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Rewriting Techniques and Applications

Overview of attention for book
Cover of 'Rewriting Techniques and Applications'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 Modular Termination of Basic Narrowing
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    Chapter 2 Linear-algebraic λ -calculus: higher-order, encodings, and confluence.
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    Chapter 3 Term-Graph Rewriting Via Explicit Paths
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    Chapter 4 Finer Is Better: Abstraction Refinement for Rewriting Approximations
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    Chapter 5 A Needed Rewriting Strategy for Data-Structures with Pointers
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    Chapter 6 Effectively Checking the Finite Variant Property
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    Chapter 7 Dependency Pairs for Rewriting with Built-In Numbers and Semantic Data Structures
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    Chapter 8 Maximal Termination
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    Chapter 9 Usable Rules for Context-Sensitive Rewrite Systems
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    Chapter 10 Combining Equational Tree Automata over AC and ACI Theories
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    Chapter 11 Closure of Hedge-Automata Languages by Hedge Rewriting
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    Chapter 12 On Normalisation of Infinitary Combinatory Reduction Systems
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    Chapter 13 Innermost Reachability and Context Sensitive Reachability Properties Are Decidable for Linear Right-Shallow Term Rewriting Systems
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    Chapter 14 Arctic Termination ...Below Zero
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    Chapter 15 Logics and Automata for Totally Ordered Trees
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    Chapter 16 Diagram Rewriting for Orthogonal Matrices: A Study of Critical Peaks
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    Chapter 17 Nominal Unification from a Higher-Order Perspective
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    Chapter 18 Functional-Logic Graph Parser Combinators
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    Chapter 19 Proving Quadratic Derivational Complexities Using Context Dependent Interpretations
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    Chapter 20 Tree Automata for Non-linear Arithmetic
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    Chapter 21 Confluence by Decreasing Diagrams
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    Chapter 22 A Finite Simulation Method in a Non-deterministic Call-by-Need Lambda-Calculus with Letrec, Constructors, and Case
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    Chapter 23 Root-Labeling
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    Chapter 24 Combining Rewriting with Noetherian Induction to Reason on Non-orientable Equalities
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    Chapter 25 Deciding Innermost Loops
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    Chapter 26 Termination Proof of S-Expression Rewriting Systems with Recursive Path Relations
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    Chapter 27 Encoding the Pure Lambda Calculus into Hierarchical Graph Rewriting
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    Chapter 28 Revisiting Cut-Elimination: One Difficult Proof Is Really a Proof
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    Chapter 29 Reduction Under Substitution
  31. Altmetric Badge
    Chapter 30 Normalization of Infinite Terms
Overall attention for this book and its chapters
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About this Attention Score

  • Average Attention Score compared to outputs of the same age and source

Mentioned by

wikipedia
1 Wikipedia page

Readers on

mendeley
3 Mendeley
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Title
Rewriting Techniques and Applications
Published by
Lecture notes in computer science, January 2008
DOI 10.1007/978-3-540-70590-1
ISBNs
978-3-54-070588-8, 978-3-54-070590-1
Editors

Voronkov, Andrei

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 3 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 3 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 1 33%
Professor > Associate Professor 1 33%
Student > Master 1 33%
Readers by discipline Count As %
Computer Science 3 100%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 31 August 2021.
All research outputs
#8,107,497
of 24,325,299 outputs
Outputs from Lecture notes in computer science
#2,511
of 8,154 outputs
Outputs of similar age
#43,942
of 163,480 outputs
Outputs of similar age from Lecture notes in computer science
#39
of 86 outputs
Altmetric has tracked 24,325,299 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 8,154 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.1. This one has gotten more attention than average, scoring higher than 54% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 163,480 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 18th percentile – i.e., 18% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 86 others from the same source and published within six weeks on either side of this one. This one is in the 32nd percentile – i.e., 32% of its contemporaries scored the same or lower than it.