Small follow-up pushed on top of this draft:

• adds coverage for the explicit julialowering backend stub path
• improves the stub error message so it distinguishes between:
  • JuliaLowering not installed in the environment, and
  • JuliaLowering installed but integration not implemented on this branch yet

Validation rerun: julia --project=. -e 'using Pkg; Pkg.test(; test_args=["main"])'

Another incremental follow-up pushed:

• factors JuliaLowering environment detection into a small capability probe
• adds direct tests for the probe and derived error message
• keeps the actual backend behavior unchanged (still legacy-by-default; JuliaLowering path still explicit stub)

Validation rerun: julia --project=. -e 'using Pkg; Pkg.test(; test_args=["main"])'

Dependency viability note from the JuliaLowering spike work:

I tested whether upstream JuliaLowering is currently usable enough to move from seam/probe work into a real backend experiment.

Observed local runtime matrix:

• Julia 1.11.9: package resolves, but precompile fails with UndefVarError: IncludeInto not defined in Base
• Julia 1.12.5 (julia +release) in a clean temp project: package resolves, but using JuliaLowering fails with unknown Kind name "StrMacroName"

So the current blocker appears to be deeper than just the ResumableFunctions.jl environment: upstream JuliaLowering main does not seem consumable out-of-the-box on the locally available stable runtimes I tested.

That means the next useful step is probably one of:

1. identify a known-good Julia / JuliaLowering / JuliaSyntax revision combination for this spike, or
2. treat runtime compatibility itself as the current blocker for deeper issue Use JuliaLowering.jl for a cleaner way to transform resumable functions to finite state machines [$600] #99 work.

I'm keeping the draft PR focused on seam/probe/prep work until that dependency path is clearer.

Follow-up on the JuliaLowering viability search: I tested two plausible pinned revisions from JuliaLowering history to see whether there was an obvious working commit for this spike.

Tested revisions:

• 134d4ad (Adapt to JuliaSyntax MacroName change (#71)) on Julia 1.12.5
  • still fails on import/precompile with unknown Kind name "StrMacroName"
• f1d6246 (pre-Base.IncludeInto path) on Julia 1.11.9
  • avoids the IncludeInto failure, but still fails on import/precompile with unknown Kind name ".&&"

So the current evidence is:

• current main is not usable out-of-the-box on my tested stable runtimes
• one plausible pre-IncludeInto pin also still fails
• one plausible post-JuliaSyntax-adaptation pin also still fails

That makes this look less like a single bad HEAD commit and more like a broader runtime / JuliaSyntax / JuliaLowering compatibility matrix problem. I'm keeping this draft focused on seam/probe/prep work until I can identify a genuinely importable revision/runtime combination.

Good news on the JuliaLowering viability search: I found a combination that does import cleanly.

Locally confirmed working combo:

• Julia 1.12.5 (julia +release)
• JuliaLowering main
• JuliaSyntax pinned to 99e975a7

This matches the explicit source hint already present in JuliaLowering's Project.toml:

• [sources] JuliaSyntax = { rev = "99e975a7", ... }

Observed sequence in a fresh temp project:

1. Pkg.add(url="https://github.com/JuliaLang/JuliaLowering.jl")
2. Pkg.add(url="https://github.com/JuliaLang/JuliaSyntax.jl", rev="99e975a7")
3. using JuliaLowering
4. import succeeded (IMPORT_OK_RELEASE_PINNED_SYNTAX)

So the updated conclusion is:

• this is not an absolute JuliaLowering dead end
• it is a compatibility-matrix problem
• the first locally verified usable matrix is Julia 1.12.5 + JuliaLowering main + JuliaSyntax 99e975a7

That means the next logical step for this spike is a controlled experiment using exactly that combo, rather than more blind revision hunting.

Narrowed the new comprehension/closure blocker further.

The failing path goes through JuliaLowering.eval_closure_type(...) in src/runtime.jl, which currently does:

• Core.declare_const(mod, closure_type_name, type)

I checked the locally available stable runtimes directly:

• Julia 1.11.9: isdefined(Core, :declare_const) == false
• Julia 1.12.5: isdefined(Core, :declare_const) == false

And the JuliaLowering PR that introduced this runtime call (#87, New Core.declare_global and Core.declare_const lowering) explicitly includes a commit: Don't test on 1.12 in CI.

So the current picture is:

• baseline import can work in the controlled 1.12.5 + JuliaSyntax 99e975a7 environment
• but closure/comprehension evaluation now appears gated on a newer Julia runtime API floor than the stable runtimes available here

That makes the next blocker much more concrete: for comprehension-shaped experiments, this looks like a runtime-floor issue rather than a ResumableFunctions.jl integration mistake.

Another useful narrowing result from the Julia 1.12 spike repo:

I tested the problematic comprehension-shaped pattern through JuliaLowering's non-eval APIs instead of include_string(...):

• parsestmt(...)
• lower(...)
• to_lowered_expr(...)

