In recent years, multi-level modeling has become more and more popular. It is mainly due to the fact that multi-level modeling aims to reduce or even totally eliminate any accidental complexity inadvertently created as by-product in traditional model design. Moreover, besides reducing model complexity, multi-level modeling also improves on general comprehension of models. The key enablers of multi-level modeling are the concepts of clabjects and deep instantiation. The latter is often governed by the potency notion, of which many different interpretations and variations emerged over the years. However, there exist also some approaches that disregard the potency notion. Thus, multi-level modeling approaches tend to take advantage of different theoretical and practical backgrounds. In this paper, we propose a unifying framework, the Multi-Level Modeling Playground (MLMP), which is a validating modeling environment for multi-level modeling research. The MLMP environment is based on our multi-layer modeling framework (the Dynamic Multi-Layer Algebra), which provides useful mechanisms to validate different multi-level modeling constructs. Since beyond the structure also the well-formedness rules of the modeling constructs can be specified, our proposed MLMP environment delivers several practical benefits: i) well-formedness is always verified, ii) multi-level constructs can be experimented with independently of any concrete tool chains, and iii) relationships (i.e., correlations or exclusions) between different multi-level constructs can be easily investigated in practice. Also, the capability of the environment is demonstrated via complete examples inspired by state-of-the-art research literature.

近年来，多层次建模越来越流行。这主要是因为多层次建模旨在减少甚至完全消除在传统模型设计中无意中作为副产品产生的任何意外复杂性。此外，除了降低模型复杂度之外，多层次建模还提高了对模型的一般理解。多级建模的关键推动因素是 clabjects 和深度实例化的概念。后者通常受效力概念的支配，多年来出现了许多不同的解释和变化。然而，也存在一些无视效力概念的方法。因此，多层次建模方法倾向于利用不同的理论和实践背景。在本文中，我们提出了一个统一的框架，Multi-Level Modeling Playground (MLMP)，这是一个用于多级建模研究的验证建模环境。MLMP 环境基于我们的多层建模框架（动态多层代数），它提供了有用的机制来验证不同的多层建模构造。由于除了结构之外，还可以指定建模构造的良构规则，我们提出的 MLMP 环境提供了几个实际好处：i) 良构总是得到验证，ii) 可以独立于任何混凝土对多层次构造进行试验工具链，以及 iii) 不同多层次结构之间的关系（即相关性或排除性）在实践中可以很容易地进行研究。还，