dust/README.md

Dust

A programming language that is fast, safe and easy to use.

Dust is statically typed to ensure that each program is valid before it is run. It offers compile times of less than 100 microseconds on modern hardware. As a bytecode interpreter with a register-based virtual machine, Dust leverages compile-time safety guarantees and optimizations along with beautiful syntax to deliver a unique set of features rarely found in other languages. It is designed to deliver the best qualities of two disparate categories of programming language: the highly optimized but slow-to-compile languages like Rust and C++ and the quick-to-start but often slow and error-prone languages like Python and JavaScript.

Dust's syntax, safety features and evaluation model are based on Rust. Its instruction set, optimization strategies and virtual machine are based on Lua. Unlike Rust and other languages that compile to machine code, Dust has a very low time to execution. Unlike Lua and most other interpreted languages, Dust enforces static typing to improve clarity and prevent bugs. While some languages currently offer high-level features and strict typing (e.g. TypeScript), Dust has a simple approach to syntax that offers flexibility and expressiveness while still being obvious an audience of programmers, even those who don't know the language. Dust is for programmers who prefer their code to be simple and clear rather than complex and clever.

Goals

This project has lofty goals. In addition to being a wishlist, these goals should be used to provide a framework for driving the project forward and making decisions about what to prioritize.

• Fast Compilation: Despite its compile-time abstractions, Dust should compile and start executing quickly. The compilation time should feel negligible to the user.
• Fast Execution: Dust should be generally faster than Python, Ruby and NodeJS. It should be competitive with other modern register-based VM languages like Lua and JavaScript Core.
• Safety: Static types should prevent runtime errors and improve code quality, offering a superior development experience despite some additional constraints.
• Approachability: Dust should be easier to learn than Rust or C++. Its syntax should be familiar to users of other C-like languages to the point that even a new user can read Dust code and understand what it does.
• Web Assembly Support: The dust executable and, by extension, the dust-lang library, should be able to able to compile to WebAssembly and Dust should be able to run in a browser with WASM support. While running on the browser offers some fun opportunities, this is primarally a goal because of WASM's potential to become a general-purpose cross-platform runtime.
• Extended Type System: Beyond specifying the types of variables and function arguments, Dust should offer a rich yet simple type system that allows users to define their own types and compose them with static guarantees about their identity and behavior.
• Excellent Errors: Dust should provide helpful error messages that guide the user to the source of the problem and suggest a solution. Errors should be a helpful learning ressource for users rather than a source of frustration.
• High-Quality Documentation: Dust's documentation should be easy to locate and understand. Users should feel confident that the documentation is up-to-date and accurate.
• All-In-One Binary: The dust executable should aspire to be the only tool a user needs to run Dust code, visualize Dust programs, compile them to intermediate representations, analyze runtime behavior, run a REPL, format code and more as the scope of the project grows. Similar CLI tools like Cargo and Bun have set a high standard for what a single executable can do.
• Advanced Goals: Dust could one day grow to the point that users will want to share their libraries and distribute their programs. In the unlikely event that Dust becomes popular, it could warrant an ecosystem consisting of package management with a central repository, a standard library, a community of users and an organization to maintain the language. These are not within the scope of the project at this time but it may be possible one day if the project is able to realize its other goals. This is included here for maximum ambitiousness.

Non-Goals

Some features are simply out of scope for Dust. As a project's design becomes an implementation, decisions about what a project will not do are required to clarify the project's direction and purpose for both the developers and the users.

• Machine Code Compilation: Dust is not intended to compete with Rust or C++ in terms of runtime performance.
• Complex Abstractions: Dust will not introduce users to new, exotic syntax or convoluted patterns that reduce the clarity of a program. Dust will not support complex paradigm-specific abstractions like inheritance or currying. Dust will remain neither object-oriented nor functional, preferring to expand its features without committing to a single paradigm.
• Gradual Typing: Dust's compiler handles the complexities of static typing and all value and variable types are known before a program runs. The VM is and should remain type-agnostic, leaving it to the sole responsibility of execution.

