RaQuN: a generic and scalable n-way model matching algorithm
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 model...
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| Published in | Software and systems modeling Vol. 22; no. 5; pp. 1495 - 1517 |
|---|---|
| Main Authors | , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
Berlin/Heidelberg
Springer Berlin Heidelberg
01.10.2023
Springer Nature B.V |
| Subjects | |
| Online Access | Get full text |
| ISSN | 1619-1366 1619-1374 1619-1374 |
| DOI | 10.1007/s10270-022-01062-5 |
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| Abstract | 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. |
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| AbstractList | 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
$$\text {N}$$
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. 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. 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. |
| Author | Boll, Alexander Grunske, Lars Thüm, Thomas Bittner, Paul Maximilian Kehrer, Timo Schultheiß, Alexander |
| Author_xml | – sequence: 1 givenname: Alexander orcidid: 0000-0002-1509-1449 surname: Schultheiß fullname: Schultheiß, Alexander email: alexander.schultheiss@informatik.hu-berlin.de organization: Humboldt-Universität zu Berlin – sequence: 2 givenname: Paul Maximilian orcidid: 0000-0001-9388-0649 surname: Bittner fullname: Bittner, Paul Maximilian organization: University of Ulm – sequence: 3 givenname: Alexander orcidid: 0000-0002-9881-9748 surname: Boll fullname: Boll, Alexander email: alexander.boll@inf.unibe.ch organization: University of Bern – sequence: 4 givenname: Lars orcidid: 0000-0002-8747-3745 surname: Grunske fullname: Grunske, Lars organization: Humboldt-Universität zu Berlin – sequence: 5 givenname: Thomas orcidid: 0000-0001-8069-9584 surname: Thüm fullname: Thüm, Thomas organization: University of Ulm – sequence: 6 givenname: Timo orcidid: 0000-0002-2582-5557 surname: Kehrer fullname: Kehrer, Timo email: timo.kehrer@inf.unibe.ch organization: University of Bern |
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| Keywords | Model-driven engineering Clone-and-own development n-Way model matching Software product lines |
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| Snippet | Model matching algorithms are used to identify common elements in input models, which is a fundamental precondition for many software engineering tasks, such... |
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| SubjectTerms | 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 |
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| Title | RaQuN: a generic and scalable n-way model matching algorithm |
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