Architecture.md

Architecture

This project consists of four main steps that, when put together, can run Lioness source code from a raw string to an executed result.

Lioness pipeline

Full pipeline:

🛬 source code	➡️	Lexer	➡️	Parser	➡️	Compiler	➡️	Interpreter	➡️	result 🛫

The following table describes the I/O of each step in the pipeline:

	Input	Output
Lexer	Source code	Tokens
Parser	Tokens	AST
Compiler	AST	Scorpion Bytecode
Interpreter	Scorpion Bytecode	Execution result

Note: Each step in the pipeline is independent from all others. This makes unit testing very straight forward.

Practical workflow:

In practice it is common to want to compile source code once and execute it multiple times. The following pipelines provide this in an efficient way:

Pipeline 1:

🛬 source code	➡️	Lexer	➡️	Parser	➡️	Compiler	➡️	Bytecode	➡️	encode 🛫

This pipeline can be written in Swift as:

public func compileToBytecode(_ source: String) throws -> BytecodeBody {
    return try (lexer |> parse |> compile)(source)
}

This makes use of the custom |> (pipe) operator.

Pipeline 2:

🛬 decode	➡️	Bytecode	➡️	Interpreter	➡️	result 🛫

The encoding/decoding will typically be followed by writing/reading the bytecode to disk, to enable efficient distribution.

Generally the performance of the interpreter step (pipeline 2) is deemed more important than compilation time (pipeline 1). A concrete example of this is compile time code optimization: this will, by definition, slow down compilation time. But the performance gains at runtime are worth it.