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1 change: 1 addition & 0 deletions package.json
Original file line number Diff line number Diff line change
Expand Up @@ -8,6 +8,7 @@
],
"scripts": {
"test": "vitest run",
"bench": "vitest run --config packages/core/vitest.perf.config.ts",
"lint": "biome check .",
"lint:fix": "biome check --write .",
"typecheck": "tsc --build tsconfig.build.json",
Expand Down
73 changes: 73 additions & 0 deletions packages/core/__perf__/README.md
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# `@logic-md/core` perf assertions

Pre-merge regression assertions on the three core paths most likely to acquire
silent quadratic behaviour, per the analysis in #46.

## Running

From the repository root:

```bash
npm run bench
```

This invokes vitest with [`vitest.perf.config.ts`](../vitest.perf.config.ts),
which picks up only `**/__perf__/**/*.perf.ts` files and runs them serially in
a single fork (for stable timings). Default `npm test` does not run the bench
suite — `*.perf.ts` is outside the default `**/*.test.ts` glob.

## Coverage

| File | Asserts |
|---|---|
| [`compiler.perf.ts`](compiler.perf.ts) | `compileWorkflow` on a 200-step linear chain |
| [`expression.perf.ts`](expression.perf.ts) | `evaluate` × 10,000 calls on the same template against varying contexts |
| [`dag.perf.ts`](dag.perf.ts) | `resolve` on a 1000-step linear chain |

Linear chains are the worst-case input shape — depth equals node count, which
maximises the impact of any per-pop or per-level work in the DAG resolver and
maximises the per-step traversal cost in the compiler.

## Calibration methodology

Thresholds are calibrated against `main` per the methodology agreed in #46:

1. Run the bench on `main` repeatedly across multiple developer-machine
sessions with varying background load.
2. Take the worst observed elapsed time per metric.
3. Multiply by **1.5** (Math.ceil) for slower-machine headroom.
4. Round up to a clean number for the assertion threshold.

The +50% headroom is wider than the +25% suggested in the original #46 review,
based on observed variance on Windows developer machines (single-shot timings
can vary up to ~3× between quiet and loaded sessions). The bench is opt-in, not
default-CI, so this trade-off favours stable execution at the cost of slightly
weaker regression sensitivity. Once the algorithmic fixes in PRs 2-4 land, the
assertion margin will widen substantially (~100× for the compiler fix), which
provides a much sharper proof-of-fix signal than the initial calibration.

Each `*.perf.ts` file documents its own calibration data in a header comment so
that recalibration after a change is auditable. If a fix legitimately reduces
the workload (e.g. PR 2 in the #46 sequence eliminating the per-step DAG
re-resolution), the threshold should NOT be tightened in the same PR — leave
the headroom widening as visible proof of the fix.

## Adding a new bench

1. Create `<name>.perf.ts` next to existing files.
2. Use `describe` + `test` from `vitest`.
3. Always include a warm-up call before timed measurement (let v8 optimise the
hot path).
4. Run `node` directly with the same workload 5 times against `main`, capture
raw timings, document them in a header comment, and lock the worst × 1.5.

## Why these three?

These are the three concrete candidates surfaced in [#46](../../../../issues/46) — places where the implementation is correct at small scale but algorithmically quadratic+ at scale, currently invisible to all 325 unit tests. The bench suite is the regression net for the full sequence:

- **PR 1 (this scaffold):** establish discipline; assertions pass on main.
- **PR 2:** compiler fix (compileStep accepting pre-computed dagResult).
- **PR 3:** expression cache (AST cache in `evaluate`).
- **PR 4:** DAG sort tightening (eliminate per-pop queue sort and level-filter loop).

