Towards adding variety to simplicity

Abstract

Simplicity is a Turing-incomplete typed combinator language for smart contracts with a formal semantics. The design of Simplicity makes it possible to statically estimate the resources (e.g., memory) required to execute contracts. Such a feature is highly relevant in blockchain applications to efficiently determine fees to run smart contracts. Despite being Turing incomplete, the language is capable of expressing non-trivial contracts. Often, Simplicity programs contain lots of code repetition that could otherwise be avoided if it had common programming languages features, such as local definitions, functions, and bounded loops. In this work, we provide the foundations to make Simplicity a richer language. To achieve that, we connect Simplicity’s primitives with a categorical model. By doing so, we lift the language to a more abstract representation that will allow us to extend it by leveraging category theory models for computations. This methodology facilitates the addition of local definitions, functions, and bounded loops. We provide an implementation of Simplicity and its virtual machine in the functional programming language Haskell.