Dust uses a register-based VM with its own set of 32-bit instructions and a custom compiler to emit the instructions. This should not be confused with a machine code compiler. Despite its compile-time guarantees, Dust falls into the category of interpreted languages. Competing with the runtime performance of Rust or C++ is not a goal. Competing with the approachability and simplicity of those languages is a goal. On the other hand Dust does intend to be faster than Python, Ruby and NodeJS while also offering a superior development experience and more reliable code due to its static typing. Dust's development approach is informed by some [books]¹ and [academic research]² as well as practical insight from [papers]³ written by language authors. See the Inspiration section for more information or keep reading to learn about Dust's features.

write_line("Enter your name...")

let name = read_line()

write_line("Hello " + name + "!")

fn fib (n: int) -> int {
    if n <= 0 { return 0 }
    if n == 1 { return 1 }

    fib(n - 1) + fib(n - 2)
}

write_line(fib(25))

Dust uses the same library for error reporting as Rust, which provides ample opportunities to show the user where they went wrong and how to fix it. Helpful error messages are a high priority and the language will not be considered stable until they are consistently informative and actionable.

error: Compilation Error: Cannot add these types
  |
1 | 40 + 2.0
  | -- info: A value of type "int" was used here.
  |
1 | 40 + 2.0
  |      --- info: A value of type "float" was used here.
  |
1 | 40 + 2.0
  | -------- help: Type "int" cannot be added to type "float". Try converting one of the values to the other type.
  |

Project Status

Dust is under active development and is not yet ready for general use.

Features discussed in this README may be unimplemented, partially implemented, temporarily removed or only available on a seperate branch.

Dust is an ambitious project that acts as a continuous experiment in language design. Features may be redesigned and reimplemented at will when they do not meet the project's performance or usability goals. This approach maximizes the development experience as a learning opportunity and enforces a high standard of quality but slows down the process of delivering features to users. Eventually, Dust will reach a stable release and will be ready for general use. As the project approaches this milestone, the experimental nature of the project will be reduced and a replaced with a focus on stability and improvement.

Language Overview

Syntax

Dust belongs to the C-like family of languages⁴, with an imperative syntax that will be familiar to many programmers. Dust code looks a lot like Ruby, JavaScript, TypeScript and other members of the family but Rust is its primary point of reference for syntax. Rust was chosen as a syntax model because its imperative code is obvious and familiar. Those qualities are aligned with Dust's emphasis on safety and usability. However, some differences exist because Dust is a simpler language that can tolerate more relaxed syntax. The most significant difference between Dust's syntax and evaluation model and Rust's is the handling of semicolons.

There are two things you need to know about semicolons in Dust:

• Semicolons suppress the value of whatever they follow. The preceding statement or expression will have the type none and will not evaluate to a value.
• If a semicolon does not change how the program runs, it is optional.

This example shows three statements with semicolons. The compiler knows that a let statement cannot produce a value and will always have the type none. Thanks to static typing, it also knows that the write_line function has no return value so the function call also has the type none. Therefore, these semicolons are optional.

let a = 40;
let b = 2;

write_line("The answer is ", a + b);

Removing the semicolons does not alter the execution pattern.

let x = 10
let y = 3

write_line("The remainder is ", x % y)

The next example produces a compiler error because the if block returns a value of type int but the else block does not return a value at all. Dust does not allow branches of the same if/else statement to have different types. In this case, adding a semicolon after the 777 expression fixes the error by supressing the value.

// !!! Compile Error !!!
let input = read_line()
let reward = if input == "42" {
    write_line("You got it! Here's your reward.")

    777
} else {
    write_line(input, " is not the answer.")
};

Understanding that semicolons suppress values is also important for understanding Dust's evaluation model. Dust is composed of statements and expressions. If a statement ends in an expression without a trailing semicolon, the statement evaluates to the value produced by that expression. However, if the expression's value is suppressed with a semicolon, the statement does not evaluate to a value. This is identical to Rust's evaluation model. That means that the following code will not compile:

// !!! Compile Error !!!
let a = { 40 + 2; }

The a variable is assigned to the value produced by a block. The block contains an expression that is suppressed by a semicolon, so the block does not evaluate to a value. Therefore, the a variable would have to be uninitialized (which Dust does not allow) or result in a runtime error (which Dust avoids at all costs). We can fix this code by movinf the semicolon to the end of the block. In this position it suppresses the value of the entire let statement. The above examples showed that a let statement never evaluates to a value, so the semicolon has no effect on the program's behavior and could be omitted altogether.

let a = { 40 + 2 }; // This is fine

Only the final expression in a block is returned. When a let statement is combined with an if/else statement, the program can perform side effects before evaluating the value that will be assigned to the variable.

let random: int = random(0..100)
let is_even = if random == 99 {
    write_line("We got a 99!")

    false
} else {
    random % 2 == 0
}

is_even

If the above example were passed to Dust as a complete program, it would return a boolean value and might print a message to the console (if the user is especially lucky). However, note that the program could be modified to return no value by simply adding a semicolon at the end.