After each fix, re-running `npm run bench` shows the assertion margin widening — which IS the proof.
67 changes: 67 additions & 0 deletions packages/core/__perf__/_helpers.ts
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// =============================================================================
// Perf-test helpers — synthetic spec generators for scaling assertions
// =============================================================================
// These are NOT part of the public API. They live under __perf__/ and are only
// used by the bench suite (`npm run bench`).
// =============================================================================

import type { LogicSpec, Step, WorkflowContext } from "../types.js";

/**
* Generate a `LogicSpec` with `n` steps in a strict linear chain
* (step_0 → step_1 → … → step_{n-1}).
*
* Linear chains are the worst case for several scaling concerns:
* - DAG resolve's level-grouping filter (D = N depths)
* - compileWorkflow's per-step DAG re-resolution (N×(V+E) traversal)
* - Token-budget warnings as the prompt segment grows.
*/
export function makeLinearChainSpec(n: number): LogicSpec {
if (n < 1) {
throw new Error(`makeLinearChainSpec requires n >= 1, got ${n}`);
}
const steps: Record<string, Step> = {
step_0: {
description: "first",
instructions: "first step in linear chain",
},
};
for (let i = 1; i < n; i++) {
steps[`step_${i}`] = {
description: `step ${i}`,
instructions: `step ${i} in linear chain`,
needs: [`step_${i - 1}`],
};
}
return {
spec_version: "1.0",
name: "linear-chain-perf",
steps,
};
}

/**
* Just the `steps` map from `makeLinearChainSpec(n)`.
* Useful when calling `resolve(steps)` directly.
*/
export function makeLinearChainSteps(n: number): Record<string, Step> {
const spec = makeLinearChainSpec(n);
return spec.steps as Record<string, Step>;
}
Comment on lines +47 to +50
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🛠️ Refactor suggestion | 🟠 Major | ⚡ Quick win

🧩 Analysis chain

🏁 Script executed:

#!/bin/bash
# Confirm the type of LogicSpec.steps in types.ts
rg -n "steps" --type ts -A 2 -B 2 packages/core/types.ts

Repository: SingularityAI-Dev/logic-md

Length of output: 1661


🏁 Script executed:

#!/bin/bash
# Find makeLinearChainSpec implementation
rg -n "makeLinearChainSpec" --type ts -A 10 packages/core/__perf__/_helpers.ts | head -40

Repository: SingularityAI-Dev/logic-md

Length of output: 969


Replace the as Record<string, Step> cast with a proper type fix.

The cast suppresses a real type mismatch: makeLinearChainSpec always populates steps, but TypeScript sees LogicSpec.steps as optional (Record<string, Step> | undefined). While the function logic guarantees steps are present, the type definition doesn't reflect this. Either make steps non-optional in LogicSpec (or in a dedicated return type from makeLinearChainSpec), or use a non-null assertion (spec.steps!) if the optional definition must remain. The silent cast hides a type safety gap.

🤖 Prompt for AI Agents
Verify each finding against current code. Fix only still-valid issues, skip the
rest with a brief reason, keep changes minimal, and validate.

In `@packages/core/__perf__/_helpers.ts` around lines 47 - 50, The current
makeLinearChainSteps uses an unsafe cast (as Record<string, Step>) to silence
that LogicSpec.steps is optional; replace this by fixing the types instead of
casting: either update the LogicSpec definition (or the specific return type of
makeLinearChainSpec) to make steps non-optional, or if you must keep
LogicSpec.steps optional, use a non-null assertion when accessing spec.steps in
makeLinearChainSteps (spec.steps!) so the compiler sees you intended a present
value; change the type in LogicSpec or the makeLinearChainSpec return type to
reflect that steps is always populated, or use spec.steps! in
makeLinearChainSteps and remove the as Record<string, Step> cast.


