public void testExpectedFpp() {
    BloomFilter<Object> bf = BloomFilter.create(HashTestUtils.BAD_FUNNEL, 10, 0.03);
    double fpp = bf.expectedFpp();
    assertThat(fpp).isEqualTo(0.0);
    // usually completed in less than 200 iterations
    while (fpp != 1.0) {
      boolean changed = bf.put(new Object());
      double newFpp = bf.expectedFpp();
      // if changed, the new fpp is strictly higher, otherwise it is the same

import org.codelibs.core.CoreLibConstants;
import org.codelibs.fess.suggest.Suggester;
import org.codelibs.fess.suggest.converter.ReadingConverter;
import org.codelibs.fess.suggest.entity.SuggestItem;
import org.codelibs.fess.suggest.exception.SuggesterException;
import org.codelibs.fess.suggest.normalizer.Normalizer;
import org.codelibs.fess.suggest.settings.AnalyzerSettings;
import org.codelibs.fess.suggest.settings.SuggestSettings;

   * This is December 31, 9999 if the cookie is not [persistent], in which case it will expire at the
   * end of the current session.
   *
   * This may return a value less than the current time, in which case the cookie is already
   * expired. Webservers may return expired cookies as a mechanism to delete previously set cookies
   * that may or may not themselves be expired.
   */

	dataUsageUpdateDirCycles         = 16                               // Visit all folders every n cycles.
	dataScannerCompactLeastObject    = 500                              // Compact when there is less than this many objects in a branch.
	dataScannerCompactAtChildren     = 10000                            // Compact when there are this many children in a branch.

import org.codelibs.core.stream.StreamUtil;
import org.codelibs.fess.Constants;
import org.codelibs.fess.entity.FacetInfo;
import org.codelibs.fess.entity.GeoInfo;
import org.codelibs.fess.entity.HighlightInfo;
import org.codelibs.fess.entity.SearchRequestParams;
import org.codelibs.fess.exception.InvalidQueryException;
import org.codelibs.fess.exception.ResultOffsetExceededException;
import org.codelibs.fess.mylasta.action.FessUserBean;

    assertThat(cache.getUnchecked("b")).isEqualTo("b");
  }

  // "Basher tests", where we throw a bunch of stuff at a LoadingCache and check basic invariants.

  /**
   * This is a less carefully-controlled version of {@link #testRemovalNotification_clear} - this is
   * a black-box test that tries to create lots of different thread-interleavings, and asserts that

@DoNotMock("Use FluentFuture.from(Futures.immediate*Future) or SettableFuture")
@GwtCompatible
public abstract class FluentFuture<V extends @Nullable Object>
    extends GwtFluentFutureCatchingSpecialization<V> {

  /**
   * A less abstract subclass of AbstractFuture. This can be used to optimize setFuture by ensuring
   * that {@link #get} calls exactly the implementation of {@link AbstractFuture#get}.
   */

    assertThat(cache.getUnchecked("b")).isEqualTo("b");
  }

  // "Basher tests", where we throw a bunch of stuff at a LoadingCache and check basic invariants.

  /**
   * This is a less carefully-controlled version of {@link #testRemovalNotification_clear} - this is
   * a black-box test that tries to create lots of different thread-interleavings, and asserts that

    if (writerTask != null) {
      taskQueue.schedule(writerTask)
    }
  }

  /**
   * Attempts to remove a single frame from a queue and send it. This prefers to write urgent pongs
   * before less urgent messages and close frames. For example, it's possible that a caller will
   * enqueue messages followed by pongs, but this sends pongs followed by messages. Pongs are always
   * written in the order they were enqueued.
   *

An interesting detail is that the percentage of the **CPU used** by each process can **vary** a lot over time, but the **memory (RAM)** normally stays more or less **stable**.

If you have an API that does a comparable amount of computations every time and you have a lot of clients, then the **CPU utilization** will probably *also be stable* (instead of constantly going up and down quickly).