Motivation

The complexity of adapting software during runtime has spawned interest in how models can be used to validate, monitor, and adapt runtime behavior. The use of models during runtime extends the use of modeling techniques beyond the design and implementation phases. The goal of this workshop is to look at issues related to developing appropriate model-driven approaches to managing and monitoring the execution of systems. We aim to continue the discussion of research ideas and proposals from researchers who work in relevant areas such as MDE, software architectures, reflection, and autonomic and self-adaptive systems, and provide a "state-of-the-art" research assessment expressed in terms of challenges and achievements.

Models@run.time has to do with runtime models that are built, developed, integrated, and explored in a systematic way on top of their operation.

Objectives

The objectives of this year’s edition of the models@run.time workshop are:

• To foster work on novel topics covering fundamental as well as applied research on models@run.time or, in general, work that attempts to apply model-driven techniques at runtime.
• To bring together researchers from the model-driven software development community of different specialized areas including model evolution, model transformation, model validation and multi-paradigm modeling.
• To discuss the applicability of research results on models@run.time to industrial case studies.

Domains

Papers on models@run.time can relate (but are not limited) to the following domains:

• Machine Learning models: runtime models created by and for machine learning approaches.

• Cyber-physical Systems: hybrid runtime models.

• Digital Twins (DT), DevOps, Microservices, CyberSecurity, Systems of Systems: runtime models to make Innovative Industrial Applications autonomic and self-adaptive

• Business Processes: runtime models of (business) workflows.

• Cloud Computing: runtime models for, e.g., multi-tenant systems.

• Self-modeling: approaches able to create models on-the-fly.

• Self-adaptive and self-organizing systems in general.

Topics

We strongly encourage authors to address the following topics in their papers:

• The causal connection between the system and the runtime model, with particular focus on a transaction concept for this causal connection (timing, roll-back ability, and data consistency).

• Distributed models@run.time, i.e., having multiple, interacting systems, each having an own runtime model.

• Modular models@run.time, i.e., approaches to improve the modularity of models@run.time systems.

• Co-evolving models@run.time, i.e., systematic approaches to synchronize multiple, interacting models@run.time systems.

• No papers on executable models, unless they are causally (bi-)connected to a running system (else consider submitting to the co-located workshop on executable modeling).