}

  @SuppressWarnings("unchecked") // Safe because we only cast if key is found in map.
  @Override
  @Nullable V get(Object key) {
    checkNotNull(key);
    V value = getIfCached(key);
    if (value != null) {
      return value;
    }

    value = getWithoutCaching(key);
    if (value != null) {
      addToCache((K) key, value);
    }
    return value;
  }

   * Multimap#asMap} view determines the ordering in which data is written to the stream.
   *
   * <p>The serialized output consists of the number of distinct keys, and then for each distinct
   * key: the key, the number of values for that key, and the key's values.
   */
  static <K extends @Nullable Object, V extends @Nullable Object> void writeMultimap(

    /*
     * Accepts key multiple of 7
     * Returns enc multiple of 8
     * Multiple is the same like: 21 byte key gives 24 byte result
     */
    static void E(final byte[] key, final byte[] data, final byte[] e) throws ShortBufferException {
        final byte[] key7 = new byte[7];
        final byte[] e8 = new byte[8];

        for (int i = 0; i < key.length / 7; i++) {

    for (K key : multimap().keySet()) {
      assertTrue(multimap().asMap().get(key) instanceof List);
    }
  }

  @MapFeature.Require(SUPPORTS_REMOVE)
  public void testAsMapRemoveImplementsList() {
    List<K> keys = new ArrayList<>(multimap().keySet());
    for (K key : keys) {
      resetCollection();
      assertTrue(multimap().asMap().remove(key) instanceof List);
    }
  }

    for (K key : multimap().keySet()) {
      assertTrue(multimap().asMap().get(key) instanceof List);
    }
  }

  @MapFeature.Require(SUPPORTS_REMOVE)
  public void testAsMapRemoveImplementsList() {
    List<K> keys = new ArrayList<>(multimap().keySet());
    for (K key : keys) {
      resetCollection();
      assertTrue(multimap().asMap().remove(key) instanceof List);
    }
  }

   * remove()}. Otherwise, all optional operations are supported. Null row keys, columns keys, and
   * values are not supported.
   *
   * <p>Lookups by row key are often faster than lookups by column key, because the data is stored
   * in a {@code Map<R, Map<C, V>>}. A method call like {@code column(columnKey).get(rowKey)} still
   * runs quickly, since the row key is provided. However, {@code column(columnKey).size()} takes

 * Null row keys, columns keys, and values are not supported.
 *
 * <p>Lookups by row key are often faster than lookups by column key, because the data is stored in
 * a {@code Map<R, Map<C, V>>}. A method call like {@code column(columnKey).get(rowKey)} still runs
 * quickly, since the row key is provided. However, {@code column(columnKey).size()} takes longer,
 * since an iteration across all row keys occurs.
 *

     */
    public static <KEY, VALUE> Maps<KEY, VALUE> hashMap(final KEY key, final VALUE value) {
        return new Maps<>(new HashMap<KEY, VALUE>()).$(key, value);
    }

    /**
     * Returns a {@literal Maps} for constructing a {@link Hashtable} with the specified key and value.
     *
     * @param <KEY> the key type of the <code>Map</code>

        if (valueItr == null) {
          valueIterators.put(key, valueItr = sampleValuesIterator());
        }
        entries[i] = mapEntry(key, valueItr.next());
      }
      return multimapGenerator.create((Object[]) entries).keys();
    }

    private Iterator<V> sampleValuesIterator() {
      return ((TestMultimapGenerator<K, V, M>) multimapGenerator.getInnerGenerator())
          .sampleValues()

    }

    /** Case 5: Overwrite processing for multiple fields, existing overwrite keys are also properly removed */
    public void test_mergeResponseData_multipleOverwrite() {
        Map<String, Object> dataMap = new HashMap<>();
        // Case where the initial dataMap also contains overwrite keys
        dataMap.put("m", "M0");
        dataMap.put("n.overwrite", "N0_old");