Motivations
Model artifacts are subject to constant evolution throughout the lifecycle of systems. The evolutionary pressure emerges from various technical and business factors throughout the overall software/system engineering endeavor. Pertinent examples of such factors include changing requirements, changing environment, and changing user base, all of which give rise to unique evolutionary challenges in various system artifacts from architecture to implementation, and even in informal artifacts, such as documentation. These challenges, if left unmanaged, may lead to deteriorating quality attributes, and in severe cases inconsistent artifacts or even incorrect artifacts, preventing the system from operating as intended. Therefore, proper support for efficient and effective evolution is required.
The Models and Evolution workshop promotes novel theories, techniques, and tools to support evolution. To this end, the workshop brings together researchers and practitioners to discuss the latest developments on the topic.
Topics of Interest
The topics of interest include, but are not restricted to:
Foundations
- Theories, methods, and tools for (meta-)model evolution
- Co-evolution across multiple meta-levels (incl. instance and data levels)
Correctness & Quality
- Correctness and consistency concerns of model evolution
- Verification and validation of evolving MDE artifacts
Applications
- Software migration, reconstruction, reuse, and repurposing
- Evolution of heterogeneous systems, e.g., CPS and digital twins, including the (co-)evolution of virtual and physical artifacts and infrastructure
Empirical & Industry
- Empirical works, industry reports, patterns and catalogs
- Training and education in the area of model evolution
Special Focus 2026: Digital Twins
- Frameworks and theories handling model evolution in Digital Twin models
- Handling verification, consistency, migration and co-evolution of models in the Digital Twin
Evolution in Model-Driven Engineering: From Knowing What Changed to Knowing What to Change
Evolution is a fundamental challenge in model-driven engineering (MDE), affecting models, metamodels, transformations, and the systems and processes built around them. This talk provides an overview of the many facets of evolution in MDE, ranging from linear model evolution and the co-evolution of coupled artifacts to planned changes and configuration management. For selected challenges, we will revisit classical approaches and examine how they can be complemented, extended, or transformed by recent advances in artificial intelligence (AI). In particular, the talk will explore how AI can take us from knowing what changed to knowing what to change, while examining the opportunities and challenges of combining AI with established model-driven techniques.
Gabriele Taentzer
Gabriele Taentzer is Professor at Philipps-Universität Marburg, Germany, where she heads the Software Engineering group. Her research interests include model-driven software engineering, particularly model transformation and evolution, as well as software and data quality assurance. She has served on the organizing committees of several international conferences, as well as on the steering committees of the ETAPS conference “Fundamental Approaches to Software Engineering”, the Automated Software Engineering conference, and the Graph Transformation conference. She is on the editorial board of the journal Software and System Modeling (SoSym). She has been the principal investigator of various research projects, particularly in the DFG priority program “Design For Future – Managed Software Evolution”. She has received several awards, including the ACM SIGSOFT Distinguished Paper Award for her paper “Mutation Testing of Java Bytecode: A Model-Driven Approach”, the SoSym 10-Year Most Influential Paper Award for her paper “Generating Instance Models from Meta Models”, and the SoSym 8-Year Most Influential Theme Section Paper Award for her paper “Analysing Refactoring Dependencies Using Graph Transformation”.
