The Goose Programming Language

原文

A memory-safe systems language with no heap allocator, garbage collector, or lifetime annotations. In this repository's benchmarks, Goose runs faster than C++ and Rust while using less memory.

Tutorial · Reference · Specification · Packages · Samples · Benchmarks · Standard library

Goose has syntax familiar to C and Rust programmers, but there is no heap. Every dynamic value lives inline on a data stack managed by the compiler. Growth advances a pointer, and memory is freed when its scope ends. The language's type and lifetime rules make this memory model safe to use.

Why Goose

Faster than C++ and than safe Rust, while memory safe. Over sixteen benchmarks Goose runs at 3.3x the speed of idiomatic C++, 1.16x hand-optimized C++ and 1.12x the best safe Rust, on 1.9x, 1.3x and 1.2x less memory (results). These gains come from Goose's data layouts and memory model.
No allocator, no GC, no reference counting, no destructors. Memory is a handful of data stacks that the compiler assigns statically. Freeing a million-element structure is one store, however deeply it nests.
Growth preserves references. A reference into a growing array stays valid for as long as the array does. You keep typed references where C++ must reserve and safe Rust uses u32 indices in the corresponding benchmarks.
Memory safe with zero annotations. No lifetime syntax, no aliasing or exclusivity rules, no unsafe. The compiler infers what every reference is rooted in and rejects references that could outlive their owners.
Nested data stays inline. A string, an array of strings, a record with variable-size fields and an array of those records are each one contiguous block with no pointer in it. A record that is 160 bytes and an allocation in C++ is 29 bytes and none in Goose.
Enums that cost what they hold. Variable-mode ADTs give each value its own variant's size rather than the largest one's: 4x less memory and 2x the speed of a Rust enum on the benchmark that exercises it.
Links narrower than pointers. A relative reference stores a typed, checked link as a 1, 2 or 4-byte offset. Structures built from them are position independent, so your data structure is already its file format: saving is a write, loading is a read plus a verification pass that rejects hostile bytes.
Everything is built in place, guaranteed. A value is constructed at its final destination through any depth of calls. items.push(parse(line)) writes the parsed record straight into the array, and returning a growable array by value costs nothing.
Returns across multiple calls. return err from load returns from a function any number of frames up, statically checked, with no unwinder, no Result type and no ? on every call.
Threads that share nothing. A worker is compiled as a separate program with its own memory, and flat values cross typed queues as a memcpy. Data races, locks, atomics and memory orderings do not exist in the language.
Generics and higher-order functions with no overhead. An untyped parameter is generic. Function values are compile-time entities, so xs.filter() { it > 0 } compiles to the loop it looks like and builds its result straight into its destination.
Plain C in, plain C out. Goose compiles to one C file, so it runs wherever a C compiler does and calls C directly through extern fn. The bundled TinyCC backend compiles and runs a program in-process, with no build step.

The tutorial walks through all of this by example, the reference covers the whole language topic by topic, the specification has the exact rules, and the benchmarks have the numbers, losses included.

Features

This section focuses on what distinguishes Goose. The tutorial explains these features in more detail, and the samples show them in thirty-one complete programs.

One memory model: stacks, and scope exit is the free

A program has the native call stack, static data and N data stacks, where the compiler works out N. A data stack is a large address-space reservation with a bump pointer, and there is no other memory. At most one resizable value is live per stack and it is always on top, so growth never moves anything and never checks a capacity. All of this is proved at compile time; the runtime tracks only the bump pointers.

for round in 3 {
    var scratch: u8[>..] = [];                        // grow-only: growth is a pointer bump
    for i in 100000 { scratch.push((i % 256) as! u8); }
    print("round ", round, ": ", scratch.len, " bytes");
}                                                     // the free: one store to the stack top

struct Item { id: i32, weight: f32 }

var items: Item[>..] = [];
let first .= items.push(Item { 1, 0.5 });             // a reference to element 0
for i: i32 in 2..1000001 { items.push(Item { i, 0.0 }); }
first.weight = 99.5;                                  // still valid, a million pushes later

push returns a reference to the new element, so a program can link elements while building the array. A vector<T> or Vec<T> may reallocate and cannot provide this guarantee. Stable references account for several benchmark gains.

