Article

Adaptability of model comparison tools

Authors:

Timo Kehrer,

Udo Kelter,

Pit Pietsch,

Maik SchmidtAuthors Info & Claims

ASE '12: Proceedings of the 27th IEEE/ACM International Conference on Automated Software Engineering

Pages 306 - 309

https://doi.org/10.1145/2351676.2351731

Published: 03 September 2012 Publication History

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Abstract

Modern model-based development methodologies require a large number of efficient, high-quality model comparison tools. They must be carefully adapted to the specific model type, user preferences and application context. Implementing a large number of dedicated, monolithic tools is infeasible, the only viable approach are generic, adaptable tools. Generic tools currently available provide only partial or low-quality solutions to this challenge; their results are not satisfactory for model types such as state machines or block diagrams. This paper presents the SiDiff approach to model comparison which includes a set of highly configurable incremental matchers and a specification language to control their application.

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Cited By

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Bittner PSchultheiß AMoosherr BKehrer TThüm Td'Amorim M(2024)Variability-Aware Differencing with DiffDetectiveCompanion Proceedings of the 32nd ACM International Conference on the Foundations of Software Engineering10.1145/3663529.3663813(632-636)Online publication date: 10-Jul-2024
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Yagi THayashi S(2024)Toward Interactive Optimization of Source Code Differences: An Empirical Study of Its Performance2024 IEEE International Conference on Source Code Analysis and Manipulation (SCAM)10.1109/SCAM63643.2024.00030(224-234)Online publication date: 7-Oct-2024
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Adaptability of model comparison tools

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Published In

ASE '12: Proceedings of the 27th IEEE/ACM International Conference on Automated Software Engineering

September 2012

409 pages

ISBN:9781450312042

DOI:10.1145/2351676

General Chair:
Michael Goedicke,
Program Chairs:
Tim Menzies,
Motoshi Saeki

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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SIGAI: ACM Special Interest Group on Artificial Intelligence
Universität Duisburg Essen: Universität Duisburg Essen
TCSE: IEEE Computer Society's Tech. Council on Software Engin.

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Association for Computing Machinery

New York, NY, United States

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Published: 03 September 2012

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ASE'12: IEEE/ACM International Conference on Automated Software Engineering

September 3 - 7, 2012

Essen, Germany

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https://dl.acm.org/doi/10.1145/3663529.3663813
Yagi THayashi S(2024)Toward Interactive Optimization of Source Code Differences: An Empirical Study of Its Performance2024 IEEE International Conference on Source Code Analysis and Manipulation (SCAM)10.1109/SCAM63643.2024.00030(224-234)Online publication date: 7-Oct-2024
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Hendriks DOortwijn W(2024)gLTSdiff: a generalized framework for structural comparison of software behaviorSoftware and Systems Modeling10.1007/s10270-024-01239-0Online publication date: 28-Nov-2024
https://doi.org/10.1007/s10270-024-01239-0
Bittner PSchultheiß AGreiner SMoosherr BKrieter STinnes CKehrer TThüm T(2023)Views on Edits to Variational SoftwareProceedings of the 27th ACM International Systems and Software Product Line Conference - Volume A10.1145/3579027.3608985(141-152)Online publication date: 28-Aug-2023
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Abstract

References

Cited By

Index Terms

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Model Matching for Model Transformation

Consistence preserving model merge in collaborative development processes

Concurrent model synchronization with conflict resolution based on triple graph grammars

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