computationLatch.countDown();
    // let some computations complete
    while (computedCount.get() < nThreads) {
      Thread.yield();
    }
    cache.invalidateAll();
    tasksFinished.await();

    // Check all of the removal notifications we received: they should have had correctly-associated
    // keys and values. (An earlier bug saw removal notifications for in-progress computations,
    // which had real keys with null values.)

    computationLatch.countDown();
    // let some computations complete
    while (computedCount.get() < nThreads) {
      Thread.yield();
    }
    cache.invalidateAll();
    tasksFinished.await();

    // Check all of the removal notifications we received: they should have had correctly-associated
    // keys and values. (An earlier bug saw removal notifications for in-progress computations,
    // which had real keys with null values.)

      }
    }.start();

    getStartedSignal.await();

    // computation is in progress; asMap shouldn't have changed
    assertThat(map).hasSize(1);
    assertThat(map.containsKey(getKey)).isFalse();
    assertThat(map.get(refreshKey)).isSameInstanceAs(refreshKey);

    // let computation complete
    letGetFinishSignal.countDown();
    getFinishedSignal.await();
    checkNothingLogged();

      }
    }.start();

    getStartedSignal.await();

    // computation is in progress; asMap shouldn't have changed
    assertThat(map).hasSize(1);
    assertThat(map.containsKey(getKey)).isFalse();
    assertThat(map.get(refreshKey)).isSameInstanceAs(refreshKey);

    // let computation complete
    letGetFinishSignal.countDown();
    getFinishedSignal.await();
    checkNothingLogged();

  * Note that NumPy's type promotion rules have been changed(See [NEP 50](https://numpy.org/neps/nep-0050-scalar-promotion.html#nep50)for details). This may change the precision at which computations happen, leading either to type errors or to numerical changes to results.

  @Deprecated
  public Quantiles() {}

  /** Specifies the computation of a median (i.e. the 1st 2-quantile). */
  public static ScaleAndIndex median() {
    return scale(2).index(1);
  }

  /** Specifies the computation of quartiles (i.e. 4-quantiles). */
  public static Scale quartiles() {
    return scale(4);
  }

  /** Specifies the computation of percentiles (i.e. 100-quantiles). */

Puedes ver más detalles en [la documentación oficial de Starlette sobre Background Tasks](https://www.starlette.dev/background/).

## Advertencia { #caveat }

```

Pero justo en el momento en que Python compara la primera `j` en `johndoe` con la primera `s` en `stanleyjobson`, devolverá `False`, porque ya sabe que esas dos strings no son iguales, pensando que "no hay necesidad de gastar más computación comparando el resto de las letras". Y tu aplicación dirá "Nombre de usuario o contraseña incorrectos".

Pero luego los atacantes prueban con el nombre de usuario `stanleyjobsox` y contraseña `love123`.

import java.util.concurrent.atomic.AtomicReference;
import org.jspecify.annotations.Nullable;

/**
 * A step in a pipeline of an asynchronous computation. When the last step in the computation is
 * complete, some objects captured during the computation are closed.
 *
 * <p>A pipeline of {@code ClosingFuture}s is a tree of steps. Each step represents either an

   * computation is {@linkplain java.util.concurrent.Future#isDone() complete} or, if the
   * computation is already complete, immediately.
   *
   * <p>The callback is run on {@code executor}. There is no guaranteed ordering of execution of
   * callbacks, but any callback added through this method is guaranteed to be called once the
   * computation is complete.
   *