Atomics.waitAsync does not always return a promise in its value field. It always returns a record, and that record tells you whether the value is an immediate string or a promise for a later result. This guide traces shared memory, expected values, zero timeouts, notification and bounded tests without pretending host timing is exact.
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Read the returned record before awaiting anything. A mismatch or zero timeout is immediate; an enrolled waiter exposes a promise for a later outcome.
ROUTE 1 · CHAPTERS 1–3
Build the first trace
Identify the participating objects and the first observable steps.
ROUTE 2 · CHAPTERS 4–6
Work the decisive branch
Follow the branch that changes identity, order or timing.
ROUTE 4 · CHAPTERS 10–12
Handle limits and failures
Locate conversion, protocol and lifecycle boundaries.
Chapter contents
Build the first trace · Chapters 1–3
1. Begin with the returned record
Work the decisive branch · Chapters 4–6
4. Treat zero timeout as a fast immediate branch
Change one premise · Chapters 7–9
7. Separate changing the value from notifying
Handle limits and failures · Chapters 10–12
10. Validate index and numeric conversions first
Verify and explain · Chapters 13–15
13. Normalize outcomes without losing diagnostics
Atomics.waitAsync returns an object with async and value properties. Code must inspect async before deciding whether value is a string result or a promise. Start by naming the object, operation and observation separately. That small discipline prevents a convenient surface description from replacing the mechanism that actually decides the result.
Worked case. On a shared Int32Array containing 0, call waitAsync expecting 1. The record is {async:false,value:"not-equal"} and no await is required. Write the observations in order and keep values, calls and returned containers distinct. The point of the example is not merely to obtain an answer; it is to make every decisive step inspectable.
A useful trace records what is read first, which callable is invoked, what state is consulted, and whether the visible outcome is available now or later. If one of those facts is missing, two programs that look similar can be reported as though they had the same behaviour.
Changed-context check. Expect 0 with a positive timeout. The record becomes async true and value is a promise. Re-run the trace from the changed premise instead of editing the old conclusion. This is how the explanation transfers to unfamiliar code without turning one remembered example into a universal rule.
Limit and evidence check. Do not write await Atomics.waitAsync(...); that awaits the record object itself, not an enrolled waiter’s value promise. Prefer a finite fixture, an event ledger and an exact assertion. The check should distinguish the competing explanations rather than merely confirming the final printed value.
For a practical review, ask three questions: what did the caller request, what did the language operation actually do, and what may the host or surrounding code still change? Answering all three keeps the report useful to a learner and honest about its boundary.
Now test the tempting shortcut against this chapter’s case. A shortcut that predicts only the final value misses the decisive observation in: Atomics.waitAsync returns an object with async and value properties. Code must inspect async before deciding whether value is a string result or a promise. State what that shortcut would get wrong, then point to the one ledger entry or identity assertion that corrects it. This converts a rule into a reusable diagnostic rather than another phrase to memorise.
Waiting applies to an Int32Array or BigInt64Array backed by SharedArrayBuffer and a valid index. Ordinary ArrayBuffer storage cannot join the waiter list. Start by naming the object, operation and observation separately. That small discipline prevents a convenient surface description from replacing the mechanism that actually decides the result.
Worked case. Create SharedArrayBuffer(4), view it as Int32Array, and use index 0. Record the initial value with Atomics.load. Write the observations in order and keep values, calls and returned containers distinct. The point of the example is not merely to obtain an answer; it is to make every decisive step inspectable.
A useful trace records what is read first, which callable is invoked, what state is consulted, and whether the visible outcome is available now or later. If one of those facts is missing, two programs that look similar can be reported as though they had the same behaviour.
Changed-context check. Replace the backing store with ArrayBuffer(4). The same-looking view now fails the waitable-storage requirement. Re-run the trace from the changed premise instead of editing the old conclusion. This is how the explanation transfers to unfamiliar code without turning one remembered example into a universal rule.
Limit and evidence check. A shared buffer enables communication; it does not by itself make a larger protocol correct or race-free. Prefer a finite fixture, an event ledger and an exact assertion. The check should distinguish the competing explanations rather than merely confirming the final printed value.
