}
    try {
      return fromEntryArrayCheckingBucketOverflow(n, entryArray, throwIfDuplicateKeys);
    } catch (BucketOverflowException e) {
      // probable hash flooding attack, fall back to j.u.HM based implementation and use its
      // implementation of hash flooding protection
      return JdkBackedImmutableMap.create(n, entryArray, throwIfDuplicateKeys);
    }
  }

      expandTableThreshold = (int) (DESIRED_LOAD_FACTOR * newTableSize);
    }

    /**
     * We attempt to detect deliberate hash flooding attempts. If one is detected, we fall back to a
     * wrapper around j.u.HashSet, which has built-in flooding protection. MAX_RUN_MULTIPLIER was
     * determined experimentally to match our desired probability of false positives.
     */

      case HALF_DOWN:
      case HALF_UP:
      case HALF_EVEN:
        // Since sqrt(10) is irrational, log10(x) - floorLog can never be exactly 0.5
        BigInteger x2 = x.pow(2);
        BigInteger halfPowerSquared = floorPow.pow(2).multiply(BigInteger.TEN);
        return (x2.compareTo(halfPowerSquared) <= 0) ? floorLog : floorLog + 1;
    }
    throw new AssertionError();
  }

      return LinearTransformation.vertical(xStats.mean());
    }
  }

  /**
   * {@inheritDoc}
   *
   * <p><b>Note:</b> This tests exact equality of the calculated statistics, including the floating
   * point values. Two instances are guaranteed to be considered equal if one is copied from the
   * other using {@code second = new PairedStatsAccumulator().addAll(first).snapshot()}, if both

// int64 is the set of all signed 64-bit integers.
// Range: -9223372036854775808 through 9223372036854775807.
type int64 int64

// float32 is the set of all IEEE 754 32-bit floating-point numbers.
type float32 float32

// float64 is the set of all IEEE 754 64-bit floating-point numbers.
type float64 float64

// complex64 is the set of all complex numbers with float32 real and
// imaginary parts.
type complex64 complex64

//
//	LBRA rreg ',' rel
//	{
//		outcode(int($1), &$2, 0, &$4);
//	}
label3:
	BLTZ	R1, 1(PC)	// BLTZ R1, 1(PC)	// 04200001
	BLTZ	R1, label3	// BLTZ R1, 22		// 0420fffd

//
// floating point conditional branch
//
//	LBRA rel
label4:
	BFPT	1(PC)	// BFPT 1(PC)			// 4501000100000000
	BFPT	label4	// BFPT 24			// 4501fffd00000000

//inst:
//
// load ints and bytes
//

    return new CompactHashMap<>(expectedSize);
  }

  private static final Object NOT_FOUND = new Object();

  /**
   * Maximum allowed false positive probability of detecting a hash flooding attack given random
   * input.
   */
  @VisibleForTesting(
      )
  static final double HASH_FLOODING_FPP = 0.001;

  /**

      int expectedSize) {
    return new CompactHashSet<>(expectedSize);
  }

  /**
   * Maximum allowed false positive probability of detecting a hash flooding attack given random
   * input.
   */
  @VisibleForTesting(
      )
  static final double HASH_FLOODING_FPP = 0.001;

  /**

import org.jspecify.annotations.Nullable;

/**
 * A bundle of statistical summary values -- sum, count, mean/average, min and max, and several
 * forms of variance -- that were computed from a single set of zero or more floating-point values.
 *
 * <p>There are two ways to obtain a {@code Stats} instance:
 *
 * <ul>
 *   <li>If all the values you want to summarize are already known, use the appropriate {@code

```plaintext
/home/user/code/awesome-project/.venv/bin:/usr/bin:/bin:/usr/sbin:/sbin
```

That means that the system will now start looking first for programs in:

```plaintext
/home/user/code/awesome-project/.venv/bin
```

before looking in the other directories.

So, when you type `python` in the terminal, the system will find the Python program in

```plaintext