.addEqualityGroup(isNull)
        .addEqualityGroup(Equivalence.identity().equivalentTo("1"))
        .testEquals();
  }

  /*
   * We use large numbers to avoid the integer cache. Normally, we'd accomplish that merely by using
   * `new Integer` (as we do) instead of `Integer.valueOf`. However, under J2KT, `new Integer`

        // Should return uncompressed data for small inputs
        assertArrayEquals(smallData, compressed);
    }

    @Test
    @DisplayName("Test large data compression")
    public void testLargeDataCompression() throws CIFSException {
        byte[] compressed = compressionService.compress(largeTestData, CompressionService.COMPRESSION_LZ77);

      throw new SkipThisScenarioException();
    }
  }

  // This exclusion doesn't exclude the TOMBSTONE objects we set. So 'done' NEW futures will look
  // larger than they are.
  @SuppressWarnings("FutureReturnValueIgnored")
  @Footprint(exclude = {Runnable.class, Executor.class, Thread.class, Exception.class})
  public Object measureSize() {
    for (Thread thread : blockedThreads) {

## Installer `pwdlib` { #install-pwdlib }

pwdlib est un excellent package Python pour gérer les hachages de mots de passe.

Il prend en charge de nombreux algorithmes de hachage sécurisés et des utilitaires pour travailler avec eux.

L'algorithme recommandé est « Argon2 ».

          sink.writeUtf8("def")
        } catch (e: InterruptedException) {
          throw InterruptedIOException()
        }
      }
    }

  companion object {
    /** A large response body. Smaller bodies might successfully read after the socket is closed!  */
    private val BIG_ENOUGH_BODY = repeat('a', 64 * 1024)
  }

                        IllegalArgumentException.class),

                // Name length larger than remaining bytes - use method reference
                Arguments.of("name length exceeds remaining", (java.util.function.Supplier<byte[]>) () -> {
                    byte[] buf = buildBuffer(der, nameBytes);
                    // Corrupt NAME_LEN to be larger than actual by +5
                    int i = 2 + 2 + der.length; // index where NAME_LEN starts

        assertEquals(-1, request.threshold());
    }

    @Test
    public void testThresholdWithLargeValue() {
        CurlRequest request = new CurlRequest(Method.GET, "https://example.com");

        // Large threshold value
        int largeThreshold = Integer.MAX_VALUE;
        request.threshold(largeThreshold);

        assertEquals(largeThreshold, request.threshold());
    }

    @Test

            sb.setLength(0); // Reset length
        }
        return sb;
    }

    private void returnStringBuilder(StringBuilder sb) {
        if (sb != null && sb.capacity() < 2048) { // Avoid keeping very large builders
            stringBuilderPool.offer(sb);
        }
    }

    private Map<String, Object> getContextMap() {
        HashMap<String, Object> map = mapPool.poll();
        if (map == null) {

 * features}, the features supported by the iterator; and {@code expectedElements}, the elements the
 * iterator should return in order.
 *
 * <p>The items in {@code elementsToInsert} will be repeated if {@code steps} is larger than the
 * number of provided elements.
 *
 * @author Chris Povirk
 */
@GwtCompatible
@NullMarked
public abstract class ListIteratorTester<E extends @Nullable Object>

            }
        }
        return documentItems;
    }

    /**
     * Performs a scroll search for processing large result sets efficiently.
     *
     * This method uses OpenSearch scroll API to iterate through large numbers of
     * documents without loading them all into memory at once.
     *
     * @param params The search request parameters