Workshop on Models and Evolution

Co-located with ACM/IEEE 20th International Conference on Model Driven Engineering Languages and Systems.

Austin, Texas, Sept 18, 2017.

The 11th Workshop on Models and Evolution (ME 2017) is a satellite event at ACM/IEEE 20th International Conference on Model Driven Engineering Languages and Systems. It addresses the evolution of artefacts of the modelling process, as inspired by analogous evolution required by software artefacts, with input from academic as well as industrial practice.

With the increasing use of Model-Based Development in many domains (e.g., Automotive Software Engineering, Business Process Engineering), models are starting to become core artefacts of modern software engineering processes. By raising the level of abstraction and using concepts closer to the problem and application domain rather than the solution and technical domain, models become core assets and reusable intellectual property, being worth the effort of maintaining and evolving them. Therefore, increasingly models experience the same issues as traditional software artefacts, i.e., being subject to many kinds of changes, which range from rapidly evolving platforms to the evolution of the functionality provided by the applications developed. These modifications include changes at all levels, from requirements through architecture and design, to executable models, documentation and test suites. They typically affect various kinds of models including data models, behavioural models, domain models, source code models, goal models, etc. Coping with and managing the changes that accompany the evolution of software assets is therefore an essential aspect of Software Engineering as a discipline.

Topics

Contributions are solicited on all aspects of models and evolution, its foundations, practices and technologies. In particular, we encourage submissions from both academia and industry about the following (non-exhaustive) list of topics:

• Formalisms, theories, formal approaches, methods and languages for expressing and understanding model-driven software evolution
• Supporting processes and tools for managing model-driven software evolution
• (Co-)evolution and (co-)adaptation of models, meta-models and modeling languages; classification of (co-)evolution scenarios
• Conformance checking, inconsistency management, synchronization, differencing, comparison, impact analysis of evolving models
• Transformation techniques for evolving models: restructuring, refactoring, migration, translation, composition, versioning, etc.
• Maintenance and evolution of domain-specific languages
• Maintenance and evolution of model transformations
• Traceability maintenance, verification, and validation of evolving models, evolving model transformations, and evolving modeling languages; runtime models
• Analysis of model maintainability
• Variability management using models
• Model-driven software architecture recovery, reverse architecting, reconstruction, migration and software release engineering
• Model-based and model-related techniques for legacy systems evolution and systems integration
• Reusable evolution solutions and patterns
• Evolution issues in new and emerging systems and paradigms (e.g., cyber-security, cyber-physical systems, systems of systems, systems engineering, Internet of Things, cloud computing and its Software, Platform, Infrastructure (SPI) model, data analytics, big data, social media, devices and services, mobile applications, open source software, sustainability and modeling for social good, open architectures, product-line architectures, software ecosystems, Service-Oriented Architecture (SOA), micro-services, enterprise architectures)
• Model-driven software evolution regarding energy-awareness and sustainability
• Training, education, and certification around software evolution
• State-of-the-art and state-of-practice in software evolution
• Empirical studies, industrial needs, experience reports and experiments in software evolution
• Tools and methods supporting all of the above topics

Intended Audience

Researchers and practitioners who work in MDE to share experiences in dealing with the various forms of evolution in modeling, and value a forum to present work in progress and preliminary results.