ML2 is a textual modeling language for multi-level conceptual models, i.e., those in which classes can also be subject to categorization, extending beyond the two-level divide between classes and their instances.
The language was designed using as a basis the MLT* multi-level modeling theory. As a result, it embodies many rules to ensure models are sound.
The language was originally introduced and described in Claudenir M. Fonseca’s M.Sc. thesis.
A paper presenting ML2 received the best student paper award at ER 2018:
For a quick overview, check out some slides for an ML2 presentation (used in a Dagstuhl seminar on Multi-Level Modeling).
An in-depth presentation of the language as an extended version of the ER 2018 paper was accepted for publication at Data & Knowledge Engineering:
A fully-featured ML2-Editor for Eclipse is available, including support for syntax verification, highlight, auto-complete and model simulation with Alloy.