The Goose Programming Language

https://strlen.com/

> 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.

I’m having trouble parsing that last sentence.

how to perform this copy without atomics?

do the workers run as threads or processes?

also you claim it's faster than rust and c++. but for certain kinds of software it's certainly (and substantially) slower, right?

Looking at the repo it seems like the N stacks generated by the compiler are placed at least 2gb apart in virtual memory, have you run into any cases where that has been overflowed during runtime? The compiler cannot know which of the stacks are going to be used more than others and in a large complex program with many stacks any one of them could fail. I imagine this being an issue depends on target application - if you know you are building a game that you know the exact size of your levels / entity counts beforehand you know this is fine but if you were doing data processing / parsing potentially malicious user input it may be a problem.

I'm also interested how the memory locality works. Here you have the bases of your stacks at a series of very sparse virtual memory intervals which will be mapped by the page table to some physical memory addresses, does having them be so sparse cause any issues?

There are some unique ideas here - lifetimes on references to growable+shrinkable stacks, "balancing" stacks in recursive functions - and I'm glad you were able to use coding agents to actually materialize them.

That is about where our similarities end, though, since I'm doing quite a lot of other stuff in the midst as well (much heavier type stuff, fully incremental, retargetable, reflection, integer range tracking, blah blah blah), and the more goals you have, the complexity blows up exponentially. I do think that the region based memory part alone is worthwhile to have as a language feature, so I applaud your pragmatism. I like your syntax for returning through call stacks, too.

There are other languages that do this, though. Did you look into any of the others? Or ones like Odin which give you the configurable bump allocators and scratch space as well? Mainly I'm curious about your opinions of prior art.

Hows the compile time? Do you have a number or is it similar to another language?

I like the XY language, what do you think? https://nsl.com/k/xy/xy.htm

Do you know if Goose is the first time something like this has been done?

I'm wondering what kind of architectural corners this forces the programmer into ... have you found any so far?

How are you deciding how many stacks to use?

(And why isn't it Amiga E?)

And these strings in Goose are 6 bytes, while the ones in C++ are apparently 16 to 24 bytes each.

The obvious downside is that resizing any string but the last requires moving everything down the stack.

With objects that never need resizing, you can of course have much simpler memory layouts.

For example, you can build up a tree of all variable sized nodes inside a single array.

Where it gets interesting is if you must arbitrarily delete tree nodes, and you can't structure it to do that in stack order. The language has various tools for this, like fixed arrays with capacity, or pools of either single elements or runs of elements.

In Rust parlance this would be the difference between a `Vec<Vec<T>>` (many `Vec`s, each can be resized) and a `Vec<Box<[T]>>` (many `Box`ed slices, each with a dynamic size, but none of them can be resized).

I bet you can exploit dynamically sized values to rebuild resizable values, with the downside however that you'll likely leak their memory until you exit the current scope.

It's not entirely mad to do it this way, and I can see some benefits. For one, you might have multiple of these pools across the program for different data-types, which would make allocating to any one of them a cheaper operation. It is much more reference safe since you are only ever freeing stuff in a certain context and you can still never have dangling pointers. When you look at memory safe languages, they all default to this eventually. Like Rust in the advanced case will have you implementing your own allocator, lot's of games use this thing called ECS which is essentially a kind of allocator. Goose would just have it be more common.

Goose has a built-in generic hash table called dictionary<K, V>, provided by its standard library.

https://aardappel.github.io/goose/docs/stdlib.html#dictionar...

The name is an animal because all my past PL designs are animals (I also made Lobster etc). Goose seemed like a fun name.

If it is potentially completely unbounded, you need different solutions like a pool, or essentially reconstructing etc.

Seems any compiled language with automatic memory can make use of the techniques to obtain speed ups.

Back then though, they couldn't lean on large 64-bit address spaces like Goose can. They implemented all of this with a chain of blocks of memory instead, and tracked most of it at runtime that Goose now does at compile time.

https://github.com/aardappel/goose/blob/master/docs/design/p...

At compile time, Goose will analyze your program and determine a number of stacks, N, for it. N is the maximum number of "growable" items you can have in existence at any given point in time. Using virtual memory tricks, each stack can grow up to 2GB, but it uses a contiguous address space and only uses as much physical memory as it actually needs.

For the program you're describing, I think you would end up with two stacks: one to parse the input and a second to print it. When you parse the input, Goose reads characters from the string one at a time and puts them onto the stack. Once it has hit the end of value, it will update the stack so it now represents the decoded JSON value (strings will just leave the characters in place, numbers will pop off the characters and push the number onto the stack). Goose repeats this until it has parsed the whole JSON, and now the whole JSON is on the stack.