Compared to JavaScript, Dust's evaluation model is more predictable, less error-prone and will never trap the user into a frustating hunt for a missing semicolon. Compared to Rust, Dust's evaluation model is essentialy the same but with more relaxed rules about semicolons. In JavaScript, semicolons are both required and meaningless, which is a source of confusion for many developers. In Rust, they are required and meaningful, which provides excellent consistency but lacks flexibility.

Safety

Type System

All variables have a type that is established when the variable is declared. This usually does not require that the type be explicitly stated, Dust can infer the type from the value. Types are also associated with the arms of if/else statements and the return values of functions, which prevents different runtime scenarios from producing different types of values.

Null-Free

There is no null or undefined value in Dust. All values and variables must be initialized to one of the supported value types. This eliminates a whole class of bugs that permeate many other languages. "I call it my billion-dollar mistake. It was the invention of the null reference in 1965." - Tony Hoare

Dust does have a none type, which should not be confused for being null-like. Like the () or "unit" type in Rust, none exists as a type but not as a value. It indicates the lack of a value from a function, expression or statement. A variable cannot be assigned to none.

Immutability by Default

Memory Safety

Values, Variables and Types

Dust supports the following basic values:

• Boolean: true or false
• Byte: An unsigned 8-bit integer
• Character: A Unicode scalar value
• Float: A 64-bit floating-point number
• Function: An executable chunk of code
• Integer: A signed 64-bit integer
• String: A UTF-8 encoded byte sequence

Dust's "basic" values are conceptually similar because they are singular as opposed to composite. Most of these values are stored on the stack but some are heap-allocated. A Dust string is a sequence of bytes that are encoded in UTF-8. Even though it could be seen as a composite of byte values, strings are considered "basic" because they are parsed directly from tokens and behave as singular values. Shorter strings are stored on the stack while longer strings are heap-allocated. Dust offers built-in native functions that can manipulate strings by accessing their bytes or reading them as a sequence of characters.

Feature Progress

This list is a rough outline of the features that are planned to be implemented as soon as possible. This is not an exhaustive list of all planned features. This list is updated and rearranged to maintain a docket of what is being worked on, what is coming next and what can be revisited later.

• Lexer
• Compiler
• VM
• Disassembler (for chunk debugging)
• Formatter
• CLI REPL
• Compile dust's binary and library to WASM
• Browser-based REPL
• CLI
  • Run source
  • Compile source to a chunk and show disassembly
  • Tokenize using the lexer and show token list
  • Format using a built-in formatter
  • Compile to and run from intermediate formats
    • JSON
    • Postcard
  • Integrated REPL
• Basic Values
  • No null or undefined values
  • Booleans
  • Bytes (unsigned 8-bit)
  • Characters (Unicode scalar value)
  • Floats (64-bit)
  • Functions
  • Integers (signed 64-bit)
  • Strings (UTF-8)
• Composite Values
  • Concrete lists
  • Abstract lists (optimization)
  • Concrete maps
  • Abstract maps (optimization)
  • Ranges
  • Tuples (fixed-size constant lists)
  • Structs
  • Enums
• Types
  • Basic types for each kind of basic value
  • Generalized types: num, any, none
  • Type conversion (safe, explicit and coercion-free)
  • struct types
  • enum types
  • Type aliases
  • Type arguments
  • Compile-time type checking
    • Function returns
    • If/Else branches
    • Instruction arguments
• Variables
  • Immutable by default
  • Block scope
  • Statically typed
  • Copy-free identifiers are stored in the chunk as string constants
• Functions
  • First-class value
  • Statically typed arguments and returns
  • Pure (no "closure" of local variables, arguments are the only input)
  • Type arguments
• Control Flow
  • If/Else
  • Match
  • Loops
    • for
    • loop
    • while
• Native Functions
  • Assertions
    • assert
    • assert_eq
    • assert_ne
    • panic
  • I/O
    • read
    • read_line
    • write
    • write_line
  • Miniature Standard Library of Native Functions
    • Byte Functions
    • Character Functions
    • Float Functions
    • Integer Functions
    • String Functions
    • List Functions
    • Map Functions
    • Math Functions
    • Filesystem Functions
    • Network Functions
    • System Functions
    • Randomization Functions

Implementation

Dust is implemented in Rust and is divided into several parts, most importantly the lexer, compiler, and virtual machine. All of Dust's components are designed with performance in mind and the codebase uses as few dependencies as possible. The code is tested by integration tests that compile source code and check the compiled chunk, then run the source and check the output of the virtual machine. It is important to maintain a high level of quality by writing meaningful tests and preferring to compile and run programs in an optimal way before adding new features.