Safe references, no annotations

Every reference and slice has a static root: the variable that bounds its target's lifetime. A reference must not outlive the variable that owns its target or access that target through an incompatible type. The compiler infers roots and specializes functions for them, so no annotations are needed. There are no aliasing or exclusivity rules. When a lifetime check fails, the error names the reference's root and its destination:

fn longest(a: u8[:], b: u8[:]) -> u8[:] { if a.len >= b.len { a } else { b } }

var outer: u8[>..] = [];
var w = outer[..];
{
    var inner: u8[>..] = [];
    format(inner, "inner text");
    w = longest(outer, inner);     // error: storing a reference rooted at inner,
}                                  //        which does not outlive the destination (§9.2)

A slice T[:] lets a function accept a range from any array kind without copying its elements. For example, split returns slices into its input, and a dictionary keyed by u8[:] stores views of strings rather than copies.

Nested data stays inline

There is no single array type. There is a family that differs only in what happens to the size, and every member is [metadata][elements...], inline and packed, never a pointer to an element block:

Spelling	What it is
`T[k]`	fixed size, known at compile time
`T[]`, `T[varint]`	sized at construction, frozen after; a fixed or variable-width length
`T[..k]`, `T[..]`	capacity inline; grows and shrinks within it
`T[>..]`	grow-only: the workhorse; references into it stay valid
`T[>..<]`	grow-shrink: stacks, queues, heaps

Strings are just u8 arrays: u8[>..] is a builder, u8[] a finished string stored inline in whatever holds it, u8[..16] a small string inside a struct, u8[:] a view. A struct may contain variable-size parts, and they sit inline in declaration order, so a record is a run of bytes with nothing indirect in it:

struct Item  { sku: u8[varint], qty: varint, cents: varint }
struct Order { id: varint, customer: u8[varint], items: Item[varint] }

var book: Order[>..] = [];
book.push(Order { id: 1001, customer: "alice",
                  items: [Item { sku: "SKU-441", qty: 2, cents: 1999 },
                          Item { sku: "SKU-7", qty: 1, cents: 500 }] });

That order is 29 bytes and 0 allocations. As C++ std::string + std::vector<Item> it is 160 bytes and 1 allocation, and as Rust String + Vec<Item> 153 bytes and 4. A whole order book is one array that streams through the cache. The price is that an array of variable-size elements is sequential: you can iterate it but not index it (unless you keep a second array of references into it as an index).

Enums in two sizes

Algebraic data types are the only dynamic polymorphism: no inheritance, no vtables. Every ADT can be stored two ways, chosen at the point of use. Fixed mode (Shape) is a tag plus room for the largest payload, indexable and overwritable. Variable mode (Shape..) gives each value exactly its variant's size; the array becomes sequential and a value never changes variant, and in exchange you may take references into a payload:

enum Shape { Circle { r: f64 }, Rect { w: f64, h: f64 }, Dot }

var packed: Shape..[>..] = [];                 // 9, 17 and 1 bytes, not 17 each
packed.push(Shape.Circle { r: 1.0 });
packed.push(Shape.Rect { w: 2.0, h: 3.0 });
packed.push(Shape.Dot);
for s in packed {
    match s { Rect &r => { r.w += 1.0; }, _ => {} }   // edits the payload in place, inside the array
}

fn area(s: Shape.Circle) -> f64 { 3.14159 * s.r * s.r }
fn area(s: Shape.Rect) -> f64   { s.w * s.h }
fn area(s: Shape.Dot) -> f64    { 0.0 }

for s in packed { print(s, " area ", area(s)); }

Links narrower than pointers

A T& is a machine address: eight bytes, never dangling. A relative reference is the same link stored as a narrow offset: T&<u32> is measured from the field itself to a target in the same array, so the structure is position independent, and T&<u32 in pool> from a named pool's base, so other arrays can link into the pool. T&<u32>? uses offset 0 as null. Here is a binary search tree in one grow-only array, with 12-byte nodes:

struct Node { key: i32, left: Node&<u32>?, right: Node&<u32>? }   // 12 bytes, links included

fn insert(pool: Node[>..]&, key: i32) {
    if pool.len == 0 { pool.push(Node { key: key }); return; }
    var cur .= pool[0];                             // .= binds a reference; = would copy the node
    loop {
        if key == cur.key { return; }
        let next = if key < cur.key { cur.left } else { cur.right };
        if next { cur .= next; continue; }          // narrowed by `if`: next is a Node&
        if key < cur.key { cur.left .= pool.push(Node { key: key }); }
        else             { cur.right .= pool.push(Node { key: key }); }
        return;
    }
}

References are transparent (no *, no ->), .= binds or retargets one, and Node? is a nullable reference that if, guard and assert narrow. The insert is one push and one store, and the push cannot invalidate cur. When lifetimes are not nested, a reusable pool pairs a grow-only array with a hidden freelist: alloc_ref reuses a slot or pushes, free hands one back, and since nothing is ever actually freed, a stale slot reads a different value of the correct type rather than corrupting memory.

Your data is already a file format

var image: u8[>..] = tree.to_bytes();           // a framed byte image of the whole array
var loaded, ok = from_bytes<Node[>..]>(image);  // verified before it becomes a value
image[image.len - 3] = 200;                     // tamper with a link ...
var bad, bok = from_bytes<Node[>..]>(image);    // ... and it is false and an empty array

spec §4.3) says a constructed value is always built in its final home, propagated top-down through calls. A function returning a grow-only array by value writes its elements straight into the caller's variable, or into a field of the record being built inside another array, so out-parameters mostly do not appear.

words.push(str("word", i));                    // formatted straight into the new element
let evens = xs.filter() { it % 2 == 0 };       // built straight into `evens`: no temporary
book.push(Order { id: 1001, customer: "alice", items: parse_items("SKU-441:2:1999;SKU-7:1:500") });

struct User { name: u8[..16], age: i32 }

fn load(text: u8[:]) -> User[>..], u8[] {
    var users: User[>..] = [];
    each_split(text, '\n') { users.push(parse_user(it)); };
    return users, "";
}

fn parse_user(line: u8[:]) -> User {              // returns a User: no Result, no error parameter
    let comma = find(line, ",");
    guard comma >= 0 else { return [], str("expected name,age: ", line) from load; }
    let age, ok = parse_int(line[comma + 1..]);
    guard ok else { return [], str("bad age: ", line) from load; }
    let name = trim(line[..comma]);
    return User { name: name, age: age as i32 };
}

return E from f returns E as the result of the innermost active call of f, however many frames up, and every function in between keeps its plain signature. It is checked statically, so every call of parse_user must lie inside a load call and nothing is uncaught at runtime. It is a hidden discriminant checked per frame rather than an unwinder, and the message is built directly where load's caller wants it. The parsers in the samples use it for every syntax error.

Generics and function blocks

fn twice(x) { x + x }                              // an untyped parameter is a generic one

fn each_pair<T, F>(xs: T[:]) {                     // F is a function value: a compile-time entity
    for i in 0..xs.len - 1 { F(xs[i], xs[i + 1]); }
}

fn first_gap(xs: i64[:]) -> i64 {
    each_pair(xs) { a, b => if b - a > 1 { return a; } };   // returns from first_gap, not each_pair
    return -1;
}

let evens = xs.filter() { it % 2 == 0 };
let total = fold(xs, 0) { acc, x => acc + x };
sort(xs) { a, b => a > b };

Everything is monomorphized. Type arguments are inferred from argument types; parameters absent from those types can be supplied explicitly. Function values are passed as generic parameters: every call is direct and inlinable, they cannot escape, and there are no closure objects or function pointers, so a higher-order function compiles to exactly the loop it looks like. A block may return from its lexically enclosing function, and nested functions see the enclosing function's locals.

