boolean[] VALUES = BooleansTest.VALUES;
    VALUES = Booleans.concat(VALUES, VALUES);

    for (int delta : new int[] {+1, 0, -1}) {
      for (int i = 0; i < VALUES.length; i++) {
        List<Boolean> list = Booleans.asList(VALUES).subList(0, i);
        Collection<Boolean> misleadingSize = Helpers.misleadingSizeCollection(delta);
        misleadingSize.addAll(list);
        boolean[] arr = Booleans.toArray(misleadingSize);

  }

  public void testToArray_threadSafe() {
    for (int delta : new int[] {+1, 0, -1}) {
      for (int i = 0; i < VALUES.length; i++) {
        List<Double> list = Doubles.asList(VALUES).subList(0, i);
        Collection<Double> misleadingSize = Helpers.misleadingSizeCollection(delta);
        misleadingSize.addAll(list);
        double[] arr = Doubles.toArray(misleadingSize);

  }

  public void testToArray_threadSafe() {
    for (int delta : new int[] {+1, 0, -1}) {
      for (int i = 0; i < VALUES.length; i++) {
        List<Long> list = Longs.asList(VALUES).subList(0, i);
        Collection<Long> misleadingSize = Helpers.misleadingSizeCollection(delta);
        misleadingSize.addAll(list);
        long[] arr = Longs.toArray(misleadingSize);

  }

  public void testToArray_threadSafe() {
    for (int delta : new int[] {+1, 0, -1}) {
      for (int i = 0; i < VALUES.length; i++) {
        List<Short> list = Shorts.asList(VALUES).subList(0, i);
        Collection<Short> misleadingSize = Helpers.misleadingSizeCollection(delta);
        misleadingSize.addAll(list);
        short[] arr = Shorts.toArray(misleadingSize);

  }

  public void testToArray_threadSafe() {
    for (int delta : new int[] {+1, 0, -1}) {
      for (int i = 0; i < VALUES.length; i++) {
        List<Float> list = Floats.asList(VALUES).subList(0, i);
        Collection<Float> misleadingSize = Helpers.misleadingSizeCollection(delta);
        misleadingSize.addAll(list);
        float[] arr = Floats.toArray(misleadingSize);

  }

  public void testToArray_threadSafe() {
    for (int delta : new int[] {+1, 0, -1}) {
      for (int i = 0; i < VALUES.length; i++) {
        List<Integer> list = Ints.asList(VALUES).subList(0, i);
        Collection<Integer> misleadingSize = Helpers.misleadingSizeCollection(delta);
        misleadingSize.addAll(list);
        int[] arr = Ints.toArray(misleadingSize);

  }

  public void testToArray_threadSafe() {
    for (int delta : new int[] {+1, 0, -1}) {
      for (int i = 0; i < VALUES.length; i++) {
        List<Float> list = Floats.asList(VALUES).subList(0, i);
        Collection<Float> misleadingSize = Helpers.misleadingSizeCollection(delta);
        misleadingSize.addAll(list);
        float[] arr = Floats.toArray(misleadingSize);

    val startNanos = System.nanoTime()
    assertFailsWith<InterruptedIOException> {
      stream.takeHeaders()
    }
    val elapsedNanos = System.nanoTime() - startNanos
    awaitWatchdogIdle()
    // 200ms delta
    assertThat(TimeUnit.NANOSECONDS.toMillis(elapsedNanos).toDouble())
      .isCloseTo(500.0, 200.0)
    assertThat(connection.openStreamCount()).isEqualTo(0)

    // Verify the peer received what was expected.

Neste caso, `str` é o parâmetro de tipo passado para `List` (ou `list` no Python 3.9 ou superior).

///

Isso significa: "a variável `items` é uma `list`, e cada um dos itens desta lista é uma `str`".

/// tip | Dica

Se você usa o Python 3.9 ou superior, você não precisa importar `List` de `typing`. Você pode utilizar o mesmo tipo `list` no lugar.

///

    // array slot is read and written exactly once. However, it can have very poor memory locality:
    // benchmarking shows it can take 7 times longer than the other two in some cases. The other two
    // do n swaps, minus a delta (0 or 2 for Reversal, gcd(d, n) for Successive), so that's about
    // twice as many reads and writes. But benchmarking shows that they usually perform better than