ALL LESSONSWEEK 24SATURDAY

SHIP · ASYNC + RUNTIME

Build an ordering predictor

The event loop in time30–60 MINUTESCORE + PRACTICAL
01

GROUND

Problem

What becomes confusing, fragile, or impossible without understanding build an ordering predictor? This lesson answers that through explanation, a worked example, two runnable exercises, and a reference solution. No teacher-supplied worksheet is required.

Event loops let one thread coordinate many delayed operations. Promises standardized continuation and error composition over callback-heavy code.
02

LEARN

Concept explanation

Build an ordering predictor belongs to “The event loop in time”. build an ordering predictor ships as one thin, inspectable slice of an event-loop prediction and trace laboratory.

For build an ordering predictor, trace concrete input, state transition, output, and failure through a state-and-time rule spanning synchronous frames, host tasks, microtasks, rendering, cancellation, or backpressure.

Synchronous frames run to completion. Hosts schedule tasks; promise reactions enter microtask queues; rendering occurs only at host-selected opportunities. Apply that model to supplied normal, boundary, and failure cases; each case below names its input and expected evidence.

Observable

Evidence produced by the build an ordering predictor experiment: output, state, trace, bytes, timing, or diagnostics.

Invariant

Condition that must remain true while inputs or implementation of build an ordering predictor change.

Boundary

Point where build an ordering predictor crosses ownership, representation, time, process, network, or trust.

Example bank

Compare normal, boundary, failure, and cross-layer cases. Predict each observation before revealing the explanation.

Baseline · one variable

SETUPAdd build an ordering predictor to an event-loop prediction and trace laboratory; demo it with: Log script, promise, queueMicrotask, timer, and message task ordering.

OBSERVEFresh clone or blank directory can run documented slice and reproduce: Final log and trace match queue model; measured timer delay grows under blocking/starvation.

WHY IT MATTERSThis isolates the normal contract of build an ordering predictor; preserve its raw evidence as the control for every later comparison.

Boundary · same contract, harder input

SETUPDocument and test shipped slice under: Add nested microtasks and long synchronous block.

OBSERVERecord what remains invariant and the first representation, owner, size, or timing value that changes in Chromium Performance · Network · async debugger.

WHY IT MATTERSA boundary example is useful only when one named dimension changes and everything else stays comparable.

Failure · evidence before repair

SETUPAdd recovery behavior and a regression check for: Starve task queue with bounded microtask chain and measure delay.

OBSERVECapture the first divergence from the baseline, including exact input, diagnostic, state, and recovery result. Expected recovery: Fresh clone or blank directory can run documented slice and reproduce: Final log and trace match queue model; measured timer delay grows under blocking/starvation.

WHY IT MATTERSThe diagnostic is part of the interface. Repair the proven cause, not the most visible symptom.

Cross-layer · follow ownership

SETUPTrace build an ordering predictor one layer below its usual abstraction through a state-and-time rule spanning synchronous frames, host tasks, microtasks, rendering, cancellation, or backpressure.

OBSERVERecord ordering, async stacks, queue delay, cancellation signals, stream state, and cleanup paths.

WHY IT MATTERSThe lower layer is earned when it explains evidence the current layer cannot. Otherwise keep build an ordering predictor at the simpler boundary.

03

SEE

Worked example

Start from supplied lab.mjs. Focus: Add build an ordering predictor to an event-loop prediction and trace laboratory; demo it with: Log script, promise, queueMicrotask, timer, and message task ordering.

  1. Run: node lab.mjs
  2. Save baseline evidence. Record ordering, async stacks, queue delay, cancellation signals, stream state, and cleanup paths.
  3. Boundary case: Document and test shipped slice under: Add nested microtasks and long synchronous block.
  4. Failure case: Add recovery behavior and a regression check for: Starve task queue with bounded microtask chain and measure delay.
RESULT
Fresh clone or blank directory can run documented slice and reproduce: Final log and trace match queue model; measured timer delay grows under blocking/starvation. Starter-level baseline: Order ends as sync:start > sync:end > microtask > task. Each line is a prefix of that final sequence.
04

START HERE

Starter material

PREREQUISITESNode.js 22 or newer. Verify with node --version.

ONE-TIME SETUPmkdir reforging-async && cd reforging-async

Create lab.mjs, paste this exact content, then run the command below.

const events = [];
const record = (value) => { events.push(value); console.log(events.join(" > ")); };

record("sync:start");
queueMicrotask(() => record("microtask:build an ordering predictor"));
setTimeout(() => record("task:build an ordering predictor"), 0);
record("sync:end");
RUNnode lab.mjs

STOP / CLEANUPScripts exit after queued work completes. Press Ctrl+C only if your experiment creates an intentional infinite loop.