Then, when you print the JSON, Goose uses the second stack to build a string. Like the parsing approach, it iterates through each element of the JSON and pushes its string representation onto the stack. Once it's done, it resets the stack pointers to free the memory.

This is really nice because allocating memory is just adding to the pointer, and freeing it is subtracting from the pointer.

In contrast, Rust automatically inserts malloc() and free() calls throughout your code, which are much more expensive than pointer arithmetic. On top of that, freeing a vector of heap-allocated objects is O(n), whereas if done right in Goose, it would be O(1)

Goose can store entire trees (of variable sized things) inside an array.

Apache modules worked like this (still do, presumably). Each request has a stack; allocations bump the stack pointer; when a request is finished, the stack pointer is reset. Incredibly efficient as long as you don't need to keep memory longer than a single request.

Looks like in Goose, each scope acts like an apache "request".

Check the features section (https://aardappel.github.io/goose/#features), which starts off with how memory works.

e.g. I see a general lack of reserve()s on strings and vectors (a few tests do use them a bit, like `graph` and `particles`), and there are several other things which I wouldn't personally call "optimized", so I assume those ones are the 'idiomatic' ones?

Same goes for the Rust code: a lot of the code seems to be using Vec::new() and String::new(), instead of ::with_capacity() which would optimize the memory re-allocation (reducing it as the containers/strings grow).

ps: Ah well, I could have searched before asking https://strlen.com/programming-languages/

super neat history !

Something that I'm interested in: How fast is the compilation speed on large programs compared to Zig, C, Go?

My ideal language is safer than Rust (no deadlocks / livelocks, no stack overflow from recursion), is optimized for cache locality, but compiles faster than Zig.

This seems like it's close to 2/3.

It is obviously has a lot of potential to be very fast.

It even does pretty good on DX. There is no borrow checker to fight. Algorithms that need indices in Rust are strongly typed references in Goose. Generally pleasant easy to read and write code.

The biggest thing against DX may be exactly where performance comes from: you need to think a bit on where to store your data :)

> Goose: my latest programming language. Safer, faster and less memory than Rust/C++ for algorithms where tightly packed, flat data structures matter.

> It can represent more kinds of data structures as flat, pointer-free bytes than any language I know.

https://xitter.cf/wvo/status/2107979660558766351

So one way to answer might be: how often do you reach for unsafe when using Rust? If you don't I guess Rust is safer. If you do… it gets trickier.

As for UB, I guess you could try looking through the spec and/or the reference? Like, the code is mostly generated by Claude after WvO wrote a specification. If it were anyone else I'd be worried, but given WvO's cv I actually suspect that means the spec leaves basically no ambiguity.

However, Goose compiles to C. Does that by definition mean UB sneaks in, or is there a "UB free" C subset? I don't write C, so I don't really know.

But sounds great for 64-bit user space, with enough (48-bit, or more) virtual addressing available. Obviously one can hit some snags if for some reason quite large allocations has to be done, but maybe one has to rethink that too.

I'm starting to fall in love with this approach ;)

https://strlen.com/programming-languages/

In Goose, things grow in-place only, since they have a large amount of address space reserved.

With the but part being the really interesting one.

You'll have to explain what you mean exactly by "dynamically sized moves and struct members".

So now your safety and performance issues are in the LLM and whatever prose you feed it for it to generate slang. Have you gained anything?

(Not meant to detract from the language. It's just that this particular goal seems... strange).

One idea that came up was this: you could define a particuda function name as the "landing pad" for handling particular error kinds. Then you "wrap" calls to the library in a function with this name. Here's a part from a larger worked example:

    fn catch_io<F: fn()>() -> IoError {
      F();
      return IoError{ message: "", ok: true }
    }

    let err = catch_io() { c(); };

Mind you, this was just discussion, no experience with how well this would work in practice.

Rust does a similar thing. When a function returns a value, a location for it will be put in the callers stack frame. That means it automatically stack-allocates values when feasible. The downside in Rust is you need to know the size of the value at compile time whereas Goose can do it for arbitrarily sized values

Why Goose - https://aardappel.github.io/goose/#why-goose

I could follow the link and read the thread and I don't have an X account.

You can also check out the language's website by googling "goose programming language", which should lead you to: https://aardappel.github.io/goose/index.html