July 07th 2026 Wed., July 15th 2026
Final paper submission: Tue., July 14th 2026 Fri., July 31th 2026
Workshop: Tue., September 29th 2026
All submission and notification times are AoE.
Authors interested in participating in the workshop are requested to submit either:
Regular papers (max. 16 pages including references) that present original research, lessons learned, or a well-argued vision-related (but not limited) to the topics on variability modeling languages.
Short papers (max. 9 pages including references) that describe sound new ideas and concepts under research or experimental studies.
Tool papers (max. 9 pages including references) that describe a novel tool or a sufficient increment of an existing tool targeting variability modeling languages.
Please use EasyChair to submit your work to the SPLC 2026's Workshop on Generative AI and Variability track.
Papers must use the Springer LNCS template according to: https://www.springer.com/gp/computer-science/lncs/conference-proceedings-guidelines
Springer provides author guidelines that should be consulted for further details: https://resource-preview-cms.springernature.com/springer-cms/rest/v1/content/19242230/data/v17
All papers must be original and not under review elsewhere. Submissions will be single-blind and reviewed by at least three experts. Submissions will be evaluated based on their novelty, relevance, rigor, transparency, and presentation. Accepted papers will appear in the VARIABILITY 2026 Proceedings published as a Springer LNCS volume.
Martin Becker
Kristof Meixner
Kentaro Yoshimura
Klaus Schmid, University of Hildesheim
Kevin Feichtinger, Karlsruhe Institute of Technology
For further questions about the workshop, feel free to contact the workshop organizers: Martin Becker, Kristof Meixner, Kentarou Yoshimura