05

DO WITH GUIDANCE

Guided exercise

Ship one vertical slice: build an ordering predictor

  1. Normal case: Add build an ordering predictor to an event-loop prediction and trace laboratory; demo it with: Log script, promise, queueMicrotask, timer, and message task ordering.
  2. Write predicted evidence from this named case before running starter.
  3. Advance weekly deliverable with one runnable, documented, inspectable slice.
  4. Run exact normal case. Save commands, inputs, outputs, and diagnostics in notebook.
  5. Explain changed evidence using lesson mental model in no more than five sentences.
Concrete guided solution
  1. Copy the supplied lab.mjs unchanged and run: node lab.mjs
  2. Write this prediction before inspecting output: Fresh clone or blank directory can run documented slice and reproduce: Final log and trace match queue model; measured timer delay grows under blocking/starvation.
  3. Perform only the named normal case: Add build an ordering predictor to an event-loop prediction and trace laboratory; demo it with: Log script, promise, queueMicrotask, timer, and message task ordering.
  4. Save the raw output, then annotate input → transition → evidence. Use Chromium Performance · Network · async debugger to confirm the transition rather than inferring it.
  5. Compare prediction with evidence; if they differ, keep both and write the rule that explains the difference. Reference baseline: Order ends as sync:start > sync:end > microtask > task. Each line is a prefix of that final sequence.
06

DO ALONE

Independent exercise

Make it recoverable: build an ordering predictor

  1. Create second case from blank file: Document and test shipped slice under: Add nested microtasks and long synchronous block.
  2. Then create controlled failure: Add recovery behavior and a regression check for: Starve task queue with bounded microtask chain and measure delay.
  3. Use Chromium Performance · Network · async debugger to prove behavior, then repair controlled failure.
  4. Compare result against supplied acceptance checks and reference approach before marking complete.
Concrete independent solution
  1. Duplicate the starter into a clean comparison case; change only this boundary: Document and test shipped slice under: Add nested microtasks and long synchronous block.
  2. Save its evidence beside the baseline and identify the first changed value. Record ordering, async stacks, queue delay, cancellation signals, stream state, and cleanup paths.
  3. Create the exact controlled failure: Add recovery behavior and a regression check for: Starve task queue with bounded microtask chain and measure delay.
  4. Define one user-visible outcome for build an ordering predictor inside an event-loop prediction and trace laboratory.
  5. Implement thinnest path from input to observable output using baseline: Log script, promise, queueMicrotask, timer, and message task ordering.
  6. Document setup and exact run command; verify from blank directory.
  7. Add boundary fixture and regression fixture: Add nested microtasks and long synchronous block. / Starve task queue with bounded microtask chain and measure delay.
  8. Ship only when another person can reproduce: Final log and trace match queue model; measured timer delay grows under blocking/starvation.
  9. Rerun baseline, boundary, and repaired failure together. Accept only if all reproduce: Fresh clone or blank directory can run documented slice and reproduce: Final log and trace match queue model; measured timer delay grows under blocking/starvation.
07

COMPARE

Expected result

  • Fresh clone or blank directory can run documented slice and reproduce: Final log and trace match queue model; measured timer delay grows under blocking/starvation.
  • Order ends as sync:start > sync:end > microtask > task. Each line is a prefix of that final sequence.
  • Controlled build an ordering predictor failure produces captured evidence; repair restores stated invariant without hiding error.
08

PROVE

Acceptance checks

Lesson is complete only when every check is true. Each check is stored locally and travels with your JSON backup.

0/5 complete · saved on this device

09

UNSTICK

Hints

Reveal hints
  1. Start with supplied normal case exactly as written: Add build an ordering predictor to an event-loop prediction and trace laboratory; demo it with: Log script, promise, queueMicrotask, timer, and message task ordering.
  2. For boundary case, change only named dimension: Document and test shipped slice under: Add nested microtasks and long synchronous block.
  3. If result is confusing, diff raw inputs and evidence before editing implementation.
  4. If tool shows nothing useful, move observation one boundary lower: representation, runtime, OS, or network.
10

VERIFY

Solution

Attempt both exercises before opening reference approach.

Reveal reference solution
  1. Run unmodified starter and preserve baseline evidence: Order ends as sync:start > sync:end > microtask > task. Each line is a prefix of that final sequence.
  2. Define one user-visible outcome for build an ordering predictor inside an event-loop prediction and trace laboratory.
  3. Implement thinnest path from input to observable output using baseline: Log script, promise, queueMicrotask, timer, and message task ordering.
  4. Document setup and exact run command; verify from blank directory.
  5. Add boundary fixture and regression fixture: Add nested microtasks and long synchronous block. / Starve task queue with bounded microtask chain and measure delay.
  6. Ship only when another person can reproduce: Final log and trace match queue model; measured timer delay grows under blocking/starvation.
11

PREDICT · INSPECT · BREAK · DEBUG · MEASURE

Interrogate reality

Prediction: write expected output, state transition, ordering, and failure evidence before running either exercise.

