* Table} interface.
 *
 * <p>The views returned by {@link #column}, {@link #columnKeySet()}, and {@link #columnMap()} have
 * iterators that don't support {@code 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

 * Table} interface.
 *
 * <p>The views returned by {@link #column}, {@link #columnKeySet()}, and {@link #columnMap()} have
 * iterators that don't support {@code 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

   * generated by applying the specified functions. If multiple inputs are mapped to the same row
   * and column pair, they will be combined with the specified merging function in encounter order.
   *
   * <p>The returned {@code Collector} will throw a {@code NullPointerException} at collection time
   * if the row, column, value, or merging functions return null on any input.
   *

   *
   * <p>The views returned by the {@code Table} methods {@link Table#column}, {@link
   * Table#columnKeySet}, and {@link Table#columnMap} have iterators that don't support {@code
   * 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

   * generated by applying the specified functions. If multiple inputs are mapped to the same row
   * and column pair, they will be combined with the specified merging function in encounter order.
   *
   * <p>The returned {@code Collector} will throw a {@code NullPointerException} at collection time
   * if the row, column, value, or merging functions return null on any input.
   *

 * 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.
 *

 *
 * <p>The allowed row and column keys must be supplied when the table is created. The table always
 * contains a mapping for every row key / column pair. The value corresponding to a given row and
 * column is null unless another value is provided.
 *
 * <p>The table's size is constant: the product of the number of supplied row keys and the number of

   * @return the corresponding map from column keys to values
   */
  Map<C, V> row(@ParametricNullness R rowKey);

  /**
   * Returns a view of all mappings that have the given column key. For each row key / column key /
   * value mapping in the table with that column key, the returned map associates the row key with
   * the value. If no mappings in the table have the provided column key, an empty map is returned.
   *

      table.put(row, 2, 'b');
    }
  }

  private static void populateForColumnKeySet(
      Table<Integer, String, Character> table, String[] elements) {
    for (String column : elements) {
      table.put(1, column, 'a');
      table.put(2, column, 'b');
    }
  }

  private static void populateForValues(
      Table<Integer, Character, String> table, String[] elements) {
    for (int i = 0; i < elements.length; i++) {

  }

  @Generates
  static <R, C, V> Table<R, C, V> generateTable(R row, C column, V value) {
    return generateHashBasedTable(row, column, value);
  }

  @Generates
  static <R, C, V> HashBasedTable<R, C, V> generateHashBasedTable(R row, C column, V value) {
    HashBasedTable<R, C, V> table = HashBasedTable.create();
    table.put(row, column, value);
    return table;
  }