For a practical review, ask three questions: what did the caller request, what did the language operation actually do, and what may the host or surrounding code still change? Answering all three keeps the report useful to a learner and honest about its boundary.
Now test the tempting shortcut against this chapter’s case. A shortcut that predicts only the final value misses the decisive observation in: Waiting applies to an Int32Array or BigInt64Array backed by SharedArrayBuffer and a valid index. Ordinary ArrayBuffer storage cannot join the waiter list. State what that shortcut would get wrong, then point to the one ledger entry or identity assertion that corrects it. This converts a rule into a reusable diagnostic rather than another phrase to memorise.
The operation compares the current element with the expected value while coordinating the waiter list. A mismatch returns immediately as not-equal. Start by naming the object, operation and observation separately. That small discipline prevents a convenient surface description from replacing the mechanism that actually decides the result.
Worked case. Store 7 and wait expecting 6. The record is async false with not-equal. Write the observations in order and keep values, calls and returned containers distinct. The point of the example is not merely to obtain an answer; it is to make every decisive step inspectable.
A useful trace records what is read first, which callable is invoked, what state is consulted, and whether the visible outcome is available now or later. If one of those facts is missing, two programs that look similar can be reported as though they had the same behaviour.
Changed-context check. Change only the expected value to 7 and supply a finite timeout. The call may enroll an asynchronous waiter. Re-run the trace from the changed premise instead of editing the old conclusion. This is how the explanation transfers to unfamiliar code without turning one remembered example into a universal rule.
Limit and evidence check. A not-equal result is a useful retry signal, not proof that a notification was missed. Prefer a finite fixture, an event ledger and an exact assertion. The check should distinguish the competing explanations rather than merely confirming the final printed value.
For a practical review, ask three questions: what did the caller request, what did the language operation actually do, and what may the host or surrounding code still change? Answering all three keeps the report useful to a learner and honest about its boundary.
Now test the tempting shortcut against this chapter’s case. A shortcut that predicts only the final value misses the decisive observation in: The operation compares the current element with the expected value while coordinating the waiter list. A mismatch returns immediately as not-equal. State what that shortcut would get wrong, then point to the one ledger entry or identity assertion that corrects it. This converts a rule into a reusable diagnostic rather than another phrase to memorise.
CHAPTER 4 OF 15 · Work the decisive branch
4. Treat zero timeout as a fast immediate branch
When the value matches but the asynchronous timeout is zero, the operation returns immediately with timed-out and avoids unnecessary promise jobs. Start by naming the object, operation and observation separately. That small discipline prevents a convenient surface description from replacing the mechanism that actually decides the result.
Worked case. Store 7, expect 7 and pass timeout 0. The record is async false with timed-out. Write the observations in order and keep values, calls and returned containers distinct. The point of the example is not merely to obtain an answer; it is to make every decisive step inspectable.
A useful trace records what is read first, which callable is invoked, what state is consulted, and whether the visible outcome is available now or later. If one of those facts is missing, two programs that look similar can be reported as though they had the same behaviour.
Changed-context check. Pass a small positive timeout. The branch may be async true, with a promise that later fulfils timed-out. Re-run the trace from the changed premise instead of editing the old conclusion. This is how the explanation transfers to unfamiliar code without turning one remembered example into a universal rule.
Limit and evidence check. Host timeout padding and scheduling mean a positive timeout is a lower-bound style signal, not an exact stopwatch promise. Prefer a finite fixture, an event ledger and an exact assertion. The check should distinguish the competing explanations rather than merely confirming the final printed value.
For a practical review, ask three questions: what did the caller request, what did the language operation actually do, and what may the host or surrounding code still change? Answering all three keeps the report useful to a learner and honest about its boundary.
Now test the tempting shortcut against this chapter’s case. A shortcut that predicts only the final value misses the decisive observation in: When the value matches but the asynchronous timeout is zero, the operation returns immediately with timed-out and avoids unnecessary promise jobs. State what that shortcut would get wrong, then point to the one ledger entry or identity assertion that corrects it. This converts a rule into a reusable diagnostic rather than another phrase to memorise.