/**
* Default `WorkflowContext` for compile-bench measurements.
*/
export function makeWorkflowContext(): WorkflowContext {
return {
currentStep: "step_0",
previousOutputs: {},
input: {},
attemptNumber: 1,
branchReason: null,
previousFailureReason: null,
totalSteps: 0,
completedSteps: [],
dagLevels: [],
};
}
60 changes: 60 additions & 0 deletions packages/core/__perf__/compiler.perf.ts
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// =============================================================================
// Perf assertion: compileWorkflow scaling
// =============================================================================
// Pins the cost of compiling a 200-step linear-chain workflow against current
// `main`. Linear chains are the worst-case shape for `compileWorkflow` because
// every `compileStep` call re-resolves the full DAG (Candidate 1 in #46).
//
// Chain size of 200 (rather than 1000) keeps the bench under 2 seconds per
// run; once Candidate 1's fix lands the same workload should drop ~100×, and
// the assertion margin will widen dramatically — exactly the proof-of-fix
// signal Rain asked for in his sequencing comment.
//
// Threshold calibration methodology (per #46 review, with +50% adjustment
// noted in the calibration block below):
// 1. Run on `main` repeatedly across developer-machine sessions with
// varying background load.
// 2. Take the worst observed elapsed time.
// 3. Multiply by 1.5 (Math.ceil) for slower-machine headroom.
// 4. Lock that value in as the assertion threshold.
//
// Calibration data captured 2026-05-07 on Node v22.18.0 across multiple
// developer-machine sessions with varying background load:
// quiet runs: 746ms, 778ms, 1318ms, 1326ms, 1398ms
// loaded runs: 2102ms, 2607ms, 2899ms
// worst observed = 2899ms → ceil(2899 × 1.5) = 4349ms → 4500ms (rounded)
//
// The +50% headroom (rather than the +25% suggested in the original #46
// review) reflects observed variance on Windows developer machines under
// realistic background load. The bench is opt-in (`npm run bench`, NOT
// default `npm test`), so this trade-off favours stable execution at the
// cost of slightly weaker regression sensitivity. Once Candidate 1's fix
// lands, the assertion margin will widen from ~1.5× to ~100×, providing
// a much sharper proof-of-fix signal.
// =============================================================================

import { describe, expect, test } from "vitest";
import { compileWorkflow } from "../index.js";
import { makeLinearChainSpec, makeWorkflowContext } from "./_helpers.js";

/**
* Calibrated threshold for compileWorkflow on a 200-step linear chain.
* See header comment for methodology and raw data.
*/
const COMPILE_200_STEP_THRESHOLD_MS = 4500;

describe("perf: compileWorkflow scaling", () => {
test(`compileWorkflow on 200-step linear chain completes <${COMPILE_200_STEP_THRESHOLD_MS}ms`, () => {
const spec = makeLinearChainSpec(200);
const ctx = makeWorkflowContext();

// Warm-up: let v8 optimise the hot path before measurement.
compileWorkflow(spec, ctx);

const t0 = performance.now();
compileWorkflow(spec, ctx);
const elapsed = performance.now() - t0;

expect(elapsed).toBeLessThan(COMPILE_200_STEP_THRESHOLD_MS);
});
});
43 changes: 43 additions & 0 deletions packages/core/__perf__/dag.perf.ts
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// =============================================================================
// Perf assertion: resolve() scaling on a 1000-step linear chain
// =============================================================================
// Pins the cost of topological sort + level grouping on the worst-case DAG
// shape (linear chain, where depth = N). Catches regressions in the per-pop
// queue sort, neighbour sort, and level-filter loop in `dag.ts`.
// Threshold calibrated against current `main` (5 runs, take worst, +25%).
// =============================================================================

import { describe, expect, test } from "vitest";
import { resolve } from "../index.js";
import { makeLinearChainSteps } from "./_helpers.js";

