Type Inference and Subtyping for Higher-Order Generative Communication

Models for generative communication use a common space, where concurrent agents put or retrieve data; data extraction is controlled by various kinds of filtering techniques, usually based on the structure of the data itself. However, for higher-order communication, i.e. when the data consists of software fragments, such techniques are not appropriate: structural information does not reflect the behaviour of a software fragment. This paper studies a filtering mechanism based instead on type information, so that software components can be retrieved according to type specifications. A rich type system with polymorphism and subtyping gives enough flexibility to formulate type specifications at various levels of detail.