//    second thread can then dispatch to the subscriber it took before the first thread does.
    //
    // All this makes me really wonder if there's any value in queueing here at all. A dispatcher
    // that simply loops through the subscribers and dispatches the event to each would actually
    // probably provide a stronger order guarantee, though that order would obviously be different
    // in some cases.

    /** Global event queue. */

		{256},
		{512},
		{1024},
	}
	for _, testCase := range cases {
		key := randString(testCase.key)
		b.Run("", func(b *testing.B) {
			b.SetBytes(1024)
			b.ReportAllocs()
			b.ResetTimer()
			for b.Loop() {
				crcHashMod(key, 16)
			}
		})
	}
}

func BenchmarkSipHash(b *testing.B) {
	cases := []struct {
		key int
	}{
		{16},
		{64},
		{128},
		{256},
		{512},
		{1024},
	}

		// will keep performing the callhome. If the leader goes down for some reason,
		// the lock will be released and another node will acquire it and take over
		// because of this loop.
		for {
			if !globalCallhomeConfig.Enabled() {
				return
			}

			if !runCallhome(ctx, objAPI) {
				// callhome was disabled or context was canceled
				return
			}

        int result = response.readBytesWireFormat(buffer, bufferIndex);

        assertEquals(8, result);
        assertNotNull(response.getResults());
        // Even with -1, the do-while loop executes at least once due to the bug
        assertEquals(1, response.getResults().length);
    }

    @Test
    @DisplayName("Test readBytesWireFormat with offset calculation")

   *   <li>{@code ImmutableList.of(2, "C")}
   * </ul>
   *
   * <p>The result is guaranteed to be in the "traditional", lexicographical order for Cartesian
   * products that you would get from nesting for loops:
   *
   * {@snippet :
   * for (B b0 : lists.get(0)) {
   *   for (B b1 : lists.get(1)) {
   *     ...
   *     ImmutableList<B> tuple = ImmutableList.of(b0, b1, ...);
   *     // operate on tuple
   *   }

      TF_GUARDED_BY(mu);
  bool delete_requested TF_GUARDED_BY(mu);  // set true by TF_DeleteGraph

  // Used to link graphs contained in TF_WhileParams to the parent graph that
  // will eventually contain the full while loop.
  TF_Graph* parent;
  TF_Output* parent_inputs;
};

struct TF_OperationDescription {
  TF_OperationDescription(TF_Graph* g, const char* op_type,
                          const char* node_name)

		b.ReportAllocs()
		b.ResetTimer()
		b.SetBytes(855) // number of versions...
		for b.Loop() {
			mergeXLV2Versions(8, false, 0, vers...)
		}
	})

	b.Run("requested-v1", func(b *testing.B) {
		b.ReportAllocs()
		b.ResetTimer()
		b.SetBytes(855) // number of versions...
		for b.Loop() {
			mergeXLV2Versions(8, false, 1, vers...)
		}
	})

	b.Run("requested-v2", func(b *testing.B) {

        when(mockReferral.getPathConsumed()).thenReturn(15); // e.g., "\\\\server\\share".length()
        when(mockReferral.next()).thenReturn(mockReferral); // Simple loop for the do-while
        assertDoesNotThrow(() -> dfsImpl.cache(mockContext, "\\\\server\\share\\path", mockReferral));
    }

        assertEquals(initialReferral, appendedReferral.next,
                "The 'next' property of the appended referral should point back to the initial referral, closing the loop.");
    }

    /**
     * Tests the toString method of the DfsReferral class.
     * It verifies that the toString method returns a string representation of the object
     * that accurately reflects its properties.

	sha256hex := ""

	// benchmark utility which helps obtain number of allocations and bytes allocated per ops.
	b.ReportAllocs()
	// the actual benchmark for PutObject starts here. Reset the benchmark timer.

	for i := 0; b.Loop(); i++ {
		// insert the object.
		objInfo, err := obj.PutObject(b.Context(), bucket, "object"+strconv.Itoa(i),
			mustGetPutObjReader(b, bytes.NewReader(textData), int64(len(textData)), md5hex, sha256hex), ObjectOptions{})