thread_fn worker() {                                // a separate program with its own memory
    loop {
        let job = qget<Job>();                      // blocks on the typed queue for Job
        guard job.n >= 0 else { break; }            // -1 means stop
        qput(Result { n: job.n, digits: count_digits(job.n) });
    }
}

for i in n { ids.push(thread_spawn(worker)); }

There is no shared mutable memory. A thread_fn and everything it calls is compiled as its own program with its own data stacks and its own copies of the globals. Values cross through typed queues, one per type, and must be flat, with no references at any depth. That is cheap because a flat Goose value is contiguous: a job or a result carries real data, pixels included, and crossing is a memcpy.

A failed check or abort in a worker started with thread_spawn_contained ends only that worker. Its message goes to whoever waits for it, not to stderr, so a supervisor can log it and start another:

var why: u8[>..] = [];
while !thread_wait(thread_spawn_contained(serve, attempt), why) {
    log(why);                                       // "assert failed (serve.goose:12)"
    why.clear();
    attempt++;
}

extern fn hypot(x: f64, y: f64) -> f64;             // straight from libm
extern fn crc32_bytes(s: const u8[:]) -> u32;       // a slice crosses as { data, len }
extern fn stats_of(xs: i32[:], out: Stats&);        // a struct filled through a pointer

An extern fn binds a Goose signature to a C symbol. The math and os modules use this interface. Only types with supported C representations may cross the boundary; unsupported signatures are rejected at the declaration. The compiler emits one C file for the whole program. The bundled TinyCC backend can compile and run that C inside the Goose compiler's process.

Where the speed comes from

Much of the speed comes from the memory model: no heap allocation or per-object teardown, contiguous data, narrow links, and enums sized for the variant they contain. Every index is bounds-checked, and the compiler removes checks it can prove unnecessary. An assert on a slice length often lets a kernel eliminate its remaining checks and vectorize. --bce-lines reports the checks that remain. checkfree fn rejects a kernel if any bounds check survives; index types let graph edges retain validation done during construction. Benchmark measurements use whole-process wall-clock time, including teardown.

Geometric mean over 16 benchmarks	vs idiomatic C++	vs hand-optimized C++	vs best safe Rust
speed, MSVC backend	3.51x	1.24x	1.13x
speed, clang backend	3.54x	1.26x	1.19x
peak memory	1.95x less	1.32x less	1.25x less

summary explains the gains and losses; results.md has every measurement, and design.md explains what the suite tests.

What it costs you

You think about where data lives: who owns this, and how long does its scope last. Usually the answer is "the function that builds it", and that is free; when it is not, it is a reusable pool.
Recursive functions cannot keep growable data across a recursive call; scratch ends before the call, and what outlives it is passed in as a pool.
Arrays of variable-size elements iterate but do not index (short of an index of references kept beside them), a fixed-mode enum cannot be pointed into, and a variable-mode one cannot be overwritten. You choose per container.
No escaping closures, no function pointers, no dynamic dispatch beyond ADT tags, and whole-program compilation only.
A slot handed back to a reusable pool and still named reads whatever its next owner put there: a logic bug, never memory corruption.

Tutorial §18 is the full list.

Install a release

Prebuilt compilers for Windows (x64), Linux (x64) and macOS (Apple silicon and Intel) are on the releases page, with the graphics, audio, ui and physics packages compiled in. Unpack one anywhere and put its directory on PATH: the compiler finds the standard library, TinyCC's runtime and the packages beside itself, and keeps what it builds under ~/.goose (GOOSE_HOME). The archive also holds these docs, the samples and the VS Code extension.

Running a program in-process (goose file.goose) needs nothing else on Windows. On Linux it needs the C library's headers (libc6-dev, or glibc-devel); on macOS, the SDK of the Xcode command line tools (xcode-select --install). goose build also needs a C compiler: Visual Studio 2022 or later, or clang, on Windows; gcc or clang elsewhere. The Linux compiler needs glibc 2.35 or later (Ubuntu 22.04, Debian 12), the macOS one macOS 13.3 or later. macOS keeps a downloaded archive's files from running until xattr -dr com.apple.quarantine is run on the unpacked directory.

