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Mathematical Foundations of Programming Language Semantics

Overview of attention for book
Cover of 'Mathematical Foundations of Programming Language Semantics'

Table of Contents

  1. Altmetric Badge
    Book Overview
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    Chapter 1 A categorical treatment of polymorphic operations
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    Chapter 2 A categorical approach to realizability and polymorphic types
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    Chapter 3 Rule-based semantics for an extended lambda-calculus
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    Chapter 4 Semantics of block structured languages with pointers
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    Chapter 5 Assertional categories
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    Chapter 6 Kan extensions in effective semantics
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    Chapter 7 The versatile continuous order
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    Chapter 8 On the Smyth power domain
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    Chapter 9 The metric closure powerspace construction
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    Chapter 10 A powerdomain construction
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    Chapter 11 Closure properties of a probabilistic domain construction
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    Chapter 12 Quasi-uniformities: Reconciling domains with metric spaces
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    Chapter 13 Solving reflexive domain equations in a category of complete metric spaces
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    Chapter 14 Topological completeness in an ideal model for polymorphic types
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    Chapter 15 New results on hierarchies of domains
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    Chapter 16 Semantically based axiomatics
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    Chapter 17 Metric spaces as models for real-time concurrency
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    Chapter 18 Mathematical Foundations of Programming Language Semantics
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    Chapter 19 Continuous auxiliary relations
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    Chapter 20 Computable one-to-one enumerations of effective domains
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    Chapter 21 Mathematical Foundations of Programming Language Semantics
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    Chapter 22 Semantics-based tools for a specification-support environment
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    Chapter 23 A treatment of languages with stages of evaluation
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    Chapter 24 Operational semantics and a distributed implementation of CSP
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    Chapter 25 The semantics of Miranda's algebraic types
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    Chapter 26 Path semantics
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    Chapter 27 The formal description of data types using sketches
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    Chapter 28 Initial algebra semantics and concurrency
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    Chapter 29 High-level semantics
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    Chapter 30 An action semantics of standard ML
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    Chapter 31 An algorithmic approach to p-adic integers
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    Chapter 32 The shuffle bialgebra
Overall attention for this book and its chapters
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About this Attention Score

  • High Attention Score compared to outputs of the same age (80th percentile)

Mentioned by

facebook
1 Facebook page
wikipedia
8 Wikipedia pages

Citations

dimensions_citation
11 Dimensions

Readers on

mendeley
5 Mendeley
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Title
Mathematical Foundations of Programming Language Semantics
Published by
Lecture notes in computer science, January 1988
DOI 10.1007/3-540-19020-1
ISBNs
978-3-54-038920-0, 978-3-54-019020-2
Editors

Michael Main, Austin Melton, Michael Mislove, David Schmidt

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 5 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 20%
Sweden 1 20%
Unknown 3 60%

Demographic breakdown

Readers by professional status Count As %
Researcher 2 40%
Student > Ph. D. Student 1 20%
Professor > Associate Professor 1 20%
Unknown 1 20%
Readers by discipline Count As %
Computer Science 2 40%
Linguistics 1 20%
Mathematics 1 20%
Unknown 1 20%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 27 June 2023.
All research outputs
#7,348,158
of 23,164,913 outputs
Outputs from Lecture notes in computer science
#2,402
of 8,150 outputs
Outputs of similar age
#9,437
of 50,149 outputs
Outputs of similar age from Lecture notes in computer science
#1
of 3 outputs
Altmetric has tracked 23,164,913 research outputs across all sources so far. This one has received more attention than most of these and is in the 67th percentile.
So far Altmetric has tracked 8,150 research outputs from this source. They receive a mean Attention Score of 5.0. This one has gotten more attention than average, scoring higher than 69% 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 50,149 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 80% of its contemporaries.
We're also able to compare this research output to 3 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them