CHAPTER 5 OF 15 · Work the decisive branch
5. Enroll a waiter only on the matching positive path
A matching value and nonzero timeout create a waiter record and return async true with a promise. The caller should branch once and normalize only if needed. Start by naming the object, operation and observation separately. That small discipline prevents a convenient surface description from replacing the mechanism that actually decides the result.
Worked case. Use r.async ? await r.value : r.value as the explicit normalizer in a controlled async function. Write the observations in order and keep values, calls and returned containers distinct. The point of the example is not merely to obtain an answer; it is to make every decisive step inspectable.
A useful trace records what is read first, which callable is invoked, what state is consulted, and whether the visible outcome is available now or later. If one of those facts is missing, two programs that look similar can be reported as though they had the same behaviour.
Changed-context check. Change the element before the call so it mismatches. The same normalizer returns not-equal without creating a promise. Re-run the trace from the changed premise instead of editing the old conclusion. This is how the explanation transfers to unfamiliar code without turning one remembered example into a universal rule.
Limit and evidence check. Do not use Promise.resolve(r.value) until after preserving the async flag if diagnostics need to distinguish the two paths. Prefer a finite fixture, an event ledger and an exact assertion. The check should distinguish the competing explanations rather than merely confirming the final printed value.
For a practical review, ask three questions: what did the caller request, what did the language operation actually do, and what may the host or surrounding code still change? Answering all three keeps the report useful to a learner and honest about its boundary.
Now test the tempting shortcut against this chapter’s case. A shortcut that predicts only the final value misses the decisive observation in: A matching value and nonzero timeout create a waiter record and return async true with a promise. The caller should branch once and normalize only if needed. State what that shortcut would get wrong, then point to the one ledger entry or identity assertion that corrects it. This converts a rule into a reusable diagnostic rather than another phrase to memorise.
CHAPTER 6 OF 15 · Work the decisive branch
6. Notify an enrolled waiter from another agent
Atomics.notify removes up to the requested count of waiters and gives notified waiters an ok result. A real demonstration needs another agent or worker capable of sharing the buffer. Start by naming the object, operation and observation separately. That small discipline prevents a convenient surface description from replacing the mechanism that actually decides the result.
Worked case. Start a worker that waits asynchronously on index 0, confirm enrolment through a message, then notify one waiter and observe ok. Write the observations in order and keep values, calls and returned containers distinct. The point of the example is not merely to obtain an answer; it is to make every decisive step inspectable.
A useful trace records what is read first, which callable is invoked, what state is consulted, and whether the visible outcome is available now or later. If one of those facts is missing, two programs that look similar can be reported as though they had the same behaviour.
Changed-context check. Notify before the worker enrols. The count can be zero and the later waiter remains pending until another notification or timeout. Re-run the trace from the changed premise instead of editing the old conclusion. This is how the explanation transfers to unfamiliar code without turning one remembered example into a universal rule.
Limit and evidence check. Notification is not stored for future waiters; coordinate the demonstration rather than relying on arbitrary delay. Prefer a finite fixture, an event ledger and an exact assertion. The check should distinguish the competing explanations rather than merely confirming the final printed value.
For a practical review, ask three questions: what did the caller request, what did the language operation actually do, and what may the host or surrounding code still change? Answering all three keeps the report useful to a learner and honest about its boundary.
Now test the tempting shortcut against this chapter’s case. A shortcut that predicts only the final value misses the decisive observation in: Atomics.notify removes up to the requested count of waiters and gives notified waiters an ok result. A real demonstration needs another agent or worker capable of sharing the buffer. State what that shortcut would get wrong, then point to the one ledger entry or identity assertion that corrects it. This converts a rule into a reusable diagnostic rather than another phrase to memorise.
A writer commonly stores a new state and then notifies, but these are distinct operations. A notification does not itself write the awaited value. Start by naming the object, operation and observation separately. That small discipline prevents a convenient surface description from replacing the mechanism that actually decides the result.
Worked case. Store 1 with Atomics.store and call Atomics.notify. The waiter wakes with ok, then rechecks the shared condition in its protocol loop. Write the observations in order and keep values, calls and returned containers distinct. The point of the example is not merely to obtain an answer; it is to make every decisive step inspectable.
A useful trace records what is read first, which callable is invoked, what state is consulted, and whether the visible outcome is available now or later. If one of those facts is missing, two programs that look similar can be reported as though they had the same behaviour.
