What would have happened if Gradle was limited to _only Java 11_ at the time?

## Decision

1. The Gradle distribution will never include a Java runtime.
   Instead, Gradle will leverage Java toolchains for the Daemon and worker processes.

 * elements FIFO (first-in-first-out). The head of the queue is that element that has been
 * on the queue the longest time. The tail of the queue is that element that has been on
 * the queue the shortest time. New elements are inserted at the tail of the queue, and the queue
 * retrieval operations obtain elements at the head of the queue.
 *

If <code>x</code> is <code>nil</code>, an attempt to evaluate <code>*x</code>
will cause a <a href="#Run_time_panics">run-time panic</a>.
</p>

<pre>
&amp;x
&amp;a[f(2)]
&amp;Point{2, 3}
*p
*pf(x)

var x *int = nil
*x   // causes a run-time panic
&amp;*x  // causes a run-time panic
</pre>


<h3 id="Receive_operator">Receive operator</h3>

<p>

    fun cancel()
  }

  companion object {
    /**
     * The timeout to use while discarding a stream of input data. Since this is used for connection
     * reuse, this timeout should be significantly less than the time it takes to establish a new
     * connection.
     */
    const val DISCARD_STREAM_TIMEOUT_MILLIS = 100
  }

 *   protected void visitWildcardType(WildcardType t) {
 *     throw new IllegalArgumentException("Cannot contain wildcard type.");
 *   }
 * }.visit(type);
 * }
 *
 * <p>One {@code Type} is visited at most once. The second time the same type is visited, it's
 * ignored by {@link #visit}. This avoids infinite recursion caused by recursive type bounds.
 *
 * <p>This class is not thread safe.
 *
 * @author Ben Yu
 */

    // value seen so far
    while (cache.getUnchecked(nextRandomKey()) < maximumSize) {}

    requests.set(0);
    misses.set(0);
  }

  @Benchmark
  int time(int reps) {
    int dummy = 0;
    for (int i = 0; i < reps; i++) {
      dummy += cache.getUnchecked(nextRandomKey());
    }
    requests.addAndGet(reps);
    return dummy;
  }

  private int nextRandomKey() {

        long create = 1600000000000L;
        long lastAccess = 1600000100000L;
        long lastWrite = 1600000200000L;
        long change = 1600000300000L;
        int attributes = 0x1234;
        // Convert Unix time to Windows FILETIME (100-nanosecond intervals since 1601)
        long MILLISECONDS_BETWEEN_1970_AND_1601 = 11644473600000L;
        writeLong(buffer, 0, (create + MILLISECONDS_BETWEEN_1970_AND_1601) * 10000L);

    return new MinimalIterable<>(asList(elements).iterator());
  }

  /**
   * Returns an iterable whose iterator returns the given elements in order. The elements are copied
   * out of the source collection at the time this method is called.
   */
  @SuppressWarnings("unchecked") // Es come in, Es go out
  public static <E extends @Nullable Object> MinimalIterable<E> from(Collection<E> elements) {

        // Referral flags (2 bytes)
        SMBUtil.writeInt2(0, buffer, 14);

        // Proximity (2 bytes for v3)
        SMBUtil.writeInt2(0, buffer, 16);

        // Time to live (2 bytes for v3)
        SMBUtil.writeInt2(300, buffer, 18);

        // DFS path offset (2 bytes) - points to string data
        SMBUtil.writeInt2(stringDataStart - 8, buffer, 20); // Offset from start of referral

   * types. CharBuffer has poor performance when being written into or read out of so round tripping
   * all the bytes through the buffer takes a long time. With these specialized types we can just
   * use a char array.
   *
   * @param from the object to read from
   * @param to the object to write to
   * @return the number of characters copied