Scalable N-Way Model Matching Using Multi-Dimensional Search Trees

SchultheiB, Alexander; Bittner, Paul Maximilian; Grunske, Lars; Thüm, Thomas; Kehrer, Timo

doi:10.1109/models50736.2021.00010

Cited by 6 publications

(4 citation statements)

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“…In this paper, we extend our previous publication [37] in three aspects. First, we evaluate RaQuN on five additional experimental subjects comprising Simulink models, a model type which we have not considered before.…”

Section: Introductionmentioning

confidence: 57%

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

et al. 2022

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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.

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Section: Introductionmentioning

confidence: 57%

“…In our MODELS paper [37], we proposed RaQuN (Range Queries on N input models), a generic, heuristic n-way model matching algorithm. As illustrated in Fig.…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2022

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“…Three-way differencing usually combines the results of two pairwise two-way differencing of each model with their common ancestor. Rubin & Chechik (2013) and Schultheiß et al (2021) introduce novel approaches that are faster than the pairwise method, though Schultheiß et al (2021) preferred a pairwise comparison over a straight rating of entire matches to evaluate almost correct matches better than completely incorrect matches.…”

Section: Features For Three-way Domain-specific Model Differencingmentioning

confidence: 99%

From two-way to three-way: domain-specific model differencing and conflict detection.

Jafarlou,

Syriani,

Alam

2023

JOT

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In collaborative work, developers evolve their models in parallel, leading to substantial differences and conflicts.To better consolidate these changes, developers need to understand the differences in terms of syntax and semantics of the models. Despite myriad efforts, the existing version control systems and model comparison tools focus on the generic models, are hardly adaptable to a domain-specific language (DSL), and primarily present syntactical changes to the developer. Furthermore, they report differences and conflicts of domain-specific models based on their abstract syntax instead of the concrete syntax of the DSL. To address these issues, we previously introduced DSMCompare to detect fine-grained and semantic differences between pairs of model versions and present the changes in the concrete syntax of the DSL. In this paper, we have further enhanced our practice by considering a three-way model comparison, typical in the context of version control systems. DSMCompare can now report differences coming from either version as well as conflicts. To detect semantic differences and conflicts, our approach relies on the DSL engineer specifying semantic differencing patterns in an editor adapted to the DSL. To evaluate DSMCompare, we reverse-engineered the commit history of several open-source projects where Java-based code refactoring changes occur. We show that DSMCompare effectively finds these semantic differences and conflicts with high accuracy.

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“…ArgoUML was used to evaluate the scalability of the approach given its size. Schultheiß et al also used the UML class models to evaluate n-way model matching techniques that are meant to support variability mining (Schultheiß et al 2021). The previously mentioned works were interested in technical aspects, thus, they did not investigate the original reengineering process, nor they compared the effort required for the original extraction.…”

Section: Argouml Extensive Usementioning

confidence: 99%

Open-source software product line extraction processes: the ArgoUML-SPL and Phaser cases

et al. 2022

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Software Product Lines (SPLs) are rarely developed from scratch. Commonly, they emerge from one product when there is a need to create tailored variants, or from existing variants created in an ad-hoc way once their separated maintenance and evolution become challenging. Despite the vast literature about re-engineering systems into SPLs and related technical approaches, there is a lack of detailed analysis of the process itself and the effort involved. In this paper, we provide and analyze empirical data of the extraction processes of two open-source case studies, namely ArgoUML and Phaser. Both cases emerged from the transition of a monolithic system into an SPL. The analysis relies on information mined from the version control history of their respective source-code repositories and the discussion with developers that took part in the process. Unlike previous works that focused mostly on the structural results of the final SPL, the contribution of this study is an in-depth characterization of the processes. With this work, we aimed at providing a deeper understanding of the strategies for SPL extraction and their implications. Our results indicate that the source code changes can range from almost a fourth to over half of the total lines of code. Developers may or may not use branching strategies for feature extraction. Additionally, the problems faced during the extraction process may be due to lack of tool support, complexity on managing feature dependencies and issues with feature constraints. We made publicly available the datasets and the analysis scripts of both case studies to be used as a baseline for extractive SPL adoption research and practice.

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Scalable N-Way Model Matching Using Multi-Dimensional Search Trees

Cited by 6 publications

References 50 publications

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

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

From two-way to three-way: domain-specific model differencing and conflict detection.

Open-source software product line extraction processes: the ArgoUML-SPL and Phaser cases

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