/** Raw mode capability */
    int CAP_RAW_MODE = 0x0001;
    /** MPX mode capability */
    int CAP_MPX_MODE = 0x0002;
    /** Unicode capability */
    int CAP_UNICODE = 0x0004;
    /** Large files capability */
    int CAP_LARGE_FILES = 0x0008;
    /** NT SMBs capability */
    int CAP_NT_SMBS = 0x0010;
    /** RPC remote APIs capability */
    int CAP_RPC_REMOTE_APIS = 0x0020;

    void testDataHandlingWithVariousSizes() {
        // Test with small data count
        response.setDataCount(10);
        assertEquals(10, response.getDataCount());

        // Test with large data count
        response.setDataCount(65535);
        assertEquals(65535, response.getDataCount());

        // Test with zero data count
        response.setDataCount(0);

         * than a handful of exceptions. But it seems prudent to set a cap on how many we'll cache.
         * This avoids out-of-control memory consumption, and it keeps the cache from growing so
         * large that doing the lookup is noticeably slower than redoing the work would be.
         *
         * Ideally we'd have a real eviction policy, but until we see a problem in practice, I hope

   * safe range. If {@code safeMax < safeMin} then no code points are considered safe. This
   * initializer is useful when explicit instances of ArrayBasedEscaperMap are used to allow the
   * sharing of large replacement mappings.
   *
   * <p>If a code point has no mapped replacement then it is checked against the safe range. If it
   * lies outside that, then {@link #escapeUnsafe} is called, otherwise no escaping is performed.
   *

 * @since 13.0
 */
@J2ktIncompatible
@GwtIncompatible
public abstract class Striped<L> {
  /**
   * If there are at least this many stripes, we assume the memory usage of a ConcurrentMap will be
   * smaller than a large array. (This assumes that in the lazy case, most stripes are unused. As
   * always, if many stripes are in use, a non-lazy striped makes more sense.)
   */
  private static final int LARGE_LAZY_CUTOFF = 1024;

/**
 * <p>
 * {@link ESSourceReader} reads documents from Elasticsearch using the scroll API.
 * It implements the {@link DocumentReader} interface to provide a way to iterate over documents
 * in a large index without loading all of them into memory at once.
 * </p>
 *
 * <p>
 * The reader supports limiting the number of documents read based on a percentage of the total documents

// A chunk has the following format:
//
//	<chunk-size-as-hex> + ";chunk-signature=" + <signature-as-hex> + "\r\n" + <payload> + "\r\n"
//
// First, we read the chunk size but fail if it is larger
// than 16 MiB. We must not accept arbitrary large chunks.
// One 16 MiB is a reasonable max limit.
//
// Then we read the signature and payload data. We compute the SHA256 checksum

    bytesIn.writeShort(0xff00) // == Indexed - Add idx = 127
    assertFailsWith<IOException> {
      hpackReader!!.readHeaders()
    }.also { expected ->
      assertThat(expected.message).isEqualTo("Header index too large 127")
    }
  }

  // Example taken from twitter/hpack DecoderTest.testInsidiousIndex
  @Test
  fun readIndexedHeaderFieldInsidiousIndex() {
    bytesIn.writeByte(0xff) // == Indexed - Add ==

        }

        // Test boundary values
        assertEquals("1bytes", MemoryUtil.byteCountToDisplaySize(1L));
        assertEquals("999bytes", MemoryUtil.byteCountToDisplaySize(999L));

        // Test very large values close to EB boundary
        assertEquals("1.024EB", MemoryUtil.byteCountToDisplaySize(FileUtils.ONE_EB));

        // Test exact thresholds
        assertEquals("1.024KB", MemoryUtil.byteCountToDisplaySize(1024L));

        assertTrue(negInfinityOpt.isPresent());
        assertTrue(Float.isInfinite(negInfinityOpt.get()));

        // Test with very large strings
        StringBuilder largeString = new StringBuilder();
        for (int i = 0; i < 10000; i++) {
            largeString.append("x");
        }