* underlying model is a continuous function mapping storedPermits (from 0.0 to maxStoredPermits)
   * onto the 1/rate (i.e. intervals) that is effective at the given storedPermits. "storedPermits"
   * essentially measure unused time; we spend unused time buying/storing permits. Rate is
   * "permits / time", thus "1 / rate = time / permits". Thus, "1/rate" (time / permits) times

   * to hang (possibly too quickly, but too-quick failures should be very unlikely, given that we
   * used to bail after 20ms during the expected-successful tests, and there we saw a failure rate
   * of ~1/5000, meaning that the other thread's get() call nearly always completes within 20ms if
   * it's going to complete at all).
   *

 *       token attempt, one measure of the quality of a hash function is <i>how well</i> it succeeds
 *       at this goal. Important note: it may be easy to achieve the theoretical minimum collision
 *       rate when using completely <i>random</i> sample input. The true test of a hash function is
 *       how it performs on representative real-world data, which tends to contain many hidden

  int maximumSize;

  @Param("5000")
  int distinctKeys;

  @Param("4")
  int segments;

  // 1 means uniform likelihood of keys; higher means some keys are more popular
  // tweak this to control hit rate
  @Param("2.5")
  double concentration;

  Random random = new Random();

  LoadingCache<Integer, Integer> cache;

  int max;

  static AtomicLong requests = new AtomicLong(0);

   * out.
   */
  long timeoutMillis() {
    return SHORT_DELAY_MS / 4;
  }

  /** Returns a new Date instance representing a time delayMillis milliseconds in the future. */
  Date delayedDate(long delayMillis) {
    return new Date(System.currentTimeMillis() + delayMillis);
  }

  /** The first exception encountered if any threadAssertXXX method fails. */

    Builder<String, Integer> builder =
        new Builder<String, Integer>()
            .put("one", 1)
            .put("one", 1); // throwing on this line might be better but it's too late to change

    try {
      builder.buildOrThrow();
      fail();
    } catch (IllegalArgumentException expected) {
    }
  }

  public void testBuildKeepingLast_allowsOverwrite() {

   *
   * The Least Recently Used page replacement algorithm was chosen due to its simplicity, high hit
   * rate, and ability to be implemented with O(1) time complexity. The initial LRU implementation
   * operates per-segment rather than globally for increased implementation simplicity. We expect
   * the cache hit rate to be similar to that of a global LRU algorithm.
   */

  // Constants

  /**

   * to hang (possibly too quickly, but too-quick failures should be very unlikely, given that we
   * used to bail after 20ms during the expected-successful tests, and there we saw a failure rate
   * of ~1/5000, meaning that the other thread's get() call nearly always completes within 20ms if
   * it's going to complete at all).
   *

import com.google.common.testing.NullPointerTester;
import com.google.common.testing.TearDown;
import com.google.common.testing.TearDownStack;
import com.google.errorprone.annotations.CanIgnoreReturnValue;
import java.util.Date;
import java.util.concurrent.ArrayBlockingQueue;
import java.util.concurrent.BlockingQueue;
import java.util.concurrent.CountDownLatch;
import java.util.concurrent.ExecutorService;
import java.util.concurrent.Executors;

  int maximumSize;

  @Param("5000")
  int distinctKeys;

  @Param("4")
  int segments;

  // 1 means uniform likelihood of keys; higher means some keys are more popular
  // tweak this to control hit rate
  @Param("2.5")
  double concentration;

  Random random = new Random();

  LoadingCache<Integer, Integer> cache;

  int max;

  static AtomicLong requests = new AtomicLong(0);