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https://doi.org/10.1007/978-3-...
Part of book or chapter of book . 2021 . Peer-reviewed
License: Springer TDM
Data sources: Crossref
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
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Composition of Languages, Models, and Analyses

Authors: Talcott C; Ananieva S; Bae K; Combemale B; Heinrich R; Hills M; Khakpour N; +6 Authors

Composition of Languages, Models, and Analyses

Abstract

This chapter targets a better understanding of the compositionality of analyses, including different forms of compositionality and specific conditions of composition. Analysis involves models, contexts, and properties. These are all expressed in languages with their own semantics. For a successful composition of analyses, it is therefore important to compose models as well as the underlying languages. We aim to develop a better understanding of what is needed to answer questions such as “When I want to compose two or more analyses, what do I need to take into account?” We describe the elements impacting analysis compositionality, the relation of these elements to analysis, and how composition of analysis relates to compositionality of these elements

Countries
Belgium, Italy, United Kingdom
Keywords

Computer. Automation, Linguistics

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    influence
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
9
Top 10%
Top 10%
Top 10%
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