Ironic Space Lisp Part 3


Have you ever been working on a project and felt stupid and scared? Not in an anxious way, and not in an imposter syndrome way, but in a visceral way, like “I don’t really know what I’m doing, and I’m not sure I can do this.” Some languages are so complex and different that, although I know they’re full feature and Turing complete languages, I don’t know that I can even write whatever program I’m trying to make. Or at least that I can’t write it idiomatically.

On the one hand, this really doesn’t feel good. On the other hand, it’s a very strong sign that I’m actually learning something. Right now, I’m only scared of 2 languages: Rust and Haskell. On this side of the learning curve, I can’t say with total confidence exactly what I’m learning from them, but I’m very much learning something.

Rust’s really mind bending parts are mostly the type system differentiating between stack and heap data, the lifetime system, and the borrow checker. Luckily, writing a lisp interpreter is a good way of really exploring those systems. Haskell enforces radical functional purity at a level I haven’t really encountered in any other language, despite my experience with other functional languages.

Anyway, my practice of having 1000+ tabs open paid of once again when I noticed Bob Nystrom’s book, “Crafting Interpreters” in my browser. “Hey, that’s what I’m doing,” I thought, stupidly. One the book’s main points was that tree-walk interpreters are slow. In retrospect (particularly with the book’s subsequent paragraphs), it’s fairly obvious. Modern CPUs are optimized for fast loops over linear data. One of their main “bottlenecks” is pointers: dereferencing pointers into uncached memory is really slow (almost guaranteed to generate a cache miss).

As it turns out, tree walk interpreters dereference pointers constantly. Because AST trees are inherently recursive, and structs can’t be of indeterminant size, all child nodes in ASTs must be pointers, and usually pointers to heap data, which in turn point to more heap data.

pub enum Lisp {

A lot of languages make these pointers implicit, like Java, where there are no value/stack objects, only heap allocated objects, and everything is a reference. Writing a recursive interpreter over a simple tree structure like this is really easy, and it’s the go to technique for “writing your first interpreter” tutorials and articles, like “Write Yourself a Scheme in 48 Hours” (which includes the phrase “you’ll have to forget most of what you already know about programming”, which is how you know it’s a good tutorial). Nystrom’s book complicates that slightly by employing the visitor pattern to implement evaluation, but I found his justification for it entirely convincing, and it really didn’t change the performance implications of tree-walk. Additionally, my interpreter almost never deals with data values directly, they’re almost always wrapped in an Rc,

// from src/frames/
pub struct IfFrame {
    lisp: Rc<Lisp>,
    predicate: Option<Rc<Lisp>>,
    answer: Option<Rc<Lisp>>,
    state: FState,

primarily to prevent ownership issues. The AST/data are all treated as immutable, so reference counting the entire thing and directly sharing data and code is reasonable semantically speaking (especially for a Lisp), but too much indirection is inefficient.

It’s worth noting that although the Ironic Space Lisp interpreter isn’t a normal tree walk interpreter. The ISL interpreter, as it’s implemented on the master branch right now, reifies the stack frames tracking the recursive descent into the AST to permit preemptive pausing. This really doesn’t help the locality issue, as the AST still lives in arbitrary heap memory. Additionally, although I thought that reifing the frame stack would assist in implementing Tail Call Optimization (an important part of the language), I subsequently realized it wouldn’t: it would be mildly easier than in a normal recurse tree-walk implementation, but still wouldn’t be easy.

By contrast, in a bytecode VM, implementing TCO is easy, and can be done both at code generation and at runtime in the VM. Nystrom also convincingly claims that bytecode VMs are much faster than treewalk interpreters, and not much harder to write. I find myself convinced by these arguments (and the ever increasing complexity of the frame code, see, and I’ve restarted work on the stack VM in the ISL repo. It’s still in the old_stack branch.

It isn’t substantially smaller than the stepped interpreter, but it’s a fair amount simpler, partially because it’s just a VM. It does have nested environments and bindings before the stepped interpreter, but doesn’t have complex data types like lists 🤔. It currently treats bytecode addresses as normal data, which is something which might change, but exposing those sorts of externals to the user is something that might have interesting gameplay implications. It might also be relevant if I want to implement some other type of language on the bytecode VM, but that seems less likely, particularly because I’ve already implemented environment bindings in the VM.

In the end, Nystrom baited me: he’s completed the section on the tree-walk interpreter, but his chapter on the bytecode VM ends at compiling expressions, leaving such topics as “local variables”, “calls and functions”, “closures”, and “garbage collection” incomplete. I think I’ll be alright: I can see how to implement all of these, although I’m particularly interested in his approach to closures.

I’m hoping to make closures serializable, or at least transferrable between different VMs with different environments: possible in Java, difficult in PHP, involves eval in Ruby, possible in Erlang, etc (how crazy is it that it’s possible in Java but not Ruby?). In particular, capturing bound values and passing them over the wire with the function seems doable, but weird. I’m not sure I need to serialize closures all the way to strings and send them over the network, but copying/moving functions made from and parameterized by higher order functions from one VM to another seems like a really flexible and powerful tool for the languages ultimate purpose.

It’s worth nothing that this presentation was very interesting, although it covers a lot of topics that weren’t directly relevant to this project.

Addendum: Tests

Why haven’t you written any tests?

This is a pretty bad look for me: no tests of any of the implementations. To explain, allow me to draw your attention to the phrase “any of the implementation”. I’ve written two and a half implementations, and none of them have reached any sort of completeness. Between uncertainty over language, API, and implementation, the code is changing so fast that tests would be mostly wasted effort. I’ve had very little solid idea of what this project is going to look like in the end, and without a solid vision, any tests that get written have a very good chance of being abandoned as that code base becomes obsolete. I’ve abandoned the bytecode VM, then picked it up again, but I ended up rewriting it substantially, so any existing tests would either restrict me unreasonably or be deleted. Certain design decisions in the stepped interpreter made it harder to implement the naive tree-walk version, so tests written for that partial interpreter would also have been thrown out. The stepped interpreter is very complicated with lots of moving parts, but all the parts are very tightly bound, which makes testing them independently very difficult, and testing them together very difficult too. The VM is easier to write tests for, luckily.

rust code language