}
  }

  public void testLog2NegativeAlwaysThrows() {
    for (int x : NEGATIVE_INTEGER_CANDIDATES) {
      for (RoundingMode mode : ALL_ROUNDING_MODES) {
        assertThrows(IllegalArgumentException.class, () -> IntMath.log2(x, mode));
      }
    }
  }

  // Relies on the correctness of BigIntegerMath.log2 for all modes except UNNECESSARY.

    }
    return tmp;
  }

  @Benchmark
  int log2Round(int reps) {
    int tmp = 0;
    for (int i = 0; i < reps; i++) {
      int j = i & ARRAY_MASK;
      tmp += DoubleMath.log2(positiveDoubles[j], mode);
    }
    return tmp;
  }

    }
  }

  public void testLog2NegativeAlwaysThrows() {
    for (long x : NEGATIVE_LONG_CANDIDATES) {
      for (RoundingMode mode : ALL_ROUNDING_MODES) {
        assertThrows(IllegalArgumentException.class, () -> LongMath.log2(x, mode));
      }
    }
  }

  /* Relies on the correctness of BigIntegerMath.log2 for all modes except UNNECESSARY. */

     *
     * The key idea is that based on the number of leading zeros (equivalently, floor(log2(x))), we
     * can narrow the possible floor(log10(x)) values to two. For example, if floor(log2(x)) is 6,
     * then 64 <= x < 128, so floor(log10(x)) is either 1 or 2.
     */
    int y = maxLog10ForLeadingZeros[Long.numberOfLeadingZeros(x)];
    /*

  @SuppressWarnings("UseCorrectAssertInTests") // TODO(b/345814817): Remove or convert assertion.
  private static BigInteger oldSlowFactorial(int n1, int n2) {
    assert n1 <= n2;
    if (IntMath.log2(n2, CEILING) * (n2 - n1) < Long.SIZE - 1) {
      // the result will definitely fit into a long
      long result = 1;
      for (int i = n1 + 1; i <= n2; i++) {
        result *= i;
      }

    }
    return tmp;
  }

  @Benchmark
  int log2Round(int reps) {
    int tmp = 0;
    for (int i = 0; i < reps; i++) {
      int j = i & ARRAY_MASK;
      tmp += DoubleMath.log2(positiveDoubles[j], mode);
    }
    return tmp;
  }

  @SuppressWarnings("UseCorrectAssertInTests") // TODO(b/345814817): Remove or convert assertion.
  private static BigInteger oldSlowFactorial(int n1, int n2) {
    assert n1 <= n2;
    if (IntMath.log2(n2, CEILING) * (n2 - n1) < Long.SIZE - 1) {
      // the result will definitely fit into a long
      long result = 1;
      for (int i = n1 + 1; i <= n2; i++) {
        result *= i;
      }

    // This is an extremely fast implementation of BigInteger.doubleValue(). JDK patch pending.
    BigInteger absX = x.abs();
    int exponent = absX.bitLength() - 1;
    // exponent == floor(log2(abs(x)))
    if (exponent < Long.SIZE - 1) {
      return x.longValue();
    } else if (exponent > MAX_EXPONENT) {
      return x.signum() * POSITIVE_INFINITY;
    }

    /*

    // This is an extremely fast implementation of BigInteger.doubleValue(). JDK patch pending.
    BigInteger absX = x.abs();
    int exponent = absX.bitLength() - 1;
    // exponent == floor(log2(abs(x)))
    if (exponent < Long.SIZE - 1) {
      return x.longValue();
    } else if (exponent > MAX_EXPONENT) {
      return x.signum() * POSITIVE_INFINITY;
    }

    /*

 * offering expected O(n + k log k) performance (worst case O(n log k)) for n calls to {@link
 * #offer} and a call to {@link #topK}, with O(k) memory. In comparison, quickselect has the same
 * asymptotics but requires O(n) memory, and a {@code PriorityQueue} implementation takes O(n log
 * k). In benchmarks, this implementation performs at least as well as either implementation, and