We introduce a categorical framework for operational semantics, in which we define substitution-closed bisimilarity, an abstract analogue of the open extension of Abramsky's applicative bisimilarity. We furthermore prove a congruence theorem for substitution-closed bisimilarity, following Howe's method. We finally demonstrate that the framework covers the call-by-name and call-by-value variants of -calculus in big-step style. As an intermediate result, we generalise the standard framework of Fiore et al. for syntax with variable binding to the skew-monoidal case.
Abstract. The ML module system provides powerful parameterization facilities, but lacks the ability to split mutually recursive definitions across modules, and does not provide enough facilities for incremental programming. A promising approach to solve these issues is Ancona and Zucca's mixin modules calculus CMS . However, the straightforward way to adapt it to ML fails, because it allows arbitrary recursive definitions to appear at any time, which ML does not support. In this paper, we enrich CMS with a refined type system that controls recursive definitions through the use of dependency graphs. We then develop a separate compilation scheme, directed by dependency graphs, that translate mixin modules down to a CBV λ-calculus extended with a non-standard let rec construct.
Abstract. We propose a semantics for permutation equivalence in higher-order rewriting. This semantics takes place in cartesian closed 2-categories, and is proved sound and complete.
We propose a categorical framework for structural operational semantics, in which we prove that under suitable hypotheses bisimilarity is a congruence. We then refine the framework to prove soundness of bisimulation up to context, an efficient method for reducing the size of bisimulation relations. Finally, we demonstrate the flexibility of our approach by reproving known results in three variants of the-calculus.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.