Command Line Interface

Dust's command line interface and developer experience are inspired by tools like Bun and especially Cargo, the Rust package manager that includes everything from project creation to documentation generation to code formatting to much more. Dust's CLI has started by exposing the most imporant features for debugging and developing the language itself. Tokenization, compiling, disassembling and running Dust code are currently supported. The CLI will eventually support a REPL, code formatting, linting and other features that enhance the development experience and make Dust more fun and easy to use.

Lexer and Tokens

The lexer emits tokens from the source code. Dust makes extensive use of Rust's zero-copy capabilities to avoid unnecessary allocations when creating tokens. A token, depending on its type, may contain a reference to some data from the source code. The data is only copied in the case of an error. In a successfully executed program, no part of the source code is copied unless it is a string literal or identifier.

Compiler

The compiler creates a chunk, which contains all of the data needed by the virtual machine to run a Dust program. It does so by emitting bytecode instructions, constants and locals while parsing the tokens, which are generated one at a time by the lexer.

Parsing

Dust's compiler uses a custom Pratt parser, a kind of recursive descent parser, to translate a sequence of tokens into a chunk. Each token is given a precedence and may have a prefix and/or infix parser. The parsers are just functions that modify the compiler and its output. For example, when the compiler encounters a boolean token, its prefix parser is the parse_boolean function, which emits a LoadBoolean instruction. An integer token's prefix parser is parse_integer, which emits a LoadConstant instruction and adds the integer to the constants list. Tokens with infix parsers include the math operators, which emit Add, Subtract, Multiply, Divide, Modulo and Power instructions.

Functions are compiled into their own chunks, which are stored in the constant list. A function's arguments are stored in its locals list. Before the function is run, the VM must bind the arguments to values by filling locals' corresponding registers. Instead of copying the arguments, the VM uses a pointer to one of the parent's registers or constants.

Instruction Optimization

When generating instructions for a register-based virtual machine, there are opportunities to optimize the generated code by using fewer instructions or fewer registers. While it is best to output optimal code in the first place, it is not always possible. Dust's uses a single-pass compiler and therefore applies optimizations immeadiately after the opportunity becomes available. There is no separate optimization pass and the compiler cannot be run in a mode that disables optimizations.

Type Checking

Dust's compiler associates each emitted instruction with a type. This allows the compiler to enforce compatibility when values are used in expressions. For example, the compiler will not allow a string to be added to an integer, but it will allow either to be added to another of the same type. Aside from instruction arguments, the compiler also checks the types of function arguments and the blocks of if/else statements.

The compiler always checks types on the fly, so there is no need for a separate type-checking pass. Type information is removed from the instructions list before the chunk is created, so the VM (which is entirely type-agnostic) never sees it.

Instructions

Dust's virtual machine uses 32-bit instructions, which encode seven pieces of information:

Bit	Description
0-4	Operation code
5	Flag indicating if the B field is a constant
6	Flag indicating if the C field is a constant
7	D field (boolean)
8-15	A field (unsigned 8-bit integer)
16-23	B field (unsigned 8-bit integer)
24-31	C field (unsigned 8-bit integer)

Operations

The 1.0 version of Dust will have more than the current number of operations but cannot exceed 32 because of the 5 bit format.

Stack manipulation

• MOVE: Makes a register's value available in another register by using a pointer. This avoids copying the value or invalidating the original register.
• CLOSE: Sets a range of registers to the "empty" state.

Value loaders

• LOAD_BOOLEAN: Loads a boolean to a register. Booleans known at compile-time are not stored in the constant list. Instead, they are encoded in the instruction itself.
• LOAD_CONSTANT: Loads a constant from the constant list to a register. The VM avoids copying the constant by using a pointer with the constant's index.
• LOAD_LIST: Creates a list abstraction from a range of registers and loads it to a register.
• LOAD_MAP: Creates a map abstraction from a range of registers and loads it to a register.
• LOAD_SELF: Creates an abstraction that represents the current function and loads it to a register.

