RaQuN: a generic and scalable n-way model matching algorithm

• Published in: Software and systems modeling Vol. 22; no. 5; pp. 1495 - 1517
• Main Authors: Schultheiß, Alexander, Bittner, Paul Maximilian, Boll, Alexander, Grunske, Lars, Thüm, Thomas, Kehrer, Timo
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.10.2023; Springer Nature B.V
• Subjects: Algorithms; Compilers; Computer Science; Information Systems Applications (incl.Internet); Interpreters; IT in Business; Model matching; Programming Languages; Programming Techniques; Queries; Software Engineering; Software Engineering/Programming and Operating Systems; Special Section Paper; Model-driven engineering; Clone-and-own development; n-Way model matching; Software product lines
• ISSN: 1619-1366; 1619-1374; 1619-1374
• DOI: 10.1007/s10270-022-01062-5

Model matching algorithms are used to identify common elements in input models, which is a fundamental precondition for many software engineering tasks, such as merging software variants or views. If there are multiple input models, an n-way matching algorithm that simultaneously processes all models typically produces better results than the sequential application of two-way matching algorithms. However, existing algorithms for n-way matching do not scale well, as the computational effort grows fast in the number of models and their size. We propose a scalable n-way model matching algorithm, which uses multi-dimensional search trees for efficiently finding suitable match candidates through range queries. We implemented our generic algorithm named RaQuN   (Range Queries on N input models) in Java and empirically evaluate the matching quality and runtime performance on several datasets of different origins and model types. Compared to the state of the art, our experimental results show a performance improvement by an order of magnitude, while delivering matching results of better quality.