Abstract Metamodels, like many other software artifacts, evolve and exist in multiple versions. As a result, their instances, i.e., models, can become outdated and require adaptation. This process is known as model co-evolution. Co-evolution, however, typically uses an all-or-nothing approach that overlooks four key aspects: (a) preserving the history of the metamodel, (b) retaining the model’s history before co-evolution, (c) supporting the coexistence of models across multiple metamodel versions to allow delayed co-evolution and (d) lack of traceability between model and metamodel changes. In this paper, we introduce a novel, operation-based approach that supports versioning, records the complete history of metamodels and models, and enables the coexistence of different metamodel versions. Our approach allows engineers to delay model co-evolution without losing a model’s history. It further enables both forward co-evolution and reverse de-evolution of models. In addition to that, it establishes cross-layer traceability by linking model changes back to their corresponding metamodel changes, thus improving the maintainability and understandability of evolving systems. We evaluated our approach empirically using metamodels from different domains, demonstrating that it accurately records both model and metamodel histories, supports de-evolution, and correctly traces over 17 million model changes to their metamodel origins. Scalability measurements show that our approach handles co-evolution even in large-scale scenarios, successfully evolving models with over 88,000 elements and 2 million properties while tracking nearly 500,000 changes.

One of the most important artifacts of Model-Driven Engineering (MDE) are metamodels. Like other software artifacts, they are expected to evolve. Consequently, their models thus become invalid and need to be fixed. The usual strategy is to adapt those models based on changes made to the metamodel, i.e., co-evolution. Co-evolution, however, depends on correctly recorded changes since even small deviations can impact the models that will be evolved. One problem is that those changes are usually not preserved or complete. The reason is that the most common way to record the history of metamodels is by using text-based version control systems, i.e., Git. This, however, hinders the detection of the concrete changes made to the metamodel, which are used for co-evolution. This aspect leads to problems in maintaining and evolving metamodels and their models in practice. In this paper, we propose a novel approach that allows engineers to reconstruct the history of metamodels with the help of ChangeTrees. These ChangeTrees recommend possible sequences of changes between two metamodel versions, i.e., evolved metamodels. We conducted an empirical study that detected changes to eight different metamodels across varying domains. The results show that our approach can correctly reconstruct the metamodel's history by detecting all possible changes between the two versions. Furthermore, performance results show that, in the worst case, our approach required 15.65 seconds to detect and generate a ChangeTree of a metamodel with more than 351 changes applied to it (between two versions), leading to 11,268 branching change paths (alternative sequences of changes).

Metamodels like many other software artifacts, are expected to evolve and exist in different versions. Consequently, the instances of these metamodels (models), become invalid and need fixing. The usual strategy for this is adapting models based on changes made to the metamodels, i.e., co-evolution. However, co-evolution usually adopts an all-or-nothing strategy that overlooks three important aspects: (a) preserving the history of the metamodel, (b) preserving the model's history before the co-evolution, and (c) supporting models to co-exist for different metamodel versions and delay their co-evolution. These aspects lead to problems for maintaining models in practice since often co-evolution gets driven by customer needs, e.g., the customer decides when to update. In this paper, we propose a novel approach that allows the creation of a metamodel version and records the history of metamodels and models by adopting an operation-based infrastructure. These metamodel versions allow engineers to delay the co-evolution of certain models by having co-existing metamodel versions. This notion of co-existence, in addition to the operation-based infrastructure, helps to preserve the complete history of metamodel and models, i.e., the history before and after co-evolving a model. To evaluate our approach, we conducted an empirical study, where we co-evolved models of varying domains. The results show that our approach correctly records the history of the metamodel and model. Furthermore, we measured the performance during co-evolution while having all versions co-existing in the same space. It shows that in the worst case, our approach required 887.91 seconds to co-evolve a model with more than 88,000 elements and 2,000,000 properties.