MODELS 2022
Sun 23 - Fri 28 October 2022 Montréal, Canada
Wed 26 Oct 2022 13:30 - 13:52 at A-5502.1 - Model Management Chair(s): Ileana Ober

Similarity-based model matching is the foundation of model versioning. It pairs model elements based on a distance metric (e.g., edit distance). Because it is expensive to calculate the distance between two elements, a similarity-based matcher usually suffers from performance issues when the model size increases. This paper proposes a hash-based approach to accelerate similarity-based model matching. Firstly, we design a novel similarity-preserving hash function that maps a model element to a 64-bit hash value. If two elements are similar, their hashes are also very close. Secondly, we propose a 3-layer index structure and a query algorithm to quickly filter out impossible candidates for the element to be matched based on their hashes. For the remaining candidates, we employ the classical similarity-based matching algorithm to determine the final matches. Our approach has been realized and integrated into EMF Compare. The evaluation results show that our hash function is effective to preserve the similarity between model elements and our matching approach reduces 16% 72% of time costs while assuring the matching results consistent with EMF Compare.

Wed 26 Oct

Displayed time zone: Eastern Time (US & Canada) change

13:30 - 15:00
Model ManagementJournal-first / Technical Track at A-5502.1
Chair(s): Ileana Ober University of Toulouse
13:30
22m
Talk
Accelerating Similarity-Based Model Matching Using On-The-Fly Similarity Preserving HashingFT
Technical Track
Xiao He University of Science and Technology Beijing, China, Letian Tang School of Computer and Communication Engineering, University of Science and Technology Beijing, Yutong Li School of Computer and Communication Engineering, University of Science and Technology Beijing
13:52
22m
Talk
An efficient line-based approach for resolving merge conflicts in XMI-based modelsJ1st
Journal-first
Alfonso de la Vega Universidad de Cantabria, Dimitris Kolovos University of York
Link to publication
14:15
22m
Talk
A generic approach to detect design patterns in model transformations using a string-matching algorithmJ1st
Journal-first
Chihab eddine Mokaddem DIRO, Université de Montréal, Houari Sahraoui Université de Montréal, Eugene Syriani Université de Montréal
Link to publication
14:37
22m
Talk
Nested OSTRICH: Hatching Compositions of Low-code TemplatesP&I
Technical Track
João Costa Seco NOVA LINCS -- Universidade Nova de Lisboa, Hugo Lourenço OutSystems SA, Joana Baptista Parreira NOVA University of Lisbon, Carla Ferreira NOVA University Lisbon