Variable operations

• GET_LOCAL: Loads a variable's value to a register by using a pointer to point to the variable's canonical register (i.e. the register whose index is stored in the locals list).
• SET_LOCAL: Changes a variable's register to a pointer to another register, effectively changing the variable's value.

Arithmetic

Arithmetic instructions use the A, B and C fields. The A field is the destination register, the B and C fields are the arguments, and the flags indicate whether the arguments are constants.

• ADD: Adds two values and stores the result in a register. Unlike the other arithmetic operations, the ADD instruction can also be used to concatenate strings and/or characters. Characters are the only type of value that can perform a kind of implicit conversion. Although the character itself is not converted, its underlying bytes are concatenated to the string.
• SUBTRACT: Subtracts one argument from another and stores the result in a register.
• MULTIPLY: Multiplies one argument by another and stores the result in a register.
• DIVIDE: Divides one value by another and stores the result in a register.
• MODULO: Calculates the division remainder of two values and stores the result in a register.
• POWER: Raises one value to the power of another and stores the result in a register.

Logic and Control Flow

Logic instructions work differently from arithmetic and comparison instructions, but they are still essentially binary operations with a left and a right argument. These areguments, however, are other instructions. This is reminiscent of a stack-based virtual machine in which the arguments are found in the stack rather than having their location encoded in the instruction. The logic instructions perform a check on the left-hand argument and, based on the result, either skip the right-hand argument or allow it to be executed. A TEST is always followed by a JUMP. If the left argument passes the test (a boolean equality check), the JUMP instruction is skipped and the right argument is executed. If the left argument fails the test, the JUMP is not skipped and it jumps past the right argument.

• TEST
• TEST_SET

Comparison

• EQUAL
• LESS
• LESS_EQUAL

Unary operations

• NEGATE
• NOT

Execution

• CALL
• CALL_NATIVE
• JUMP
• RETURN

Virtual Machine

The virtual machine is simple and efficient. It uses a stack of registers, which can hold values or pointers. Pointers can point to values in the constant list or the stack itself.

While the compiler has multiple responsibilities that warrant more complexity, the VM is simple enough to use a very straightforward design. The VM's run function uses a simple while loop with a match statement to execute instructions. When it reaches a Return instruction, it breaks the loop and optionally returns a value.

Previous Implementations

Dust has gone through several iterations, each with its own design choices. It was originally implemented with a syntax tree generated by an external parser, then a parser generator, and finally a custom parser. Eventually the language was rewritten to use bytecode instructions and a virtual machine. The current implementation is by far the most performant and the general design is unlikely to change.

Dust previously had a more complex type system with type arguments (or "generics") and a simple model for asynchronous execution of statements. Both of these features were removed to simplify the language when it was rewritten to use bytecode instructions. Both features are planned to be reintroduced in the future.

Inspiration

[Crafting Interpreters] by Bob Nystrom was a great resource for writing the compiler, especially the Pratt parser. The book is a great introduction to writing interpreters. Had it been discovered sooner, some early implementations of Dust would have been both simpler in design and more ambitious in scope.

[The Implementation of Lua 5.0] by Roberto Ierusalimschy, Luiz Henrique de Figueiredo, and Waldemar Celes was a great resource for understanding register-based virtual machines and their instructions. This paper was recommended by Bob Nystrom in [Crafting Interpreters].

[A No-Frills Introduction to Lua 5.1 VM Instructions] by Kein-Hong Man has a wealth of detailed information on how Lua uses terse instructions to create dense chunks that execute quickly. This was essential in the design of Dust's instructions. Dust uses compile-time optimizations that are based on Lua optimizations covered in this paper.

[A Performance Survey on Stack-based and Register-based Virtual Machines] by Ruijie Fang and Siqi Liup was helpful for a quick yet efficient primer on getting stack-based and register-based virtual machines up and running. The included code examples show how to implement both types of VMs in C. The performance comparison between the two types of VMs is worth reading for anyone who is trying to choose between the two¹. Some of the benchmarks described in the paper inspired similar benchmarks used in this project to compare Dust to other languages.

License

Dust is licensed under the GNU General Public License v3.0. See the LICENSE file for details.

References

---

1. Crafting Interpreters ↩︎

2. A Performance Survey on Stack-based and Register-based Virtual Machines ↩︎

3. The Implementation of Lua 5.0 ↩︎

4. List of C-family programming languages ↩︎