RAIRO-Theor. Inf. Appl.
Volume 53, Number 3-4, July–December 2019
|Page(s)||153 - 206|
|Published online||10 January 2020|
East China University of Science and Technology,
200237, PR China.
*** Corresponding author: firstname.lastname@example.org
Accepted: 15 November 2019
Parameterization extends higher-order processes with the capability of abstraction and application (like those in lambda-calculus). As is well-known, this extension is strict, meaning that higher-order processes equipped with parameterization are strictly more expressive than those without parameterization. This paper studies strictly higher-order processes (i.e., no name-passing) with two kinds of parameterization: one on names and the other on processes themselves. We present two main results. One is that in presence of parameterization, higher-order processes can interpret first-order (name-passing) processes in a quite elegant fashion, in contrast to the fact that higher-order processes without parameterization cannot encode first-order processes at all. We present two such encodings and analyze their properties in depth, particularly full abstraction. In the other result, we provide a simpler characterization of the standard context bisimilarity for higher-order processes with parameterization, in terms of the normal bisimilarity that stems from the well-known normal characterization for higher-order calculus. As a spinoff, we show that the bisimulation up-to context technique is sound in the higher-order setting with parameterization.
Mathematics Subject Classification: 68Q05 / 68Q10 / 68Q85
Key words: Parameterization / encoding / context bisimulation / normal bisimulation / higher-order / first-order / processes
A preliminary version of this work was presented at EXPRESS/SOS 2016. This paper revises and extends that version with full-fledged proofs and more refined discussions (at least more than half new materials), and moreover, the detailed analysis of a variant encoding of interest. This encoding, mentioned only as a further direction in the preliminary version, is given thorough examination in this work.
© EDP Sciences, 2020
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