Probability theory and statistics are fundamental disciplines in a data-driven world. Synthetic
probability theory is a general, axiomatic formalism to describe their underlying structures …

We make a formal analogy between random sampling and fresh name generation. We show
that quasi-Borel spaces, a model for probabilistic programming, can soundly interpret the ν …

Memory models play an important role in verified compilation of imperative programming
languages. A representative one is the block-based memory model of CompCert---the state …

We present a full classification of decidable and undecidable cases for contextual
equivalence in a finitary ML-like language equipped with full ground storage (both integers …

Game Semantics arguably stands for one of the most successful techniques in denotational
semantics, having provided not only proper denotational, accurate models for a large variety …

Game-semantic models usually start from the core model of the prototypical language PCF,
which is characterised by a range of combinatorial constraints on the shape of plays …

We present a full classification of decidable and undecidable cases for contextual
equivalence in a finitary ML-like language equipped with full ground storage (both integers …

We present a bounded equivalence verification technique for higher-order programs with
local state. This technique combines fully abstract symbolic environmental bisimulations …

In game semantics, a computation is represented by a play, which is traditionally a
sequence of messages exchanged by a program and an environment. Because of the …

We develop a denotational semantics for general reference types in an impredicative
version of guarded homotopy type theory, an adaptation of synthetic guarded domain theory …