Changed-context check. Call notify without storing. The waiter may wake, but the application condition can remain false. Re-run the trace from the changed premise instead of editing the old conclusion. This is how the explanation transfers to unfamiliar code without turning one remembered example into a universal rule.
Limit and evidence check. Use a loop around the application predicate; a wake result is not the protected data itself. Prefer a finite fixture, an event ledger and an exact assertion. The check should distinguish the competing explanations rather than merely confirming the final printed value.
For a practical review, ask three questions: what did the caller request, what did the language operation actually do, and what may the host or surrounding code still change? Answering all three keeps the report useful to a learner and honest about its boundary.
Now test the tempting shortcut against this chapter’s case. A shortcut that predicts only the final value misses the decisive observation in: A writer commonly stores a new state and then notifies, but these are distinct operations. A notification does not itself write the awaited value. State what that shortcut would get wrong, then point to the one ledger entry or identity assertion that corrects it. This converts a rule into a reusable diagnostic rather than another phrase to memorise.
CHAPTER 8 OF 15 · Change one premise
8. Handle multiple waiters and notification counts
The count argument limits how many waiters are removed from the queue. The returned number reports how many were notified, not how many agents eventually finish application work. Start by naming the object, operation and observation separately. That small discipline prevents a convenient surface description from replacing the mechanism that actually decides the result.
Worked case. Enroll two workers on the same location, notify count 1, and record one notified waiter while the other remains. Write the observations in order and keep values, calls and returned containers distinct. The point of the example is not merely to obtain an answer; it is to make every decisive step inspectable.
A useful trace records what is read first, which callable is invoked, what state is consulted, and whether the visible outcome is available now or later. If one of those facts is missing, two programs that look similar can be reported as though they had the same behaviour.
Changed-context check. Notify again or let the second timeout. Keep each outcome attached to its worker identity. Re-run the trace from the changed premise instead of editing the old conclusion. This is how the explanation transfers to unfamiliar code without turning one remembered example into a universal rule.
Limit and evidence check. Queue choice among waiters should not be presented as a product-level fairness guarantee without a stronger protocol. Prefer a finite fixture, an event ledger and an exact assertion. The check should distinguish the competing explanations rather than merely confirming the final printed value.
For a practical review, ask three questions: what did the caller request, what did the language operation actually do, and what may the host or surrounding code still change? Answering all three keeps the report useful to a learner and honest about its boundary.
Now test the tempting shortcut against this chapter’s case. A shortcut that predicts only the final value misses the decisive observation in: The count argument limits how many waiters are removed from the queue. The returned number reports how many were notified, not how many agents eventually finish application work. State what that shortcut would get wrong, then point to the one ledger entry or identity assertion that corrects it. This converts a rule into a reusable diagnostic rather than another phrase to memorise.
Near a timeout boundary, either timeout processing or notification can win according to the actual ordering. A test should accept only allowed outcomes and record the event order it controls. Start by naming the object, operation and observation separately. That small discipline prevents a convenient surface description from replacing the mechanism that actually decides the result.
Worked case. Use a generous timeout for the notification-path unit test, and a separate zero-timeout test for the immediate branch. Write the observations in order and keep values, calls and returned containers distinct. The point of the example is not merely to obtain an answer; it is to make every decisive step inspectable.
A useful trace records what is read first, which callable is invoked, what state is consulted, and whether the visible outcome is available now or later. If one of those facts is missing, two programs that look similar can be reported as though they had the same behaviour.
Changed-context check. Move notification close to the timeout only in a race test whose assertion accepts ok or timed-out as designed. Re-run the trace from the changed premise instead of editing the old conclusion. This is how the explanation transfers to unfamiliar code without turning one remembered example into a universal rule.
Limit and evidence check. A flaky single expected winner is evidence of a weak fixture, not of random language semantics. Prefer a finite fixture, an event ledger and an exact assertion. The check should distinguish the competing explanations rather than merely confirming the final printed value.
For a practical review, ask three questions: what did the caller request, what did the language operation actually do, and what may the host or surrounding code still change? Answering all three keeps the report useful to a learner and honest about its boundary.
