Overview
- Includes supplementary material: sn.pub/extras
Part of the book series: Lecture Notes in Computer Science (LNCS, volume 10373)
Part of the book sub series: Theoretical Computer Science and General Issues (LNTCS)
Included in the following conference series:
Conference proceedings info: ICGT 2017.
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About this book
The 14 papers presented were carefully reviewed and selected from 23 submissions. The papers cover a wide range of topics including theoretical approaches to graph transformation and their verification, model-driven engineering, chemical reactions as well as various applications. They are organized in the following topical sections: foundations; graph language and parsing; analysis and verification; and model transformation and tools.
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Keywords
- semantics
- graph transformation
- Petri nets
- programming languages
- graph theory
- software engineering
- computer software selection and evaluation
- computer architecture
- hidden Markov models
- speech recognition
- context sensitive grammars
- geometry
- formal languages
- signal processing
- theorem proving
- set theory
- software design
- graph grammar
- world wide web
- learning systems
- algorithm analysis and problem complexity
Table of contents (14 papers)
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Graph Languages and Parsing
Other volumes
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Graph Transformation
Editors and Affiliations
Bibliographic Information
Book Title: Graph Transformation
Book Subtitle: 10th International Conference, ICGT 2017, Held as Part of STAF 2017, Marburg, Germany, July 18-19, 2017, Proceedings
Editors: Juan de Lara, Detlef Plump
Series Title: Lecture Notes in Computer Science
DOI: https://doi.org/10.1007/978-3-319-61470-0
Publisher: Springer Cham
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Springer International Publishing AG 2017
Softcover ISBN: 978-3-319-61469-4Published: 22 June 2017
eBook ISBN: 978-3-319-61470-0Published: 03 July 2017
Series ISSN: 0302-9743
Series E-ISSN: 1611-3349
Edition Number: 1
Number of Pages: XIV, 231
Number of Illustrations: 76 b/w illustrations
Topics: Discrete Mathematics in Computer Science, Algorithm Analysis and Problem Complexity, Programming Languages, Compilers, Interpreters, Programming Techniques, Data Structures, System Performance and Evaluation