/* HMACT64 keyed hashing algorithm
 * Copyright (C) 2003 "Eric Glass" <jcifs at samba dot org>
 *
 * This library is free software; you can redistribute it and/or
 * modify it under the terms of the GNU Lesser General Public
 * License as published by the Free Software Foundation; either
 * version 2.1 of the License, or (at your option) any later version.
 *
 * This library is distributed in the hope that it will be useful,

		Metadata:         nil,
		Parts:            nil,
		Erasure: ErasureInfo{
			Algorithm:    ReedSolomon.String(),
			DataBlocks:   4,
			ParityBlocks: 2,
			BlockSize:    10000,
			Index:        1,
			Distribution: []int{1, 2, 3, 4, 5, 6, 7, 8},
			Checksums: []ChecksumInfo{{
				PartNumber: 1,
				Algorithm:  HighwayHash256S,
				Hash:       nil,
			}},
		},
		MarkDeleted:      false,

    /**
     * Store a session key
     *
     * @param sessionId unique session identifier
     * @param key the secret key to store
     * @param algorithm the key algorithm (e.g., "AES")
     */
    public void storeSessionKey(String sessionId, byte[] key, String algorithm) {
        checkNotClosed();

        if (key == null || sessionId == null) {
            throw new IllegalArgumentException("Session ID and key must not be null");

	// formatErasureV3.Erasure.Version - version '3'.
	formatErasureVersionV3 = "3"

	// Distribution algorithm used, legacy
	formatErasureVersionV2DistributionAlgoV1 = "CRCMOD"

	// Distributed algorithm used, with N/2 default parity
	formatErasureVersionV3DistributionAlgoV2 = "SIPMOD"

	// Distributed algorithm used, with EC:4 default parity
	formatErasureVersionV3DistributionAlgoV3 = "SIPMOD+PARITY"
)

  double median(int reps) {
    double dummy = 0.0;
    for (int i = 0; i < reps; i++) {
      dummy += algorithm.singleQuantile(1, 2, dataset(i));
    }
    return dummy;
  }

  @Benchmark
  double percentile90(int reps) {
    double dummy = 0.0;
    for (int i = 0; i < reps; i++) {
      dummy += algorithm.singleQuantile(90, 100, dataset(i));
    }
    return dummy;
  }

  @Benchmark

  double median(int reps) {
    double dummy = 0.0;
    for (int i = 0; i < reps; i++) {
      dummy += algorithm.singleQuantile(1, 2, dataset(i));
    }
    return dummy;
  }

  @Benchmark
  double percentile90(int reps) {
    double dummy = 0.0;
    for (int i = 0; i < reps; i++) {
      dummy += algorithm.singleQuantile(90, 100, dataset(i));
    }
    return dummy;
  }

  @Benchmark

    private static final byte[] ZERO_IV = { 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 };

    /**
     * Calculates a MAC using the ARCFOUR-HMAC-MD5 algorithm.
     * This method implements the Microsoft variant of the Kerberos ARCFOUR-HMAC-MD5 checksum.
     *
     * @param keyusage the Kerberos key usage number for this operation

    val responseString = decompressed.body.string()
    assertThat(responseString).isEqualTo("hello not compressed world")
  }

  @Test
  fun testUnknownAlgorithm() {
    val s = "hello unknown algorithm world".encodeUtf8()

    val response =
      response("https://example.com/", s) {
        header("Content-Encoding", "deflate")
      }

    val decompressed = zstdInterceptor.decompress(response)

		return ErrDecrypt
	}
	if len(value.Nonce) != NonceSize {
		return ErrDecrypt
	}

	switch value.Algorithm {
	case AES256GCM:
		c.Algorithm = kms.AES256
	case CHACHA20POLY1305:
		c.Algorithm = kms.ChaCha20
	default:
		c.Algorithm = 0
	}
	c.ID = value.ID
	c.IV = value.IV
	c.Nonce = value.Nonce
	c.Bytes = value.Bytes
	return nil

        assertEquals("Missing key", e.getMessage());
    }

    /**
     * Test calculateMac with an invalid algorithm type.
     */
    @Test
    void testCalculateMacInvalidAlgorithm() {
        Map<Integer, KerberosKey> keys = new HashMap<>();