/**
* Calibrated threshold for resolve() on a 1000-step linear chain.
*
* Calibration methodology: multiple runs on `main` across developer-machine
* sessions with varying background load; take worst observed, multiply by 1.5
* for headroom.
*
* Calibration data captured 2026-05-07 on Node v22.18.0:
* quiet runs: 117ms, 128ms, 143ms, 152ms, 215ms
* loaded runs: 419ms, 484ms
* worst observed = 484ms → ceil(484 × 1.5) = 727ms → 800ms (rounded)
*/
const RESOLVE_1000_STEP_THRESHOLD_MS = 800;

describe("perf: dag.resolve scaling", () => {
test(`resolve(1000-step linear chain) completes <${RESOLVE_1000_STEP_THRESHOLD_MS}ms`, () => {
const steps = makeLinearChainSteps(1000);

// Warm-up.
const warm = resolve(steps);
expect(warm.ok).toBe(true);

const t0 = performance.now();
const r = resolve(steps);
const elapsed = performance.now() - t0;

expect(r.ok).toBe(true);
expect(elapsed).toBeLessThan(RESOLVE_1000_STEP_THRESHOLD_MS);
});
});
50 changes: 50 additions & 0 deletions packages/core/__perf__/expression.perf.ts
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// =============================================================================
// Perf assertion: evaluate() throughput on repeated expressions
// =============================================================================
// Pins the cost of evaluating the same `{{ ... }}` expression 10,000 times
// against varying contexts. Catches regressions in tokenize/parse hot path
// (e.g. accidental disabling of an AST cache once one is added in PR 3).
// Threshold calibrated against current `main` (5 runs, take worst, +25%).
// =============================================================================

import { describe, expect, test } from "vitest";
import { evaluate } from "../index.js";

/**
* Calibrated threshold for 10,000 evaluate() calls on the same template.
*
* Calibration methodology: multiple runs on `main` across developer-machine
* sessions with varying background load; take worst observed, multiply by 1.5
* for headroom. The +50% (rather than the original +25%) reflects observed
* variance on Windows developer machines.
*
* Calibration data captured 2026-05-07 on Node v22.18.0:
* quiet runs: 135ms, 197ms, 234ms, 268ms, 382ms
* loaded runs: 617ms
* worst observed = 617ms → ceil(617 × 1.5) = 926ms → 1000ms (rounded)
*/
const EVAL_10K_THRESHOLD_MS = 1000;

describe("perf: evaluate() throughput", () => {
test(`evaluate same expression 10,000 times <${EVAL_10K_THRESHOLD_MS}ms`, () => {
const tmpl = "{{ output.findings.length > 3 && output.confidence >= 0.6 }}";

// Warm-up: prime the parser path.
for (let i = 0; i < 100; i++) {
evaluate(tmpl, { output: { findings: [], confidence: 0 } });
}

const t0 = performance.now();
for (let i = 0; i < 10_000; i++) {
evaluate(tmpl, {
output: {
findings: new Array(i % 5),
confidence: (i % 100) / 100,
},
});
}
const elapsed = performance.now() - t0;

expect(elapsed).toBeLessThan(EVAL_10K_THRESHOLD_MS);
});
});
25 changes: 25 additions & 0 deletions packages/core/vitest.perf.config.ts
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// =============================================================================
// Vitest config for the bench suite (`npm run bench`)
// =============================================================================
// Picks up only `__perf__/**/*.perf.ts`, runs them serially in a single fork
// for stable timings, and bypasses the default `**/*.test.ts` glob so the
// bench suite never runs as part of `npm test`.
// =============================================================================

import { defineConfig } from "vitest/config";

export default defineConfig({
test: {
include: ["**/__perf__/**/*.perf.ts"],
// Serialise execution to minimise cross-test interference on timings.
// `pool: "forks"` alone does NOT serialise — in Vitest 4 the option
// that guarantees one-file-at-a-time execution is `fileParallelism:
// false` at the top of the `test` block. (Pre-Vitest-4 this was
// `poolOptions.forks.singleFork`; both `poolOptions` and the per-pool
// `singleFork` were removed in the v4 pool rework.)
pool: "forks",
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fileParallelism: false,
// 60s ceiling — well above any realistic threshold; only fires on hangs.
testTimeout: 60_000,
},
});
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