scholarly journals Evaluating Well-Formedness Constraints on Incomplete Models

2017 ◽  
Vol 23 (2) ◽  
pp. 687-713 ◽  
Author(s):  
Oszkár Semeráth ◽  
Dániel Varró

In modern modeling tools used for model-driven development, the validation of several well-formedness constraints is continuously been carried out by exploiting advanced graph query engines to highlight conceptual design aws. However, while models are still under development, they are frequently par- tial and incomplete. Validating constraints on incomplete, partial models may identify a large number of irrelevant problems. By switching o the val- idation of these constraints, one may fail to reveal problematic cases which are dicult to correct when the model becomes suciently detailed. Here, we propose a novel validation technique for evaluating well-formed- ness constraints on incomplete, partial models with may and must semantics, e.g. a constraint without a valid match is satisable if there is a completion of the partial model that may satisfy it. To this end, we map the problem of constraint evaluation over partial models into regular graph pattern matching over complete models by semantically equivalent rewrites of graph queries.

2019 ◽  
Vol 30 (4) ◽  
pp. 24-40
Author(s):  
Lei Li ◽  
Fang Zhang ◽  
Guanfeng Liu

Big graph data is different from traditional data and they usually contain complex relationships and multiple attributes. With the help of graph pattern matching, a pattern graph can be designed, satisfying special personal requirements and locate the subgraphs which match the required pattern. Then, how to locate a graph pattern with better attribute values in the big graph effectively and efficiently becomes a key problem to analyze and deal with big graph data, especially for a specific domain. This article introduces fuzziness into graph pattern matching. Then, a genetic algorithm, specifically an NSGA-II algorithm, and a particle swarm optimization algorithm are adopted for multi-fuzzy-objective optimization. Experimental results show that the proposed approaches outperform the existing approaches effectively.


2021 ◽  
Author(s):  
Daniel Mawhirter ◽  
Samuel Reinehr ◽  
Wei Han ◽  
Noah Fields ◽  
Miles Claver ◽  
...  

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