Pattern tested:

let i = 1
    [a[i] for a in [(1,2), (3,4)]]
end

This path succeeds in the controlled environment (Julia 1.12.5 + JuliaLowering main + JuliaSyntax 99e975a7). The lowered form comes back as an Expr and clearly shows the closure-conversion/comprehension machinery, including boxed capture of i, JuliaLowering.eval_closure_type(...), and the generated Base.Generator(...) / Base.collect(...) path.

So the updated split is:

• lowering/analysis of the comprehension-shaped scope pattern works
• runtime evaluation of that lowered form is what currently fails on the newer Core.declare_const path

That means there is still productive issue #99 work available on the lowering/analysis side even before the runtime-floor problem is solved.

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Another meaningful narrowing result from the spike repo: the non-eval lowering path also works on a much more ResumableFunctions-shaped example, not just the tiny comprehension toy case.

I lowered a function with:

• nested loops
• let i=i, j
• a comprehension capturing the shadowed i
• accumulation into out

using:

• parsestmt(...)
• lower(...)
• to_lowered_expr(...)

This succeeds in the controlled environment and the lowered form clearly shows the expected structure:

• boxed capture of the shadowed i
• generated closure constructor path
• Base.Generator(...)
• Base.collect(...)
• push into out

So the current evidence is now fairly strong that JuliaLowering can lower the actual shape of the scope/comprehension pattern relevant to this spike. The remaining blocker is runtime evaluation / closure materialization on stable Julia, not lowering of the pattern itself.

I now have both sides of the comparison for the same resumable-shaped pattern.

Current ResumableFunctions.jl manual scoping pass (ScopeTracker / scoping(...)) rewrites the example by direct symbol renaming in AST form, eg:

• out -> out_0
• u -> u_1
• loop i -> i_2
• shadowed let i=i becomes i_3 = i_2
• comprehension variable becomes a_5
• resulting inner form looks like: val_6 = [a_5[i_3] for a_5 = u_1]

By contrast, the JuliaLowering non-eval lowering path for the same pattern gives the explicit closure/generator structure:

• boxed capture of the shadowed i
• generated closure constructor path
• Base.Generator(...)
• Base.collect(...)
• push into out

So the integration question is now a lot more concrete: the next slice probably shouldn't try to replace runtime behavior end-to-end yet. It should instead focus on whether JuliaLowering can provide the scope/capture analysis needed by ResumableFunctions.jl while leaving runtime evaluation out of scope for now.

Short comparison snapshot from the latest probes:

Current manual ScopeTracker/scoping(...) path expresses the resumable-shaped shadowing pattern as renamed source identifiers like:

• out_0
• u_1
• i_2
• i_3
• a_5
• val_6

JuliaLowering expresses the same distinctions differently: not by renaming source identifiers, but by keeping the original names while separating them into distinct slot/binding entities. For the focused probe, the useful slot groups are:

• closure side: #self#, a, i
• function side: out, u, i, i, j, val

That feels like the clearest bridge layer yet between the two approaches:

• manual path = source renaming to encode shadowing
• JuliaLowering path = slot/binding identity to encode shadowing

So the next practical slice is likely to derive a compact binding/shadowing map from JuliaLowering metadata and compare that map against the current rename map, rather than attempting an all-at-once runtime replacement.

I turned the last comparison snapshot into a first role map between the current manual rename strategy and JuliaLowering metadata for the same resumable-shaped probe.

Role bridge so far:

• out_0 -> function slot out
• u_1 -> function slot u
• i_2 -> one function slot i
• i_3 -> second function slot i
• a_5 -> closure slot a
• val_6 -> function slot val
• implicit j local -> function slot j

That feels like the first actually actionable bridge layer:

• manual path distinguishes scope roles by renaming identifiers
• JuliaLowering distinguishes the same roles by separate slot/binding identity while keeping names stable

So the next practical slice is likely to derive stable role labels from JuliaLowering metadata and use those labels to replace or validate pieces of ScopeTracker incrementally, rather than trying to swap runtime behavior all at once.

I packaged the latest bridge work into a small local validator and ran it on the resumable-shaped probe.

Validation result: MATCHES_EXPECTED_ROLE_FAMILY

It checks that the current manual rename family:

• out_0, u_1, i_2, i_3, a_5, val_6

lines up with the JuliaLowering-derived slot family:

• function slots: out, u, i, i, j, val
• closure slot: a

So at the role level, the current ScopeTracker output and the JuliaLowering metadata are now matching in the way we would hope:

• manual path distinguishes roles via renamed identifiers
• JuliaLowering distinguishes the same roles via separate slot/binding identity

This doesn't solve runtime eval, but it does make the next integration slice more concrete: use JuliaLowering-derived role labels as a validation/bridge layer for parts of ScopeTracker rather than replacing everything at once.

I added a tiny bridge consumer on the ResumableFunctions.jl side that reads the machine-readable JuliaLowering role-family JSON, reruns the current manual scoping probe, and compares the two role families directly.

Result on the resumable-shaped probe:

• compare_status=MATCH

So we now have a repeatable cross-artifact check showing that the current manual rename family matches the JuliaLowering-derived role family on the same example.

That still isn't end-to-end integration, but it feels like the first genuinely test-harness-like bridge between the two approaches rather than just side-by-side notes.