// Example taken from twitter/hpack DecoderTest.testInsidiousMaxHeaderSize
  @Test
  fun readHeaderTableStateChangeInsidiousMaxHeaderByteCount() {
    bytesIn.writeByte(0x3f)
    bytesIn.write("e1ffffff07".decodeHex()) // count = -2147483648
    assertFailsWith<IOException> {
      hpackReader!!.readHeaders()
    }.also { expected ->
      assertThat(expected.message)
        .isEqualTo("Invalid dynamic table size update -2147483648")
    }

				spb = append(strconv.AppendInt(spb, s.Length, 10), '\n')
			}
			pad := blockPadding(int64(len(spb)))
			spb = append(spb, zeroBlock[:pad]...)
			hdr.Size += int64(len(spb)) // Accounts for encoded sparse map

			// Add and modify appropriate PAX records.
			dir, file := path.Split(realName)
			hdr.Name = path.Join(dir, "GNUSparseFile.0", file)
			paxHdrs[paxGNUSparseMajor] = "1"

- Object count quota is now supported for namespaced custom resources using the `count/<resource>.<group>` syntax. ([#72384](https://github.com/kubernetes/kubernetes/pull/72384), [@zhouhaibing089](https://github.com/zhouhaibing089))

Alternately, you can provide a YAML file that specifies parameter values while installing the chart. For example, ```bash helm install --name my-release -f values.yaml minio/minio ``` Persistence ---------- This chart provisions a PersistentVolumeClai and mounts corresponding persistent volume to default location `/export`. You'll need physical storage available in the Kubernetes cluster for this to work. If you'd rather use `emptyDir`, disable PersistentVolumeClai by: ```bash helm install --set persistence.enabled=false...

    }
    ```

    This above code relies on this `responseCount` extension val:

    ```kotlin
    val Response.responseCount: Int
      get() = generateSequence(this) { it.priorResponse }.count()
    ```
=== ":material-language-java: Java"
    ```java
      private final OkHttpClient client;

      public Authenticate() {
        client = new OkHttpClient.Builder()

pkg go/types, const Float32 BasicKind
pkg go/types, const Float64 = 14
pkg go/types, const Float64 BasicKind
pkg go/types, const Int = 2
pkg go/types, const Int BasicKind
pkg go/types, const Int16 = 4
pkg go/types, const Int16 BasicKind
pkg go/types, const Int32 = 5
pkg go/types, const Int32 BasicKind
pkg go/types, const Int64 = 6
pkg go/types, const Int64 BasicKind
pkg go/types, const Int8 = 3
pkg go/types, const Int8 BasicKind

    // for 5.5 seconds happens about 2% of the time.
    boolean longWait = NANOSECONDS.toSeconds(thread.timeSpentBlocked) >= 5;
    // Count how long it actually took to return; we'll accept any number between the expected delay
    // and the approximate actual delay, to be robust to variance in thread scheduling.
    char overWaitNanosFirstDigit =

La **concurrence** et le **parallélisme** sont tous deux liés à l'idée de "différentes choses arrivant plus ou moins au même moment".

Mais les détails entre la **concurrence** et le **parallélisme** diffèrent sur de nombreux points.

Pour expliquer la différence, voici une histoire de burgers :

#### Burgers concurrents

    @Override
    public int count(@Nullable Object element) {
      Collection<V> values = Maps.safeGet(multimap.asMap(), element);
      return (values == null) ? 0 : values.size();
    }

    @Override
    public int remove(@Nullable Object element, int occurrences) {
      checkNonnegative(occurrences, "occurrences");
      if (occurrences == 0) {
        return count(element);
      }

    @Override
    public int count(@Nullable Object element) {
      Collection<V> values = Maps.safeGet(multimap.asMap(), element);
      return (values == null) ? 0 : values.size();
    }

    @Override
    public int remove(@Nullable Object element, int occurrences) {
      checkNonnegative(occurrences, "occurrences");
      if (occurrences == 0) {
        return count(element);
      }