Now test the tempting shortcut against this chapter’s case. A shortcut that predicts only the final value misses the decisive observation in: Near a timeout boundary, either timeout processing or notification can win according to the actual ordering. A test should accept only allowed outcomes and record the event order it controls. State what that shortcut would get wrong, then point to the one ledger entry or identity assertion that corrects it. This converts a rule into a reusable diagnostic rather than another phrase to memorise.
CHAPTER 10 OF 15 · Handle limits and failures
10. Validate index and numeric conversions first
The typed array, index, expected value and timeout are validated and converted before waiting. These steps can throw synchronously. Start by naming the object, operation and observation separately. That small discipline prevents a convenient surface description from replacing the mechanism that actually decides the result.
Worked case. Pass an out-of-range index and observe a RangeError before any returned record exists. Write the observations in order and keep values, calls and returned containers distinct. The point of the example is not merely to obtain an answer; it is to make every decisive step inspectable.
A useful trace records what is read first, which callable is invoked, what state is consulted, and whether the visible outcome is available now or later. If one of those facts is missing, two programs that look similar can be reported as though they had the same behaviour.
Changed-context check. Use BigInt64Array with a Number expected value, then with a BigInt expected value. The conversion boundary becomes visible. Re-run the trace from the changed premise instead of editing the old conclusion. This is how the explanation transfers to unfamiliar code without turning one remembered example into a universal rule.
Limit and evidence check. Do not route synchronous validation failures through code that assumes a record with async and value fields. Prefer a finite fixture, an event ledger and an exact assertion. The check should distinguish the competing explanations rather than merely confirming the final printed value.
For a practical review, ask three questions: what did the caller request, what did the language operation actually do, and what may the host or surrounding code still change? Answering all three keeps the report useful to a learner and honest about its boundary.
Now test the tempting shortcut against this chapter’s case. A shortcut that predicts only the final value misses the decisive observation in: The typed array, index, expected value and timeout are validated and converted before waiting. These steps can throw synchronously. State what that shortcut would get wrong, then point to the one ledger entry or identity assertion that corrects it. This converts a rule into a reusable diagnostic rather than another phrase to memorise.
Atomics.waitAsync is designed to avoid synchronous suspension of the calling agent. That does not remove the need to keep UI and worker architecture appropriate. Start by naming the object, operation and observation separately. That small discipline prevents a convenient surface description from replacing the mechanism that actually decides the result.
Worked case. Use waitAsync in a worker-coordination module and let the surrounding event loop continue while the value promise is pending. Write the observations in order and keep values, calls and returned containers distinct. The point of the example is not merely to obtain an answer; it is to make every decisive step inspectable.
A useful trace records what is read first, which callable is invoked, what state is consulted, and whether the visible outcome is available now or later. If one of those facts is missing, two programs that look similar can be reported as though they had the same behaviour.
Changed-context check. Compare with Atomics.wait in an environment where suspension is disallowed. The synchronous API can throw instead of waiting. Re-run the trace from the changed premise instead of editing the old conclusion. This is how the explanation transfers to unfamiliar code without turning one remembered example into a universal rule.
Limit and evidence check. Availability and host restrictions should be checked for the deployment environment; a spec mechanism is not a browser support promise. Prefer a finite fixture, an event ledger and an exact assertion. The check should distinguish the competing explanations rather than merely confirming the final printed value.
For a practical review, ask three questions: what did the caller request, what did the language operation actually do, and what may the host or surrounding code still change? Answering all three keeps the report useful to a learner and honest about its boundary.
Now test the tempting shortcut against this chapter’s case. A shortcut that predicts only the final value misses the decisive observation in: Atomics.waitAsync is designed to avoid synchronous suspension of the calling agent. That does not remove the need to keep UI and worker architecture appropriate. State what that shortcut would get wrong, then point to the one ledger entry or identity assertion that corrects it. This converts a rule into a reusable diagnostic rather than another phrase to memorise.
A reliable test uses explicit ready, enrolled, notify and result messages, a finite timeout and cleanup. Arbitrary sleep is only a fallback observation aid. Start by naming the object, operation and observation separately. That small discipline prevents a convenient surface description from replacing the mechanism that actually decides the result.
