
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.
Game semantics, omnipotent opponent, omniscient opponent, Theoretical Computer Science, Computer Science(all)
Game semantics, omnipotent opponent, omniscient opponent, Theoretical Computer Science, Computer Science(all)
| 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). | 24 | |
| 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. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