Build and run

You need CMake 3.27 or later, a C++20 compiler (MSVC, clang or gcc) and Python 3 for the test and sample runners. TinyCC, which the in-process backend is built from, is part of the tree. The graphics, audio, ui and physics modules are packages in repositories of their own (goose_gfx and goose_physics; docs/design/packages.md): -DGOOSE_BUILTIN_LIBS=all fetches them at the pinned tags (git, at configure time) and compiles them into the compiler, so their programs run with nothing else installed. Without it the compiler builds alone, and a program importing one of them has it built into ~/.goose the first time, which needs git, cmake and a C compiler.

git clone https://github.com/aardappel/goose
cd goose
cmake -B build -DCMAKE_BUILD_TYPE=Release -DGOOSE_BUILTIN_LIBS=all
cmake --build build --config Release

third_party/SDL/docs/README-linux.md); without them the build leaves the gfx module out and says what to install.

The runner scripts prefer build/Release, then build/RelWithDebInfo, then build, then build/Debug. Pass --exe to select a specific compiler; use an explicit Debug executable when testing with compiler assertions enabled. The compiler is build/goose (build/Release/goose.exe with the Visual Studio generator), and it finds the standard library in the source tree it was built from. On Windows 10 version 1903 and later, its embedded manifest selects a UTF-8 process code page so compiler paths do not depend on the system locale. Earlier Windows versions retain their legacy code page. Generated native executables retain their own process settings.

Run a program straight from source, in-process (goose run says the same explicitly, and goose check only typechecks):

build/goose samples/01_tour.goose

Or build an executable, which lands beside the source (-o puts it elsewhere). The compiler finds a C compiler on the machine (goose toolchain says which: MSVC or clang on Windows, cc, gcc or clang elsewhere; --cc chooses) and links the generated C with the runtime and whatever native modules the program uses, graphics included. Programs that use threads need this route, since TinyCC cannot place thread-local storage.

build/goose build samples/01_tour.goose && samples/01_tour
build/goose build samples/27_gfx_cube.goose && samples/27_gfx_cube

--debug turns on the overflow, range and tag checks in the generated C, each abort naming its source line (and an overflow or a cast the values involved), and builds the C with debug information; --dry-run prints the commands a build would run, for a build system of your own; -v prints them as they run. Intermediates go under ~/.goose (GOOSE_HOME), the runtime object compiled once per C compiler. Useful flags of both forms: -O0/-O1/-O2 set the inlining level (a build defaults to -O2, a run to -O1), --bce-lines reports the bounds checks kept per line, and -DGS_DEBUG=1 is what --debug defines. Every resizable value lives on a data stack of 2 GB of reserved address space, committed as it is used: --stack-reserve 16G changes that for a program, --stacks reports how many data stacks the program and each of its workers can take and the cap that puts on hardware_threads(), and -DGS_STACK_STATS=1 makes a program report its actual use as it ends.

A program with C of its own names it in a sidecar beside the source, foo.build beside foo.goose: c_sources = ["impl.c"];, with c_include, c_defines, c_libs and _windows, _linux or _macos variants of each for one platform's part. Both forms build it: goose build links it in, and goose run builds it into a library the in-process run loads, so an extern fn reaches it either way. A library does the same with a sidecar beside its entry (or names the static library target of its own CMake project, cmake_target = "x";, which the compiler builds through cmake), and a program takes a library with import name from "source"; in its root file: a directory ("./lib"), or a git repository at a tag or commit ("owner/repo@v1" on GitHub, "host/owner/repo@ref"), fetched into ~/.goose and built there once per C compiler (docs/design/packages.md).