Worked case. Have the worker send ready, create the wait record, send its async flag, then post the final value after normalization. Terminate after the assertion. Write the observations in order and keep values, calls and returned containers distinct. The point of the example is not merely to obtain an answer; it is to make every decisive step inspectable.
A useful trace records what is read first, which callable is invoked, what state is consulted, and whether the visible outcome is available now or later. If one of those facts is missing, two programs that look similar can be reported as though they had the same behaviour.
Changed-context check. Change the initial shared value for the immediate not-equal case and verify no notification is required. Re-run the trace from the changed premise instead of editing the old conclusion. This is how the explanation transfers to unfamiliar code without turning one remembered example into a universal rule.
Limit and evidence check. Always cap the test duration and terminate workers so a failed assertion cannot leave the process hanging. Prefer a finite fixture, an event ledger and an exact assertion. The check should distinguish the competing explanations rather than merely confirming the final printed value.
For a practical review, ask three questions: what did the caller request, what did the language operation actually do, and what may the host or surrounding code still change? Answering all three keeps the report useful to a learner and honest about its boundary.
Now test the tempting shortcut against this chapter’s case. A shortcut that predicts only the final value misses the decisive observation in: A reliable test uses explicit ready, enrolled, notify and result messages, a finite timeout and cleanup. Arbitrary sleep is only a fallback observation aid. State what that shortcut would get wrong, then point to the one ledger entry or identity assertion that corrects it. This converts a rule into a reusable diagnostic rather than another phrase to memorise.
CHAPTER 13 OF 15 · Verify and explain
13. Normalize outcomes without losing diagnostics
Application code may want one promise-returning helper, but the helper can return diagnostic fields alongside the normalized outcome. Start by naming the object, operation and observation separately. That small discipline prevents a convenient surface description from replacing the mechanism that actually decides the result.
Worked case. Return {wasAsync:r.async, outcome: r.async ? await r.value : r.value} from a wrapper. Write the observations in order and keep values, calls and returned containers distinct. The point of the example is not merely to obtain an answer; it is to make every decisive step inspectable.
A useful trace records what is read first, which callable is invoked, what state is consulted, and whether the visible outcome is available now or later. If one of those facts is missing, two programs that look similar can be reported as though they had the same behaviour.
Changed-context check. Add elapsed time only as host telemetry, not as the definition of timed-out. Re-run the trace from the changed premise instead of editing the old conclusion. This is how the explanation transfers to unfamiliar code without turning one remembered example into a universal rule.
Limit and evidence check. Preserve the three language outcomes not-equal, timed-out and ok rather than converting all of them to a Boolean. Prefer a finite fixture, an event ledger and an exact assertion. The check should distinguish the competing explanations rather than merely confirming the final printed value.
For a practical review, ask three questions: what did the caller request, what did the language operation actually do, and what may the host or surrounding code still change? Answering all three keeps the report useful to a learner and honest about its boundary.
Now test the tempting shortcut against this chapter’s case. A shortcut that predicts only the final value misses the decisive observation in: Application code may want one promise-returning helper, but the helper can return diagnostic fields alongside the normalized outcome. State what that shortcut would get wrong, then point to the one ledger entry or identity assertion that corrects it. This converts a rule into a reusable diagnostic rather than another phrase to memorise.
CHAPTER 14 OF 15 · Verify and explain
14. Transfer the trace to a versioned state cell
Imagine a worker waits while state cell 0 equals version 12. A producer stores 13 and notifies. The waiter wakes, then reads the new version and associated data. Start by naming the object, operation and observation separately. That small discipline prevents a convenient surface description from replacing the mechanism that actually decides the result.
Worked case. If the cell is already 13 when waitAsync expects 12, the immediate not-equal branch tells the consumer to re-read instead of sleep. Write the observations in order and keep values, calls and returned containers distinct. The point of the example is not merely to obtain an answer; it is to make every decisive step inspectable.
A useful trace records what is read first, which callable is invoked, what state is consulted, and whether the visible outcome is available now or later. If one of those facts is missing, two programs that look similar can be reported as though they had the same behaviour.
Changed-context check. Use timeout 0 as a poll-style check, then a positive timeout only when actual waiting is intended. Re-run the trace from the changed premise instead of editing the old conclusion. This is how the explanation transfers to unfamiliar code without turning one remembered example into a universal rule.
