The software industry is applying Model-driven development approaches due to a core set of benefits, such
as raising the level of abstraction and reducing coding errors. However, their underlying modeling languages
tend to be quite static, making their evolution hard, specifically when the corresponding metamodel does not
support primitives and/or functionalities required in specific business domains. This paper presents an
extension to the LiquidML language to support fast metamodel evolution by allowing experts to abstract
new language concepts from primitives while supporting automatic tool evolution and zero application
downtime. To probe our claims, we evaluate the evolutionary capabilities of existing modeling languages
and LiquidML in a real world language extension.Ministerio de Economía y Competitividad TIN2016-76956-C3-2-R (POLOLAS)Ministerio de Economía y Competitividad TIN2015-71938-RED
