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Conference object . 2015
Data sources: INRIA2
https://doi.org/10.1109/lics.2...
Article . 2015 . Peer-reviewed
Data sources: Crossref
https://dx.doi.org/10.48550/ar...
Article . 2015
License: arXiv Non-Exclusive Distribution
Data sources: Datacite
DBLP
Article . 2015
Data sources: DBLP
DBLP
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On the Relative Usefulness of Fireballs

Authors: Accattoli, Beniamino; Sacerdoti Coen, Claudio;

On the Relative Usefulness of Fireballs

Abstract

In CSL-LICS 2014, Accattoli and Dal Lago showed that there is an implementation of the ordinary (i.e. strong, pure, call-by-name) $λ$-calculus into models like RAM machines which is polynomial in the number of $β$-steps, answering a long-standing question. The key ingredient was the use of a calculus with useful sharing, a new notion whose complexity was shown to be polynomial, but whose implementation was not explored. This paper, meant to be complementary, studies useful sharing in a call-by-value scenario and from a practical point of view. We introduce the Fireball Calculus, a natural extension of call-by-value to open terms for which the problem is as hard as for the ordinary lambda-calculus. We present three results. First, we adapt the solution of Accattoli and Dal Lago, improving the meta-theory of useful sharing. Then, we refine the picture by introducing the GLAMoUr, a simple abstract machine implementing the Fireball Calculus extended with useful sharing. Its key feature is that usefulness of a step is tested---surprisingly---in constant time. Third, we provide a further optimization that leads to an implementation having only a linear overhead with respect to the number of $β$-steps.

Technical report for the LICS 2015 submission with the same title

Country
Italy
Keywords

FOS: Computer and information sciences, Computer Science - Logic in Computer Science, [INFO.INFO-LO] Computer Science [cs]/Logic in Computer Science [cs.LO], Cost Models, Abstract Machines, Lambda Calculus, Software; Mathematics (all), Logic in Computer Science (cs.LO)

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    popularity
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    Top 10%
    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!
16
Top 10%
Top 10%
Top 10%
Green