Name
Abstract | ||
|---|---|---|
Meta-models play a pivotal role in Model-Driven Engineering, as they are used to define the structure of instance models one level below. However, in some scenarios, organizing meta-models and their instances in multi-level models spanning more than two levels yields simpler solutions. This fact has triggered the proposal of different multi-level modelling tools and approaches, although each one of them supports small variations of the multi-level concepts.In order to benefit from multi-level technology, existing meta-models and their instances could be migrated manually, but this is error prone, costly, and requires expertise for choosing the most appropriate tool and approach. Hence, we propose an automated migration process. This way, starting from a meta-model annotated with multi-level "smells", our approach creates a neutral multi-level representation, and recommends the most appropriate tool according to the required multi-level features. We present an initial prototype, and a preliminary evaluation on the basis of meta-models developed by third parties. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1007/978-3-319-69904-2_5 | CONCEPTUAL MODELING, ER 2017 |
Field | DocType | Volume |
Data science,Data mining,Computer science | Conference | 10650 |
ISSN | Citations | PageRank |
0302-9743 | 0 | 0.34 |
References | Authors | |
8 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Fernando Macías | 1 | 10 | 4.67 |
| Esther Guerra | 2 | 504 | 45.53 |
| Juan Lara | 3 | 236 | 18.08 |