/**
 * One or more variables that together maintain an initially zero {@code long} sum. When updates
 * (method {@link #add}) are contended across threads, the set of variables may grow dynamically to
 * reduce contention. Method {@link #sum} (or, equivalently, {@link #longValue}) returns the current
 * total combined across the variables maintaining the sum.
 *

  }

  /**
   * Returns a larger power of 2 hashtable size given the current mask.
   *
   * <p>For hashtable sizes less than or equal to 32, the returned power of 2 is 4x the current
   * hashtable size to reduce expensive rehashing. Otherwise the returned power of 2 is 2x the
   * current hashtable size.
   */
  static int newCapacity(int mask) {
    return ((mask < 32) ? 4 : 2) * (mask + 1);
  }

Die unterstützenden zusätzlichen Funktionen `fake_password_hasher` und `fake_save_user` dienen nur zur Demo eines möglichen Datenflusses, bieten jedoch natürlich keine echte Sicherheit.

///

## Verdopplung vermeiden { #reduce-duplication }

Die Reduzierung von Code-Verdoppelung ist eine der Kernideen von **FastAPI**.

Вспомогательные функции `fake_password_hasher` и `fake_save_user` используются только для демонстрации возможного потока данных и, конечно, не обеспечивают настоящую безопасность.

///

## Сократите дублирование { #reduce-duplication }

Сокращение дублирования кода - это одна из главных идей **FastAPI**.

As funções adicionais de suporte `fake_password_hasher` e `fake_save_user` servem apenas para demonstrar um fluxo possível dos dados, mas é claro que elas não fornecem segurança real.

///

## Reduzir duplicação { #reduce-duplication }

Reduzir a duplicação de código é uma das ideias principais no **FastAPI**.

 * </ul>
 *
 * <p>The one downside of {@code Stopwatch} relative to {@link System#nanoTime()} is that {@code
 * Stopwatch} requires object allocation and additional method calls, which can reduce the accuracy
 * of the elapsed times reported. {@code Stopwatch} is still suitable for logging and metrics where
 * reasonably accurate values are sufficient. If the uncommon case that you need to maximize

   * following conditions:
   *
   * <ul>
   *   <li>You want to assign the same fraction of inputs to each bucket.
   *   <li>When you reduce the number of buckets, you can accept that the most recently added
   *       buckets will be removed first. More concretely, if you are dividing traffic among tasks,

		// a row, then make sure we print it to call attention.
		if m[err.Error()] > 2 {
			peersLogAlwaysIf(ctx, fmt.Errorf("Following error has been printed %d times.. %w", m[err.Error()], err))
			// Reduce the count to introduce further delay in printing
			// but let it again print after the 2th attempt
			m[err.Error()]--
			m[err.Error()]--
		}
		m[err.Error()]++
	}
}()

	onlineDisks = make([]StorageAPI, len(disks))

	// List all the file commit ids from parts metadata.
	modTimes := listObjectModtimes(partsMetadata, errs)

	// Reduce list of UUIDs to a single common value.
	modTime = commonTime(modTimes, quorum)

	if modTime.IsZero() || modTime.Equal(timeSentinel) {
		etags := listObjectETags(partsMetadata, errs, quorum)

 *       hand, is multiple-use, and does implement {@link Iterable}.
 *   <li>Streams offer many features not found here, including {@code min/max}, {@code distinct},
 *       {@code reduce}, {@code sorted}, the very powerful {@code collect}, and built-in support for
 *       parallelizing stream operations.
 *   <li>{@code FluentIterable} contains several features not available on {@code Stream}, which are