features down to compact but powerful abstractions, and controlling feature bloat carefully.


        Guava's main yardstick for evaluating proposed features can be summed up as [utility times
        ubiquity](https://github.com/google/guava/wiki/PhilosophyExplained#utility-times-ubiquity).


        #### Utility: compare with alternatives

   * @param values the values to use when constructing the {@code ImmutableListMultimap}
   * @param keyFunction the function used to produce the key for each value
   * @return {@code ImmutableListMultimap} mapping the result of evaluating the function {@code
   *     keyFunction} on each value in the input collection to that value
   * @throws NullPointerException if any element of {@code values} is {@code null}, or if {@code

   * stream.collect(ImmutableMap.toImmutableMap(keyFunction, v -> v))}.
   *
   * @param keyFunction the function used to produce the key for each value
   * @return a map mapping the result of evaluating the function {@code keyFunction} on each value
   *     in this fluent iterable to that value
   * @throws IllegalArgumentException if {@code keyFunction} produces the same key for more than one

 * is less error-prone and more readable than code using {@code ReentrantLock}, without significant
 * performance loss. {@code Monitor} even has the potential for performance gain by optimizing the
 * evaluation and signaling of conditions. Signaling is entirely <a
 * href="http://en.wikipedia.org/wiki/Monitor_(synchronization)#Implicit_signaling">implicit</a>. By

   */
  @ForOverride
  protected abstract int doHash(T t);

  /**
   * Returns a new equivalence relation for {@code F} which evaluates equivalence by first applying
   * {@code function} to the argument, then evaluating using {@code this}. That is, for any pair of
   * non-null objects {@code x} and {@code y}, {@code equivalence.onResultOf(function).equivalent(a,

   */
  @ForOverride
  protected abstract int doHash(T t);

  /**
   * Returns a new equivalence relation for {@code F} which evaluates equivalence by first applying
   * {@code function} to the argument, then evaluating using {@code this}. That is, for any pair of
   * non-null objects {@code x} and {@code y}, {@code equivalence.onResultOf(function).equivalent(a,

   *
   * @param values the values to use when constructing the {@code Map}
   * @param keyFunction the function used to produce the key for each value
   * @return a map mapping the result of evaluating the function {@code keyFunction} on each value
   *     in the input collection to that value
   * @throws IllegalArgumentException if {@code keyFunction} produces the same key for more than one

    return new NotPredicate<>(predicate);
  }

  /**
   * Returns a predicate that evaluates to {@code true} if each of its components evaluates to
   * {@code true}. The components are evaluated in order, and evaluation will be "short-circuited"
   * as soon as a false predicate is found. It defensively copies the iterable passed in, so future
   * changes to it won't alter the behavior of this predicate. If {@code components} is empty, the

   *
   * <p><b>Note:</b> if {@code first} is represented as an {@link Optional}, this can be
   * accomplished with {@link Optional#or(Object) first.or(second)}. That approach also allows for
   * lazy evaluation of the fallback instance, using {@link Optional#or(Supplier)
   * first.or(supplier)}.
   *
   * <p><b>Java 9 users:</b> use {@code java.util.Objects.requireNonNullElse(first, second)}
   * instead.
   *

   * to be a view, but it means that the function will be applied many times for bulk operations
   * like {@link List#contains} and {@link List#hashCode}. For this to perform well, {@code
   * function} should be fast. To avoid lazy evaluation when the returned list doesn't need to be a
   * view, copy the returned list into a new list of your choosing.
   *
   * <p>If {@code fromList} implements {@link RandomAccess}, so will the returned list. The returned