Exploring (Meta-)Model Snapshots by Combining Visual and Textual Techniques Article Swipe
Martin Gogolla
,
Lars Hamann
,
Xu Jie
,
Jun Zhang
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.14279/tuj.eceasst.41.573
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.14279/tuj.eceasst.41.573
One central task in software development by means of graph-based techniques is to inspect and to query the underlying graph. Important issues are, for example, to detect general graph properties like connectivity, to explore more special features like the applicability of left-hand side rules in graph transformations, or to validate snapshots of evolving systems by checking properties in an on-the-fly way. We propose a new approach combining visual and textual techniques for exploring graphs. We emphasize a particular aspect of the underlying graph by showing or hiding nodes and edges. We offer three different ways to explore (meta-)model snapshots which may be combined: (1) selection by object identity and class membership, (2) selection by OCL expression, and (3) selection by path length. One main motivation for our work is to access large or complicated graphs in a systematic way. We evaluate our approach by different middle-sized scenarios. Our evaluation shows that the approach works for large graphs with about 1000 nodes and 2000 edges and for graphs which instantiate metamodels representing software engineering artifacts.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.14279/tuj.eceasst.41.573
- OA Status
- green
- Cited By
- 11
- References
- 12
- Related Works
- 20
- OpenAlex ID
- https://openalex.org/W1529039679
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W1529039679Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.14279/tuj.eceasst.41.573Digital Object Identifier
- Title
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Exploring (Meta-)Model Snapshots by Combining Visual and Textual TechniquesWork title
- Type
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articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
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2024Year of publication
- Publication date
-
2024-03-25Full publication date if available
- Authors
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Martin Gogolla, Lars Hamann, Xu Jie, Jun ZhangList of authors in order
- Landing page
-
https://doi.org/10.14279/tuj.eceasst.41.573Publisher landing page
- Open access
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YesWhether a free full text is available
- OA status
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greenOpen access status per OpenAlex
- OA URL
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https://doi.org/10.14279/tuj.eceasst.41.573Direct OA link when available
- Concepts
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Computer science, Theoretical computer science, Graph, Software, Selection (genetic algorithm), Artificial intelligence, Data mining, Machine learning, Programming languageTop concepts (fields/topics) attached by OpenAlex
- Cited by
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11Total citation count in OpenAlex
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2024: 2, 2020: 2, 2018: 1, 2016: 1, 2013: 2Per-year citation counts (last 5 years)
- References (count)
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12Number of works referenced by this work
- Related works (count)
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20Other works algorithmically related by OpenAlex
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