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What I would spend box time on, if it were my budget

2026-08-30. Steve asked: for an emitter change specifically, with finite time, what would I actually do? The honest answer starts with an economic fact we have been ignoring, and most of the strategy falls out of it.

One fact does most of the work

You never need to RUN a program whose emitted zig is byte-identical across the two arms. Same source text, same zig version, same binary, same output. Its verdict cannot have moved. Running it is not a weak test — it is a guaranteed tautology, paid for at full price.

We already believe this. corpus_run.py --changed carries a banked verdict when "the emitted zig is byte-identical to the banked hash AND the toolchain that produced the banked verdict is the toolchain that would rerun it." The mechanism exists. It is pointed at a bank — the same tree yesterday — instead of at the other arm, which is the comparison we actually care about.

Look at what that cost on the bitcast change. The sweep ran 326 programs per arm. Three emitted files differed. 323 of those 326 runs were provably unnecessary before they started, and the information needed to skip them — the transpile stage's zig_sha per program — had already been computed, in the cheap stage, minutes earlier.

The two stages have wildly different prices. Transpiling all 1,704 programs is native-only: no QEMU, no zig compilation, minutes. Running them is zig build plus execute, per program, and it is the whole cost. So:

Transpile everything. Run only what differs.

Cost then scales with the blast radius of the change, not with the size of the corpus. A narrow emitter fix pays for three programs. A prelude change that touches every file pays for everything — correctly, because that change really is global. The budget self-adjusts, and nobody has to guess.

Select by emitted output, not by source

Derived selection from cites is real and I built it today: the arc tangent affects 5 of 1,704 programs, computed in a second, where a full sweep took 28 minutes to say nothing. But for the change Steve is asking about it gives nothing. A ZigEmitter edit writes every program's output; no cite relationship narrows it. affected.py says SCOPE: all and it is right.

The move that does work for emitter changes is to select on the artifact rather than the source. We have 1,704 emitted .zig files on disk from the last sweep. If a change touches the emission of IrMulRealTrapping, the programs that can possibly reveal it are the ones whose previous zig contains that construct. That is a grep over cached text — free — and it converts "I have no idea which programs matter" into a named list, before the box is touched.

Source-based selection asks what does this program cite. Output-based selection asks what does this program actually emit. For a plug change only the second question has an answer, and we have never asked it.

The middle tier nobody uses: compile without running

Right now there are two stages, transpile and run, and "run" means build and execute. But the most common emitter defect is not a wrong answer — it is zig refusing the file. Shadowed declarations, undeclared identifiers, a type that contains itself. Every one of those is caught by zig build-exe alone, at a fraction of execution cost, with no .expected needed and no oracle involved.

Three tiers, three prices, three yields:

stage cost catches
transpile minutes, all 1,704 emission changed at all; @compileError markers
compile seconds each, only what differs invalid zig — the commonest emitter defect
execute seconds each, only what compiles wrong answers

Splitting build from execute gives a rung we do not currently have, and it is the rung where most emitter bugs die.

What a targeted test can and cannot do

Steve's instinct is right: for an emitter change the first and most direct thing is a well-written test in the depot's corpus, settled on bare metal. That answers the question that matters most — does this construct emit correctly — exactly, cheaply, and permanently.

But it answers it in isolation, and that is the limit worth naming. The author writes the construct the way they are imagining it. The corpus exercises it in composition: nested inside a closure, inside a match arm, under a self tail call, as an argument to something that was itself inlined away.

The bitcast run showed this concretely. The targeted test used real-to-bits on literals. The corpus used it inside vec-array, in an expression already full of @compileError for three other missing emitters, and inside sparkplug-encode beside real-approx-to-bits which still refuses. Neither is a case anybody would think to write by hand, and both are exactly where an emitter's assumptions get tested.

So: targeted test proves the construct; corpus proves the composition. Neither substitutes for the other, and knowing which one you are buying is how you decide whether to buy it.

Never write a probe you throw away

A one-off probe and a depot test cost the same to write. The probe dies with the sandbox; the test becomes Damian's regression forever and enters our corpus permanently, so every future change gets it free.

We have been doing this right by accident on the outbound work — real-bitcast-f64 and real-int-conversions are depot tests, not probes — and wrong everywhere else. The four zz-* probes that diagnosed the inlining rule no longer exist, which is why that finding could not be re-checked today and had to be re-derived from the compiler source.

The rule I would enforce: if it is worth running twice, it goes in codex/test/. No exceptions for "this is just to check something."

Full corpus is drift detection, not a gate

This is the part I would change most.

A full corpus run answers has anything in this tree drifted — a question about the tree, not about your change. Running it per-change pays for the same answer repeatedly. If it ran nightly and was green at 3 a.m., a full run at 10 a.m. against a small emitter change tells you almost nothing you did not already know.

Move it. Full sweep once per Update, or nightly when the box is idle, as a background activity whose job is catching accumulated drift. Per-change spending goes to the targeted test, the transpile byte-diff, and the differing set. The expensive instrument gets pointed at the question only it can answer, instead of being used as an anxiety reducer on every commit.

Measure the yield, and retire what stops catching

BOX.md says an item that stops catching anything should be deleted rather than kept for completeness. That principle applies to test tiers and we have never applied it, because we do not record what each tier caught.

We should. One line per run in the result artifact: what did the full sweep find that the targeted test did not? If the answer is "nothing, eleven runs in a row," that is an argument to move it to weekly, made of evidence instead of feel. If it catches a real regression every third run, that is an argument to keep paying. Right now we cannot answer the question at all, which means the budget is set by whoever is most nervous.

The policy I would actually run

Per emitter change, always, ~10 minutes:

  1. A depot test for the construct, .expected settled on bare metal with an untouched control. This is the deliverable, not the scaffolding.
  2. Full transpile, both arms. Byte-diff the emitted zig.
  3. Read the diff set. If it is empty and you expected it not to be, stop — that is the presence check failing, and it is the most valuable signal you will get all day.

Then, proportional to what moved:

  1. Compile the differing programs. Then run them, both arms.
  2. Bare-metal any program whose verdict moved. Never wholesale — two guests each.

Periodically, not per change:

  1. One full corpus run per Update, or nightly on an idle box. Its job is drift.
  2. The tier set and the fixed point stay where they are: they answer a different question and they are cheap relative to what they cover.

Always:

  1. Every result is a committed artifact, and the yield line goes in it.

The shape of this is that cheap and total beats expensive and sampled. Transpiling everything costs minutes and tells you exactly where to spend the expensive stage. We have been doing the reverse — running an expensive stage across a corpus we had already narrowed by accident, and reading the result through tail.

— Claude