Welcome to the home page of the third AMT (Analysis of Model Transformations) workshop!

News: Our keynote speaker this year is Ronan Barrett, from Ericsson. Check AMT's program for an abstract of Ronan's talk.

To facilitate the processing and manipulation of models, a lot of research has gone into developing languages, standards, and tools to support model transformations — a quick search on the internet produces more than 30 different transformation languages that have been proposed in the literature or implemented in open-source or commercial tools. The increasing adoption of these languages and the growing size and complexity of the model transformations developed require a better understanding of how all activities in the model transformation life cycle can be optimally supported.

Properties of an artifact created by a model transformation are intimately linked to the model transformation that produced it. In other words, to be able to guarantee certain properties of the produced artifact, it may be very helpful, or even indispensable, to also have knowledge of the producing transformation. As the use and significance of modeling increase, the importance that the model transformations produce models of sufficient quality and with desirable properties increases as well; similarly, as the number and complexity of model transformations grows, the importance that transformations satisfy certain non-functional requirements and that life cycle activities for model transformations such as development, quality assurance, maintenance, and evolution are well supported grows as well.

Organizers:

• Juan de Lara, Universidad Autónoma de Madrid, Spain
  
• Jürgen Dingel, Queens University, Canada
  
• Levi Lúcio, McGill University, Canada
  
• Hans Vangheluwe, University of Antwerp, Belgium and McGill University, Canada
  

• testing and test case generation for model transformations
• formal specification and verification of model transformations
• abstract interpretation for model transformations (to, e.g., support optimization)
• static analysis for model transformations such as control and data flow analyses and slicing
• dynamic analysis for model transformations such as run-time monitoring and profiling (to, for example, determine code coverage, or detect requirements violations or likely invariants)
• metrics for model transformations (to support, for example, anti-pattern detection, refactoring and evolution)
• impact analysis model transformations (to support, for example, maintenance)
• certification and incremental re-validation for model transformations (e.g., for use in safety-critical systems)
• tools for analyzing model transformations
• (higher-order) transformation of transformation models to make them amenable for analysis
• case studies for analyzing model transformations