Inspection: Instrument ordering, use async stack traces, Performance recordings, network throttling, and AbortController signals.

Measurement: Measure latency distributions, queue delay, throughput, memory pressure, and backpressure—not only total duration.

INSPECT

Capture raw evidence before explaining.

BREAK

Change one assumption and force controlled failure.

DEBUG

Find cause with Chromium Performance · Network · async debugger before editing fix.

TOOL DRILL · keyboard only · record one retrievable command or shortcut
12

MASTERY + FRONTIER + BOUNDARY

Own the knowledge

TEACH

Explain build an ordering predictor at beginner, intermediate, and senior depth.

REBUILD

Recreate smallest useful example from blank file without notes or AI.

RETRIEVE

Schedule recall for day 1, 7, 30, and 90.

Creative frontier lab

Try first without opening the solutions. The constraints invite invention; the reference gives one concrete direction, never the only valid answer.

Constraint inversion

Re-solve build an ordering predictor by removing the most convenient abstraction. make cancellation and cleanup part of the function contract before adding concurrency.

CONSTRAINTKeep the same inputs, observable result, and failure evidence; change the means, not the contract.

ORIGINAL IDEATurn subtraction into a design tool: the missing abstraction should reveal which responsibility it used to hide.

Reveal frontier solution
  1. Freeze the contract as three fixtures: Add build an ordering predictor to an event-loop prediction and trace laboratory; demo it with: Log script, promise, queueMicrotask, timer, and message task ordering. / Document and test shipped slice under: Add nested microtasks and long synchronous block. / Add recovery behavior and a regression check for: Starve task queue with bounded microtask chain and measure delay.
  2. List every convenience used by the starter; remove the highest-level one while preserving node lab.mjs.
  3. Implement the smallest replacement using make cancellation and cleanup part of the function contract before adding concurrency.
  4. Run all fixtures and compare raw evidence. Keep the simpler version unless the removed abstraction has a demonstrated benefit.
Representation x-ray

Build an explanation artifact for build an ordering predictor: render a timestamped timeline of stack, microtask, task, cancellation, and cleanup events.

CONSTRAINTA peer must be able to locate the first divergence without reading implementation code.

ORIGINAL IDEATreat the explanation itself as a product: make invisible transitions visible, replayable, and diffable.

Reveal frontier solution
  1. Create one row or timestamped event for each transition in: Add build an ordering predictor to an event-loop prediction and trace laboratory; demo it with: Log script, promise, queueMicrotask, timer, and message task ordering.
  2. For every row record input, representation, owner, operation, output, and tool evidence from Chromium Performance · Network · async debugger.
  3. Replay Document and test shipped slice under: Add nested microtasks and long synchronous block.; highlight only changed rows.
  4. Replay Add recovery behavior and a regression check for: Starve task queue with bounded microtask chain and measure delay.; stop at the first divergent row and attach its recovery action.
Adversarial remix

Combine the boundary and failure into a new user-visible scenario for build an ordering predictor. turn a race into a deterministic test by controlling clocks and completion order.

CONSTRAINTDo not merely add more input. Invent a recovery interaction, alternate representation, or self-checking behavior.

ORIGINAL IDEAMake the system teach its own limits: the artifact should expose the invariant and offer a safe next action when it breaks.

Reveal frontier solution
  1. Combine these two pressures without changing them: Document and test shipped slice under: Add nested microtasks and long synchronous block. AND Add recovery behavior and a regression check for: Starve task queue with bounded microtask chain and measure delay.
  2. Name the invariant that must survive and the user-visible evidence when it cannot: Fresh clone or blank directory can run documented slice and reproduce: Final log and trace match queue model; measured timer delay grows under blocking/starvation.
  3. Implement this original direction: turn a race into a deterministic test by controlling clocks and completion order.
  4. Demonstrate baseline, combined failure, recovery, then baseline again; save the sequence as a regression fixture.

Capability frontier

Push build an ordering predictor until another layer becomes justified. Record one robust technique, one contextual trade-off, and one labeled hack or historical curiosity.

CORE · PRACTICAL · CONTEXTUAL · HACK · FRAGILE · HISTORICAL · GOLF

Boundary

Concurrency abstractions cannot remove shared-state hazards, cancellation policy, or capacity limits.

If this vanished tomorrow…

Model delayed work with callbacks, explicit queues, state machines, and host events.

Why next layer is earned

Browser APIs are earned when application logic needs the DOM, storage, workers, files, or other host capabilities.