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async-ordering-tests

Test async ordering - event-loop / queue / channel ordering assertions, JS Promise microtask vs macrotask ordering, Python `asyncio.gather` vs `asyncio.wait_for` semantics, Go goroutine + channel happens-before relationships, async/await re-entrancy. Use deterministic schedulers (sinon fake timers, asyncio test mode) to remove run-to-run variance. Use when a callback fires twice, a later response overwrites an earlier one, or a cancelled parent task leaves a child still running - bugs where completion order, not shared memory, is the defect.

Install with skills.sh (any agent)

npx skills add testland/qa --skill async-ordering-tests
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async-ordering-tests

Async ordering bugs ("user A's update overwrote user B's" / "callback fired twice" / "promise resolved before fetch returned") look like race conditions but operate at the runtime level (event loop / scheduler). Tests must control the scheduler to be deterministic.

When to use

  • UI updates that depend on multiple in-flight requests resolving in the right order.
  • Server-side: parallel I/O whose completion order affects the final state.
  • Callback-heavy code where re-entrancy (sync vs async dispatch) matters.

Step 1 - JS Promise microtask vs macrotask

// Microtasks (Promise callbacks) drain BEFORE next macrotask (setTimeout)
test('microtasks drain before setTimeout', async () => {
  const order: string[] = [];

  setTimeout(() => order.push('setTimeout'), 0);
  Promise.resolve().then(() => order.push('promise'));

  // Wait for both to fire
  await new Promise(r => setTimeout(r, 0));

  expect(order).toEqual(['promise', 'setTimeout']);
});

Critical: promise resolution callbacks run in the microtask queue, which drains between macrotasks. Misunderstanding this causes "why did this fire twice" bugs.

Step 2 - Use deterministic timers (Sinon / Vitest fake)

import { vi } from 'vitest';

test('debounced search fires once after 300ms', () => {
  vi.useFakeTimers();
  const search = vi.fn();
  const debounced = debounce(search, 300);

  debounced('a');
  debounced('ab');
  debounced('abc');

  vi.advanceTimersByTime(299);
  expect(search).not.toHaveBeenCalled();

  vi.advanceTimersByTime(1);
  expect(search).toHaveBeenCalledOnce();
  expect(search).toHaveBeenCalledWith('abc');
});

Real timers + sleep = flake. Fake timers = deterministic.

Step 3 - Promise.all vs sequential await

test('parallel fetch starts both before either completes', async () => {
  const order: string[] = [];

  function trackedFetch(name: string) {
    order.push(`start-${name}`);
    return new Promise<string>((resolve) =>
      setTimeout(() => {
        order.push(`done-${name}`);
        resolve(name);
      }, 50)
    );
  }

  await Promise.all([trackedFetch('A'), trackedFetch('B')]);

  // Both started before either finished
  expect(order.indexOf('done-A')).toBeGreaterThan(order.indexOf('start-B'));
});

vs sequential:

test('sequential await runs A fully before B starts', async () => {
  const order: string[] = [];
  await trackedFetch('A');
  await trackedFetch('B');

  expect(order).toEqual(['start-A', 'done-A', 'start-B', 'done-B']);
});

Test the actual model your code uses, especially when "parallelize" is an intentional optimization.

Step 4 - Python asyncio ordering

import asyncio

async def test_gather_concurrency_with_first_completed():
    started = []
    finished = []

    async def task(name, delay):
        started.append(name)
        await asyncio.sleep(delay)
        finished.append(name)

    await asyncio.gather(task("A", 0.05), task("B", 0.01))

    # Both started before either finished
    assert started == ["A", "B"]
    # B finishes first (shorter sleep)
    assert finished == ["B", "A"]

For race-style: use asyncio.wait(..., return_when=FIRST_COMPLETED) to test "whoever finishes first wins" semantics.

Step 5 - Async re-entrancy

A callback fires while another callback is still running. Tests:

test('handler not invoked while previous invocation in progress', async () => {
  const calls: string[] = [];
  let inProgress = false;

  const handler = async (msg: string) => {
    calls.push(`enter-${msg}`);
    if (inProgress) {
      throw new Error('Re-entrant call detected');
    }
    inProgress = true;
    await new Promise(r => setTimeout(r, 10));
    inProgress = false;
    calls.push(`exit-${msg}`);
  };

  const queue = createSerializingQueue(handler);
  queue.enqueue('a');
  queue.enqueue('b');

  await queue.drain();
  expect(calls).toEqual(['enter-a', 'exit-a', 'enter-b', 'exit-b']);
});

Test guards: queue serializes enqueued work even if event loop allows interleaving.

Step 6 - Go channel happens-before

func TestChannelHappensBefore(t *testing.T) {
    var x int
    done := make(chan struct{})

    go func() {
        x = 42        // (1)
        done <- struct{}{}  // (2)
    }()

    <-done           // (3)
    if x != 42 {     // (4) - guaranteed by happens-before
        t.Fatalf("expected 42, got %d", x)
    }
}

Go memory model: (1) happens-before (2); (2) happens-before (3); (3) happens-before (4). Without channel sync, (4) could see 0 even though (1) ran in the goroutine.

