Towards Evolutionary Multi-Layer Modeling With Dmla

State-of-the-art meta-model based methodologies are facing increasing pressure under new challenges originating from practical applications. In such cases, there is a strong need for approaches that support continuous, fine-graded, incremental refining of concepts. To address these challenges, our research group started working on a new modeling framework, the Dynamic Multi-Layer Algebra (DMLA) a few years ago. DMLA follows a completely new modeling paradigm, referred to as multi-layer modeling. Multi-layer modeling is originated from multi-level modeling and offers a highly flexible abstraction management approach in a level-blind fashion through its advanced deep instantiation and evolutionary snapshot management. One of the key features of DMLA is its self-validation mechanism based on a built-in, completely modeled operation language. Our initial solution had its limitations, since interactive editing was not supported, modelers could interact only with a single snapshot of the model. To overcome the limitations, we have created a virtual machine and an interpreter. In this paper, we present the novel architecture of our solution and demonstrate the feasibility of our approach by a walk-through of the concrete model management steps of an illustrative example to show the benefits of evolutionary model editing in DMLA.