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

- Run MinIO with a single secret key. MinIO supports a static cryptographic key
  that can act as minimal KMS. With this method all IAM data will be stored
  encrypted. The encryption key has to be passed as environment variable.
- Run MinIO with KES (minio/kes) in combination with any supported KMS as
  secure key store. For example, you can run MinIO + KES + Hashicorp Vault.

     * Constructs KerberosRelevantAuthData from token bytes.
     *
     * @param token the authorization data token
     * @param keys map of Kerberos keys indexed by key type
     * @throws PACDecodingException if decoding fails
     */
    public KerberosRelevantAuthData(byte[] token, Map<Integer, KerberosKey> keys) throws PACDecodingException {
        ASN1Sequence authSequence;
        try {

        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()

 * 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.
 *

	// after which listing should begin.
	KeyMarker string

	// Together with key-marker, specifies the multipart upload after which listing
	// should begin. If key-marker is not specified, the upload-id-marker parameter
	// is ignored.
	UploadIDMarker string

	// When a list is truncated, this element specifies the value that should be
	// used for the key-marker request parameter in a subsequent request.
	NextKeyMarker string

P8_STXVB16X(IVEC, IVP, R0) CLEAR_KEYS() RET #define DO1_CIPHER(iv0, keyv, key, op) \ LXVD2X (key), keyv \ ADD $16, key \ op iv0, keyv, iv0 #define DO2_CIPHER(iv0, iv1, keyv, key, op) \ DO1_CIPHER(iv0, keyv, key, op) \ op iv1, keyv, iv1 #define DO4_CIPHER(iv0, iv1, iv2, iv3, keyv, key, op) \ DO2_CIPHER(iv0, iv1, keyv, key, op) \ op iv2, keyv, iv2 \ op iv3, keyv, iv3 #define DO8_CIPHER(iv0, iv1, iv2, iv3, iv4, iv5, iv6, iv7, keyv, key, op) \ DO4_CIPHER(iv0, iv1, iv2, iv3, keyv, key, op) \ op iv4, keyv,...

            }
        }

        return serverKeys.toArray(new KerberosKey[0]);
    }

    /**
     * Retrieves a specific Kerberos key by key type.
     *
     * @param keyType the encryption type of the key to retrieve
     * @return the KerberosKey with the specified type, or null if not found
     */
    public KerberosKey getKey(int keyType) {
        KerberosKey serverKey = null;

    }

    /** 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");