Entry<K, V> entry = iterator.next();
      Entry<K, V> entryCopy = mapEntry(entry.getKey(), entry.getValue());

      iterator.remove();
      assertEquals(initialSize - 1, map.size());

      // Use "entryCopy" instead of "entry" because "entry" might be invalidated after
      // iterator.remove().
      assertFalse(entrySet.contains(entryCopy));
      assertInvariants(map);

        }

        // Simple heuristic based on data entropy
        // In practice, this would be more sophisticated
        int uniqueBytes = countUniqueBytes(data);
        double entropy = (double) uniqueBytes / 256.0;

        // Estimate compression ratio based on entropy
        // Lower entropy = better compression
        return 0.3 + (entropy * 0.6); // Range from 30% to 90%
    }

    @Override

      -1

      """.trimIndent()
    val entryBody = "abc"
    val journalBody = """libcore.io.DiskLruCache
1
201105
2

CLEAN $urlKey ${entryMetadata.length} ${entryBody.length}
"""
    fileSystem.createDirectory(cache.directoryPath)
    writeFile(cache.directoryPath, "$urlKey.0", entryMetadata)
    writeFile(cache.directoryPath, "$urlKey.1", entryBody)

            uniqueCounters.add(bytesToHex(counter));
        }

        // All nonces should be unique (high entropy from SecureRandom)
        assertEquals(sampleSize, uniqueCounters.size(), "All nonces should have unique values");

        // Verify that nonces have good entropy (not predictable)
        // With SecureRandom + counter XOR, they should all be different
        Set<String> uniqueNonces = new HashSet<>();

        `tf.initializers = tf.keras.initializers` & `tf.optimizers =
        tf.keras.optimizers`.
    *   Updates binary cross entropy logic in Keras when input is probabilities.
        Instead of converting probabilities to logits, we are using the cross
        entropy formula for probabilities.
    *   Added public APIs for `cumsum` and `cumprod` keras backend functions.

// At every read, 128 random bits from the operating system are mixed as // additional input, to make the output as strong as non-FIPS randomness. // This is not credited as entropy for FIPS purposes, as allowed by Section // 8.7.2: "Note that a DRBG does not rely on additional input to provide // entropy, even though entropy could be provided in the additional input". additionalInput := new([SeedSize]byte) sysrand.Read(additionalInput[:16]) drbg := drbgs.Get().(*Counter) defer drbgs.Put(drbg) for...