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University of Southern Denmark Research Output
Contribution for newspaper or weekly magazine . 2019
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Taking Linear Logic Apart

Authors: Wen Kokke; Fabrizio Montesi; Marco Peressotti;

Taking Linear Logic Apart

Abstract

Process calculi based on logic, such as $π$DILL and CP, provide a foundation for deadlock-free concurrent programming. However, in previous work, there is a mismatch between the rules for constructing proofs and the term constructors of the $π$-calculus: the fundamental operator for parallel composition does not correspond to any rule of linear logic. Kokke et al. (2019) introduced Hypersequent Classical Processes (HCP), which addresses this mismatch using hypersequents (collections of sequents) to register parallelism in the typing judgements. However, the step from CP to HCP is a big one. As of yet, HCP does not have reduction semantics, and the addition of delayed actions means that CP processes interpreted as HCP processes do not behave as they would in CP. We introduce HCP-, a variant of HCP with reduction semantics and without delayed actions. We prove progress, preservation, and termination, and show that HCP- supports the same communication protocols as CP.

In Proceedings Linearity-TLLA 2018, arXiv:1904.06159

Countries
United Kingdom, Denmark
Keywords

FOS: Computer and information sciences, D.3.1; D.3.2; F.3.2; F.4.1, Computer Science - Logic in Computer Science, D.3.1, Computer Science - Programming Languages, Logic, Formal methods, D.3.2, Linear logic, QA75.5-76.95, Curry-Howard correspondence, Logic in Computer Science (cs.LO), Process calculi, Deadlock-freedom, Electronic computers. Computer science, QA1-939, F.3.2, F.4.1, Programming Languages, Mathematics, Programming Languages (cs.PL)

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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!
3
Average
Average
Average
Green
gold