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Electronic Notes in Theoretical Computer Science
Article . 2012 . Peer-reviewed
License: CC BY NC ND
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Electronic Notes in Theoretical Computer Science
Article
License: CC BY NC ND
Data sources: UnpayWall
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A System-Level Game Semantics

Authors: Dan R. Ghica; Nikos Tzevelekos;

A System-Level Game Semantics

Abstract

AbstractGame semantics is a trace-like denotational semantics for programming languages where the notion of legal observable behaviour of a term is defined combinatorially, by means of rules of a game between the term (the Proponent) and its context (the Opponent). In general, the richer the computational features a language has the less constrained the rules of the semantic game. In this paper we consider the consequences of taking this relaxation of rules to the limit, by granting the Opponent omnipotence, that is, permission to play any move without combinatorial restrictions. However, we impose an epistemic restriction by not granting Opponent omniscience, so that Proponent can have undisclosed secret moves. We introduce a basic C-like programming language and we define such a semantic model for it. We argue that the resulting semantics is an appealingly simple combination of operational and game semantics and we show how certain traces explain system-level attacks, i.e. plausible attacks that are realisable outside of the programming language itself. We also show how allowing Proponent to have secrets ensures that some desirable equivalences in the programming language are preserved.

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Keywords

Game semantics, omnipotent opponent, omniscient opponent, Theoretical Computer Science, Computer Science(all)

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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!
24
Top 10%
Top 10%
Top 10%
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