byte[] buffer1 = new byte[256];
        byte[] buffer2 = new byte[256];

        // When
        int bytes1 = request.writeBytesWireFormat(buffer1, 0);
        int bytes2 = request.writeBytesWireFormat(buffer2, 10);

        // Then
        assertEquals(bytes1, bytes2);
        assertEquals(SMBUtil.readInt2(buffer1, 0), SMBUtil.readInt2(buffer2, 10));
    }

    @Test

            byte[] buffer1 = new byte[100];
            byte[] buffer2 = new byte[200];

            Arrays.fill(buffer1, (byte) 0x11);
            Arrays.fill(buffer2, (byte) 0x22);

            // First decode
            response.decode(buffer1, 0, 50);
            byte[] data1 = response.getData();

            // Second decode should overwrite
            response.decode(buffer2, 10, 60);

            byte[] buffer = new byte[512];

            int bytesWritten = req.writeBytesWireFormat(buffer, 0);

            assertEquals(48, SMBUtil.readInt2(buffer, 0)); // Structure size
            assertEquals(3, SMBUtil.readInt2(buffer, 2)); // Lock count
            assertArrayEquals(testFileId, Arrays.copyOfRange(buffer, 8, 24));

            // Each lock is 24 bytes

    void testMultipleReadsUpdateOffset() {
        byte[] buffer1 = new byte[] { 0x10, 0x00, 0x00, 0x00 }; // 16
        byte[] buffer2 = new byte[] { 0x20, 0x00, 0x00, 0x00 }; // 32

        response.readParameterWordsWireFormat(buffer1, 0);
        assertEquals(16L, response.getOffset(), "First read should set offset to 16");

        response.readParameterWordsWireFormat(buffer2, 0);

internal fun idnToAscii(host: String): String? {
  val bufferA = Buffer().writeUtf8(host)
  val bufferB = Buffer()

  // 1. Map, from bufferA to bufferB.
  while (!bufferA.exhausted()) {
    val codePoint = bufferA.readUtf8CodePoint()
    if (!IDNA_MAPPING_TABLE.map(codePoint, bufferB)) return null
  }

  // 2. Normalize, from bufferB to bufferA.
  val normalized = normalizeNfc(bufferB.readUtf8())
  bufferA.writeUtf8(normalized)

    memory usage.
*   Fixed bfloat16 integration of LIBXSMM sparse mat-mul.
*   Improved performance and reduce memory usage by allowing ops to forward
    input buffers to output buffers and perform computations in-place.
*   Improved the performance of CPU assignment for strings.
*   Speed up matrix * vector multiplication and matrix * matrix with unknown
    shapes.

            NdrShort ndrShort = new NdrShort(50);
            NdrBuffer buffer1 = mock(NdrBuffer.class);
            NdrBuffer buffer2 = mock(NdrBuffer.class);
            when(buffer2.dec_ndr_short()).thenReturn(75);

            // When: Performing multiple operations
            ndrShort.encode(buffer1);
            ndrShort.decode(buffer2);

            // Then: Should handle both operations correctly

concurrent-burgers-03.png...

parallel-burgers-06.png...

concurrent-burgers-01.png...