Limit and evidence check. The version cell coordinates visibility; the application must still define how larger payloads are published and validated. Prefer a finite fixture, an event ledger and an exact assertion. The check should distinguish the competing explanations rather than merely confirming the final printed value.
For a practical review, ask three questions: what did the caller request, what did the language operation actually do, and what may the host or surrounding code still change? Answering all three keeps the report useful to a learner and honest about its boundary.
Now test the tempting shortcut against this chapter’s case. A shortcut that predicts only the final value misses the decisive observation in: Imagine a worker waits while state cell 0 equals version 12. A producer stores 13 and notifies. The waiter wakes, then reads the new version and associated data. State what that shortcut would get wrong, then point to the one ledger entry or identity assertion that corrects it. This converts a rule into a reusable diagnostic rather than another phrase to memorise.
CHAPTER 15 OF 15 · Verify and explain
15. Write the final report around three branches
A concise explanation lists mismatch, zero-timeout match and enrolled match as separate branches, then records notification or timeout for the last branch. Start by naming the object, operation and observation separately. That small discipline prevents a convenient surface description from replacing the mechanism that actually decides the result.
Worked case. Report async false/not-equal for mismatch, async false/timed-out for zero, and async true/Promise for a matching positive wait. Write the observations in order and keep values, calls and returned containers distinct. The point of the example is not merely to obtain an answer; it is to make every decisive step inspectable.
A useful trace records what is read first, which callable is invoked, what state is consulted, and whether the visible outcome is available now or later. If one of those facts is missing, two programs that look similar can be reported as though they had the same behaviour.
Changed-context check. Changed report: notify count one after enrolment; value promise fulfils ok; consumer reloads shared state. Re-run the trace from the changed premise instead of editing the old conclusion. This is how the explanation transfers to unfamiliar code without turning one remembered example into a universal rule.
Limit and evidence check. Do not say waitAsync always returns a promise. It always returns a record whose value type depends on the branch. Prefer a finite fixture, an event ledger and an exact assertion. The check should distinguish the competing explanations rather than merely confirming the final printed value.
For a practical review, ask three questions: what did the caller request, what did the language operation actually do, and what may the host or surrounding code still change? Answering all three keeps the report useful to a learner and honest about its boundary.
Now test the tempting shortcut against this chapter’s case. A shortcut that predicts only the final value misses the decisive observation in: A concise explanation lists mismatch, zero-timeout match and enrolled match as separate branches, then records notification or timeout for the last branch. State what that shortcut would get wrong, then point to the one ledger entry or identity assertion that corrects it. This converts a rule into a reusable diagnostic rather than another phrase to memorise.
Continue with connected lessons
Trace views after buffer resizing
Trace views after buffer resizing. Follow buffer state and view boundaries before reasoning about shared storage.
Separate buffer transfer from byte copying
Separate buffer transfer from byte copying. Keep storage ownership and copying distinct from shared-memory waiting.
Keep cancellation separate from Promise rejection
Keep cancellation separate from Promise rejection. A pending wait promise also needs an explicit lifecycle protocol.
Frequently asked questions
Does Atomics.waitAsync return a promise?
It returns a record. When async is true, value is a promise; when false, value is the immediate string not-equal or timed-out.
Why can the result be not-equal immediately?
The current shared element did not match the expected value, so there is no reason to enrol a waiter.
What happens with a zero timeout?
If the value matches, the asynchronous operation returns an immediate timed-out record rather than creating a pending promise.
Does Atomics.notify change the shared value?
No. Store the application state separately; notification only wakes eligible waiters.
Can notify happen before a waiter enrols?
Yes, and that notification is not saved for a future waiter. Coordinate enrolment in tests and protocols.
What is the safest normalizer?
Inspect the record once: record.async ? await record.value : record.value, while preserving the flag when diagnostics matter.
Authoritative sources and further reading
ECMAScript: Atomics.waitAsync. The asynchronous waiting entry point.
ECMAScript: DoWait. Mismatch, zero timeout, waiter enrolment and returned record shapes.
ECMAScript: Atomics.notify. Notification count and waiter removal.
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