For tests, run with -race:

go test -race ./...

Step 7 - Backpressure / queue overflow

async def test_queue_drops_when_full():
    queue = asyncio.Queue(maxsize=3)
    dropped = []

    async def producer():
        for i in range(10):
            try:
                queue.put_nowait(i)
            except asyncio.QueueFull:
                dropped.append(i)

    await producer()
    assert len(dropped) == 7

Bounded queues + drop-on-full = silent data loss. Test the policy explicitly.

Step 8 - Cancellation propagation

async def test_cancellation_propagates_to_children():
    child_started = asyncio.Event()
    child_cancelled = asyncio.Event()

    async def child():
        try:
            child_started.set()
            await asyncio.sleep(60)
        except asyncio.CancelledError:
            child_cancelled.set()
            raise

    async def parent():
        await child()

    parent_task = asyncio.create_task(parent())
    await child_started.wait()

    parent_task.cancel()
    with pytest.raises(asyncio.CancelledError):
        await parent_task

    assert child_cancelled.is_set()

Common bug: parent cancelled, child task leaks (continues running).

Anti-patterns

Anti-patternWhy it failsFix
await sleep(100) to "let things settle"Flake on slow CIFake timers / explicit waits (Step 2)
Test Promise.all order assuming sequentialNon-deterministic interleaveTest model explicitly (Step 3)
Skip cancellation testsCancelled tasks leak foreverCancellation propagation test (Step 8)
Use real timers + setTimeout(0) for "next tick"Race with microtask drainqueueMicrotask() or Promise.resolve()
Test only "happy path" with single taskConcurrency bugs hideMulti-task scenarios (Step 4)

Limitations

  • Microtask vs macrotask semantics differ across runtimes (Node process.nextTick is a third queue between).
  • asyncio's behavior changed across Python versions (3.10's task-cancellation handling differs from 3.7).
  • Go's -race finds data races, not all happens-before violations.
  • Some libraries (RxJS) layer their own scheduling over the runtime - test their semantics, not just the runtime's.

References

  • ECMAScript spec - runtime job semantics; consult tc39.es/ecma262
  • Python asyncio docs - docs.python.org/3/library/asyncio.html
  • Go memory model - go.dev/ref/mem
  • race-condition-test-author, deadlock-detection-harness - sister concurrency skills

Related skills

deadlock-detection-harness

Build deadlock-detection harnesses - extract lock-acquire-order graph via instrumentation, run cycle detection (DFS) to spot inconsistent ordering, use lock-acquire timeouts to surface rather than hang, JVM `jstack` / `gdb thread apply all bt` for postmortem analysis. Pair with ThreadSanitizer's `detect_deadlocks=1` for runtime detection. Use when a service that holds two or more locks hangs in production with no crash or error, or before release when lock acquisition order across code paths has never been proven consistent.

go-race-detector-workflow

Runs the Go race detector and goroutine-leak checker end-to-end: instrument with `go test -race`, read race reports, configure GORACE options, stress with `-count`/`-cpu`, detect goroutine leaks with go.uber.org/goleak, and gate both checks in CI. Use when a Go service has shared state accessed by concurrent goroutines, when a race-related incident needs a regression harness, or when adding `-race` to a CI matrix for a Go module. Does not cover barrier-based deterministic interleaving or forced goroutine scheduling; use race-condition-test-author for that.

jepsen-patterns

Reference for Jepsen-style distributed-systems testing - consistency models hierarchy (linearizability vs sequential vs causal vs monotonic-reads vs eventual), nemesis primitives (network partitions, clock skew, kill nodes), workload generators, Knossos + Elle linearizability checkers. Reference-only because Jepsen tests are typically Clojure-bespoke per system; use this skill to evaluate vendor claims and structure your own test. Use when a datastore vendor advertises a consistency guarantee that has to be checked before adoption, when reading a published Jepsen report for gaps, or when a custom replicated store needs its own consistency test scoped.

mvcc-isolation-tests

Build per-database MVCC isolation-level tests - Read Uncommitted vs Read Committed vs Repeatable Read vs Serializable; verify which anomalies are prevented at each level (dirty read, non-repeatable read, phantom read, serialization anomaly, write skew). Per PostgreSQL transaction isolation docs; analogous patterns for MySQL InnoDB, SQL Server, and DynamoDB. Use when two concurrent transactions can touch the same rows (balance debit, seat booking, stock decrement), or before changing a service's default isolation level.

race-condition-test-author

Build deterministic race-condition tests - identify shared mutable state, drive interleavings via barriers / latches / manual scheduling; use ThreadSanitizer (clang `-fsanitize=thread`) for C/C++/Go data race detection; use jcstress (`@JCStressTest` + `@Actor` + `@Outcome`) for JVM stress; use Loom virtual-thread interleavings for parallel testing. Use when a defect only reproduces under load on shared in-process state (cache, counter, connection pool, lazy-init singleton), or when writing the regression test for a race-condition incident before the fix lands.