case ADD:
            {
              int delta = random.nextInt(10);
              multiset.add(key, delta);
              deltas[keyIndex] += delta;
              break;
            }
          case SET_COUNT:
            {
              int newValue = random.nextInt(3);
              int oldValue = multiset.setCount(key, newValue);
              deltas[keyIndex] += newValue - oldValue;
              break;

          int key2 = key1 ^ delta;

          // get hashes
          int hash1 = function.hashInt(key1).asInt();
          int hash2 = function.hashInt(key2).asInt();

          // this 2-bit candidate delta is not a characteristic
          // if deltas are different
          if ((hash1 ^ hash2) != delta) {
            diff = true;
            continue;
          }

        "run again after ${formatDuration(executeNanoTime - now)}"
      } else {
        "scheduled after ${formatDuration(executeNanoTime - now)}"
      }
    }

    // Insert in chronological order. Always compare deltas because nanoTime() is permitted to wrap.
    var insertAt = futureTasks.indexOfFirst { it.nextExecuteNanoTime - now > delayNanos }
    if (insertAt == -1) insertAt = futureTasks.size
    futureTasks.add(insertAt, task)

  }

  /** Returns a new bias. */
  private fun adapt(
    delta: Int,
    numpoints: Int,
    first: Boolean,
  ): Int {
    var delta =
      when {
        first -> delta / DAMP
        else -> delta / 2
      }
    delta += (delta / numpoints)
    var k = 0
    while (delta > ((BASE - TMIN) * TMAX) / 2) {
      delta /= (BASE - TMIN)
      k += BASE
    }

 * This controller manages delays and timing for various crawling states
 * including processing delays, queue waiting times, and new URL discovery.
 */
public class FessIntervalController extends DefaultIntervalController {

    /**
     * Default constructor.
     */
    public FessIntervalController() {
        super();
    }

    /**
     * Gets the delay time in milliseconds after processing a URL.
     *

    double x1 = 1.2;
    double y1 = 3.4;
    double xDelta = 5.6;
    double yDelta = 7.8;
    LinearTransformation transformation =
        LinearTransformation.mapping(x1, y1).and(x1 + xDelta, y1 + yDelta);
    assertDiagonalLinearTransformation(transformation, x1, y1, xDelta, yDelta);
  }

  public void testMappingAnd_horizontal() {
    double x1 = 1.2;
    double xDelta = 3.4;
    double y = 5.6;

    double x1 = 1.2;
    double y1 = 3.4;
    double xDelta = 5.6;
    double yDelta = 7.8;
    LinearTransformation transformation =
        LinearTransformation.mapping(x1, y1).and(x1 + xDelta, y1 + yDelta);
    assertDiagonalLinearTransformation(transformation, x1, y1, xDelta, yDelta);
  }

  public void testMappingAnd_horizontal() {
    double x1 = 1.2;
    double xDelta = 3.4;
    double y = 5.6;

      "FINE: Q10000 finished run in   0 µs: task",
    )
  }

  /** Repeat with a delay of 200 but schedule with a delay of 50. The schedule wins. */
  @Test fun executeScheduledEarlierReplacesRepeatedLater() {
    val task =
      object : Task("task") {
        val schedules = mutableListOf(50.µs)
        val delays = mutableListOf(200.µs, -1)

        override fun runOnce(): Long {

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