Abstract
This work introduces a concept for rule based model verification using a graph database on the example of Neo4j and its query language Cypher. An approach is provided that allows to define verification rules using a graph query language to detect transformation errors within a given domain model. The approach is presented based on a running example, showing its capability of detecting randomly generated errors in a transformation process. Additionally, the method’s performance is evaluated using multiple subsets of the IMDb movie data with a maximum of 17,000,000 nodes and 41,000,000 relationships. This performance evaluation is carried out in comparison to the Object Constraint Language, showing advantages in the context of highly connected datasets with a high number of nodes. Another benefit is the utilization of a well established graph database as verification tool without any need for re-implementing graph and pattern matching logic.
Original language | English |
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DOIs | |
Publication status | Published - Sept 2022 |
Event | European Modeling & Simulation Symposium 2022 - Rom, Italy Duration: 19 Sept 2022 → 21 Sept 2022 Conference number: 34 https://www.msc-les.org/emss2022/ |
Conference
Conference | European Modeling & Simulation Symposium 2022 |
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Abbreviated title | EMSS |
Country/Territory | Italy |
City | Rom |
Period | 19.09.2022 → 21.09.2022 |
Internet address |
Keywords
- Cypher
- Graph-based Modeling
- Model Verification
- Neo4j