.createTestSuite();
  }

  // We are testing Vector / testing our tests on Vector.
  @SuppressWarnings("JdkObsolete")
  private Test testsForVector() {
    return ListTestSuiteBuilder.using(
            new TestStringListGenerator() {
              @Override
              protected List<String> create(String[] elements) {
                return new Vector<>(MinimalCollection.of(elements));
              }
            })

     */
    @Override
    public Settings settings() {
        return client.settings();
    }

    /**
     * Gets term vectors for a document asynchronously.
     *
     * @param request the term vectors request
     * @return a future for the term vectors response
     */
    @Override
    public ActionFuture<TermVectorsResponse> termVectors(final TermVectorsRequest request) {

            for (i in 2..997) {
              sink.writeUtf8(String.format(" * $i = ${factor(i)}\n"))
            }
          }

          private fun factor(n: Int): String {
            for (i in 2 until n) {
              val x = n / i
              if (x * i == n) return "${factor(x)} × $i"
            }
            return n.toString()
          }
        }

   */
  public long approximateElementCount() {
    long bitSize = bits.bitSize();
    long bitCount = bits.bitCount();

    /*
     * Each insertion is expected to reduce the # of clear bits by a factor of
     * `numHashFunctions/bitSize`. So, after n insertions, expected bitCount is `bitSize * (1 - (1 -
     * numHashFunctions/bitSize)^n)`. Solving that for n, and approximating `ln x` as `x - 1` when x