new FunctionScoreQueryBuilder.FilterFunctionBuilder[] { new FunctionScoreQueryBuilder.FilterFunctionBuilder(
                                    new RandomScoreFunctionBuilder().seed(sessionId.hashCode())) }),
                    0, pollingFetchSize, SortBuilders.scoreSort().order(SortOrder.DESC));
        } else if (!ORDER_SEQUENTIAL.equals(crawlOrder)) {

  }

  interface HashFn {
    byte[] hash(byte[] input, int seed);
  }

  static void verifyHashFunction(HashFn hashFunction, int hashbits, int expected) {
    int hashBytes = hashbits / 8;

    byte[] key = new byte[256];
    byte[] hashes = new byte[hashBytes * 256];

    // Hash keys of the form {}, {0}, {0,1}, {0,1,2}... up to N=255,using 256-N as the seed
    for (int i = 0; i < 256; i++) {
      key[i] = (byte) i;

  }

  interface HashFn {
    byte[] hash(byte[] input, int seed);
  }

  static void verifyHashFunction(HashFn hashFunction, int hashbits, int expected) {
    int hashBytes = hashbits / 8;

    byte[] key = new byte[256];
    byte[] hashes = new byte[hashBytes * 256];

    // Hash keys of the form {}, {0}, {0,1}, {0,1,2}... up to N=255,using 256-N as the seed
    for (int i = 0; i < 256; i++) {
      key[i] = (byte) i;

You also get error checks for incorrect type operations:

<img src="/img/tutorial/body/image04.png">

This is not by chance, the whole framework was built around that design.

And it was thoroughly tested at the design phase, before any implementation, to ensure it would work with all the editors.

There were even some changes to Pydantic itself to support this.

    - tutorial/path-params-numeric-validations.md
    - tutorial/query-param-models.md
    - tutorial/body-multiple-params.md
    - tutorial/body-fields.md
    - tutorial/body-nested-models.md
    - tutorial/schema-extra-example.md
    - tutorial/extra-data-types.md
    - tutorial/cookie-params.md
    - tutorial/header-params.md
    - tutorial/cookie-param-models.md

				continue
			}
			// check the doc https://docs.aws.amazon.com/AmazonS3/latest/userguide/UsingMetadata.html
			// For metadata values like "ö", "ÄMÄZÕÑ S3", and "öha, das sollte eigentlich
			// funktionieren", tested against a real AWS S3 bucket, S3 may encode incorrectly. For
			// example, "ö" was encoded as =?UTF-8?B?w4PCtg==?=, producing invalid UTF-8 instead
			// of =?UTF-8?B?w7Y=?=. This mirrors errors like the ä½ in another string.

    LoadingCache<String, String> cache =
        CacheBuilder.newBuilder()
            .concurrencyLevel(1)
            .removalListener(listener)
            .build(computingFunction);

    // seed the map, so its segment's count > 0
    cache.getUnchecked("a");
    shouldWait.set(true);

    CountDownLatch computationStarted = new CountDownLatch(1);
    CountDownLatch computationComplete = new CountDownLatch(1);

A group's DN may be associated with an [access policy](#managing-usergroup-access-policy).

#### Nested groups usage in LDAP/AD
If you are using Active directory with nested groups you have to add LDAP_MATCHING_RULE_IN_CHAIN: :1.2.840.113556.1.4.1941: to your query.
For example:
```shell

 *
 * This class provides methods to normalize text by reading characters from a provided Reader
 * and processing them according to specific rules. The main functionality is encapsulated
 * within the nested {@link TextNormalizeContext} class.
 *
 * <p>The text normalization process includes:
 * <ul>
 *   <li>Treating ISO control characters and specified space characters as spaces.</li>

		}
		// uploadIds [4-9].
		uploadIDs = append(uploadIDs, res.UploadID)
	}
	// Create multipart parts.
	// Need parts to be uploaded before MultipartLists can be called and tested.
	createPartCases := []struct {
		bucketName      string
		objName         string
		uploadID        string
		PartID          int
		inputReaderData string
		inputMd5        string
		inputDataSize   int64