LEO Programming Language

Aleo has put together a solid compiler team to build a very ambitious circuit compiler language. The core aim of this endeavor is to allow developers to make use of zero knowledge proofs in their applications in as simple a manner as possible - it achieves this by minimizing cryptographic knowledge requirements. So how exactly does Leo achieve this, and what do you need to know to get started using it? Let’s find out.

Leo is a Rust-inspired statically typed programming language built for writing private applications. It is designed for developers to build intuitively on the Aleo blockchain, providing the groundwork for a private, decentralised ecosystem. It is the first known programming language to introduce a testing framework, package registry, import resolver, remote compiler, and theorem generator for general-purpose, zero-knowledge applications.

Leo is designed to remove as many cryptographic knowledge requirements as possible. Moreover, it is designed to be reminiscent of Javascript and Typescript so that the army of JS/TS developers out there will have a very straightforward learning curve.

Leo is a Rust-inspired statically typed programming language built for writing private applications. It is designed for developers to build intuitively on the Aleo blockchain, providing the groundwork for a private, decentralised ecosystem. It is the first known programming language to introduce a testing framework, package registry, import resolver, remote compiler, and theorem generator for general-purpose, zero-knowledge applications.

Leo is designed to remove as many cryptographic knowledge requirements as possible. Moreover, it is designed to be reminiscent of Javascript and Typescript so that the army of JS/TS developers out there (around 12 million of them, dwarfing crypto dev numbers) will have a very straightforward learning curve.

Let’s jump forward and say you have written a Leo program, like the bubble sort in the image above - what does Leo actually do when you run the program?

It takes your code, constructs the proof circuit that represents the computation you want to run, populates the input wires with the values you want, runs the circuit, generates proving/verifying keys, and then combines all the relevant data into a ZKP. For example, you could run it on the input data in the image below.