Improving custom-tailored variability mining using outlier and cluster detection

Willé, David; Babur, Önder; Cleophas, Loek; Seidl, Christoph; Brand, Mark van den; Schaefer, Ina

doi:10.1016/j.scico.2018.04.002

Cited by 13 publications

(5 citation statements)

References 4 publications

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“…SAMOS is in principle generic, in the sense that it can be applied to any graph-based model provided one implements the corresponding (metamodel-driven or hard-coded) feature extraction. SAMOS has been or is currently being applied in different contexts for UML class diagrams, industrial DSLs, feature models [46] and state charts [47]. It will be further investigated to what extent our technique is applicable to these and other types of models, especially in data flow or block-based languages.…”

Section: Overall Discussion and Future Workmentioning

confidence: 99%

Metamodel clone detection with SAMOS

Babur

Cleophas

Brand

2019

Journal of Computer Languages

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DOI to the publisher's website.• The final author version and the galley proof are versions of the publication after peer review.• The final published version features the final layout of the paper including the volume, issue and page numbers. Link to publication General rightsCopyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights.• Users may download and print one copy of any publication from the public portal for the purpose of private study or research. • You may not further distribute the material or use it for any profit-making activity or commercial gain • You may freely distribute the URL identifying the publication in the public portal.If the publication is distributed under the terms of Article 25fa of the Dutch Copyright Act, indicated by the "Taverne" license above, please follow below link for the End User Agreement:

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Section: Overall Discussion and Future Workmentioning

confidence: 99%

Metamodel clone detection with SAMOS

Babur

Cleophas

Brand

2019

Journal of Computer Languages

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“…However, clustering is performed on the granularity level of entire models, while our candidate initialization clusters individual model elements. In fact, as shown by Wille et al [77], both may be used complementary by first partitioning a set of model variants and then performing a fine-grained n-way matching on clusters of similar models.…”

Section: Related Workmentioning

confidence: 99%

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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“…Prior work on re-engineering variability in our group [55,76,[78][79][80][81] focuses on the solution space for MATLAB/Simulink models [64][65][66][67]. Prior work encompasses a coarse-grain variability analysis of an entire model portfolio [64], followed by a fine-grained analysis of individual systems [66,67] and, finally, the combination of both analyses to produce a holistic 150% model that represents solution-space variability for multiple MATLAB/Simulink models [65].…”

Section: Prior Work On Solution Space Variabilitymentioning

confidence: 99%

Incremental feature model synthesis for clone-and-own software systems in MATLAB/Simulink

Schlie

Knüppel

Seidl

et al. 2020

Proceedings of the 24th ACM Conference on Systems and Software Product Line: Volume a - Volume A

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Families of related MATLAB/Simulink systems commonly emerge ad hoc using clone-and-own practices. Extractively migrating systems towards a software product line (SPL) can be a remedy. A feature model (FM) represents all potential configurations of an SPL, ideally, in non-technical domain terms. However, yielding a sensible FM from automated synthesis remains a major challenge due to domain knowledge being a prerequisite for features to be adequate abstractions. In incremental reverse engineering, subsequent generation of FMs may further overwrite changes and design decisions made during previous manual FM refinement.In this paper, we propose an approach to largely automate the synthesis of a suitable FM from a set of cloned MATLAB/Simulink models as part of reverse engineering an SPL. We fully automate the extraction of an initial, i.e., a technical, FM that closely aligns with realization artifacts and their variability, and further provide operations to manually refine it to incorporate domain knowledge. Most importantly, we provide concepts to capture such operations and to replay them on a structurally different technical FM stemming from a subsequent reverse engineering increment that included further systems of the portfolio. We further provide an implementation and demonstrate the feasibility of our approach using two MATLAB/Simulink data sets from the automotive domain. CCS CONCEPTS• Software and its engineering → Software product lines; Software reverse engineering; Maintaining software.

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Improving custom-tailored variability mining using outlier and cluster detection

Cited by 13 publications

References 4 publications

Metamodel clone detection with SAMOS

Metamodel clone detection with SAMOS

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

Incremental feature model synthesis for clone-and-own software systems in MATLAB/Simulink

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