Underneath, goose -o tour.c tour.goose writes the C, which holds the program and the part of the runtime that inlines into it; the rest of the runtime (the OS layer, data stack reservation, threads, printing) is one more C file, which goose --emit-runtime goose_runtime.c writes, to be compiled once and linked with every program (cc -O2 tour.c goose_runtime.o -o tour -lm -pthread; on Windows cl /O2 tour.c goose_runtime.obj). Build the runtime with the compiler and flags the programs use; it takes no -D of its own, and a program from another version of the compiler fails to link against it. --standalone writes a C file that holds the whole runtime instead, and builds on its own. A program using audio, gfx, physics or ui also links that module's layer, which goose --audio-link msvc|cc, --gfx-link, --physics-link and --ui-link name in a response file (cc cube.c goose_runtime.o -o cube @$(goose --gfx-link cc), a ui program's before the gfx one it draws through). goose build --dry-run prints all of this for the program at hand.

audio reference.

The test suite and the samples run on Windows, macOS and Linux:

python test/run_tests.py
python samples/run_samples.py

VS Code extension gives syntax highlighting, the compiler's language server (goose lsp: errors as you type, hover, go to definition, completion, rename, symbols) and one-key runs through the JIT:

code --install-extension vscode/goose-language.vsix

editors has the configuration for Neovim, Helix and Emacs.

Documentation

Documentation index: the map of everything below, and the root of the documentation site built from these files (how).
Tutorial: the friendly introduction, by example. Read this first.
Language reference: every feature, topic by topic, with a compiling example for each: the whole language, written to be read.
Language specification: the exact rules, when you want to know why something did not compile.
Samples: thirty-one complete programs in reading order, from a tour of the language to a JSON parser, a threaded Mandelbrot, a file tree built from two pools, a spinning cube on the GPU, thousands of boxes raining into a heap and a to-do list in windows of widgets.
Standard library: fourteen modules, all readable Goose under stdlib/, including gfx, graphics on SDL3's GPU API (how it is built), physics, rigid body physics on Box3D (how it is built), and ui, fonts, text rendering and game HUDs, windows and widgets on Nuklear, drawn through gfx (how it is built).
Building programs and using packages: goose build, libraries from git repositories or directories, a program's own C, and how to make a package of your own.
Benchmarks: the numbers, with the full results and the design behind them.
Implementation notes: how the compiler works, pass by pass, and how it is tested.

Status

Goose is new. What exists today is a whole-program compiler of about thirty thousand lines of C++, the specification, the standard library, the samples, and a test suite that CI runs on Windows, macOS and Linux with an extra sanitizer job. Deliberately out of scope for now: moves for resizable values, more than one resizable per struct, labeled break, namespace privacy, and more OS/library access. Open items are tracked in the specification's Appendix B.

License

Goose is licensed under the Apache License, Version 2.0.

Authors

Wouter van Oortmerssen: Language Design, Compiler Design, Coding standards. home page, twitter.

Claude Fable: Compiler implementation, Benchmarking, Sample & Doc writing.

History & Use of AI

This repo was produced almost entirely with AI, from a human language design. I had designed Goose several years ago, and had started to implement it, but running a game startup (which is built on another programming language of mine, Lobster) there was no time to finish it. Which was sad, because I knew Goose could do things other languages can't, and it should exist.

I had not expected AI to help with this until Fable came out. I thought it might be capable enough to do a good job. I made it essentially clone the style and structure of my other recent compiler (Lobster), which is why if you look at the code, it looks rather similar to that. My initial design had left lots of things unspecified, and lots of back and forth with Fable made me decide on all of those, and it is now a better language for it.

It is also an experiment in using AI to implement a new language, rather than reproduce an existing one.

You may wonder why I had it work in C++, if clearly I could have used any language, like Rust, or my own Lobster, or.. Goose itself (that may still happen). With Fable, it was my observation that it is almost equally capable in any language, and the strong guardrails of Rust or other languages are not as pressing as they once were. Since the compiler emits C, you likely already need to have a C/C++ compiler around, so sticking inside one ecosystem would seem to simplify deployment and adoption. I've also integrated libtcc and who knows what other C libraries in the future. And, like I said, to have the compiler code mimic my existing Lobster compiler seemed fun, at least I can read it like it is my own.