* This is a big deal - we're talking factors of 2-8 in microbenchmarks, not just 10-20%. (This is
   * a hotspot optimizer bug, which should be fixed, but that's a separate, big project).
   *
   * The coding pattern above is heavily used in java.util, e.g. in ArrayList. There is a
   * RangeCheckMicroBenchmark in the JDK that was used to test this.
   *

   * }
   * }</pre>
   *
   * <p>Note that if any input set is empty, the Cartesian product will also be empty. If no sets at
   * all are provided (an empty list), the resulting Cartesian product has one element, an empty
   * list (counter-intuitive, but mathematically consistent).
   *
   * <p><i>Performance notes:</i> while the cartesian product of sets of size {@code m, n, p} is a

  public static int checkedSubtract(int a, int b) {
    long result = (long) a - b;
    checkNoOverflow(result == (int) result, "checkedSubtract", a, b);
    return (int) result;
  }

  /**
   * Returns the product of {@code a} and {@code b}, provided it does not overflow.
   *
   * @throws ArithmeticException if {@code a * b} overflows in signed {@code int} arithmetic
   */
  public static int checkedMultiply(int a, int b) {

      return BigInteger.valueOf(LongMath.factorial(n));
    } else {
      int k = 20;
      return BigInteger.valueOf(LongMath.factorial(k)).multiply(oldSlowFactorial(k, n));
    }
  }

  /** Returns the product of {@code n1} exclusive through {@code n2} inclusive. */
  private static BigInteger oldSlowFactorial(int n1, int n2) {
    assert n1 <= n2;
    if (IntMath.log2(n2, CEILING) * (n2 - n1) < Long.SIZE - 1) {

    checkState(count() > 1);
    return sumOfProductsOfDeltas / (count() - 1);
  }

  /**
   * Returns the <a href="http://mathworld.wolfram.com/CorrelationCoefficient.html">Pearson's or
   * product-moment correlation coefficient</a> of the values. The count must greater than one, and
   * the {@code x} and {@code y} values must both have non-zero population variance (i.e. {@code

         * InterruptibleChannel and JavaLangAccess.blockedOn(Thread, Interruptible), it isn't
         * predictable what work might be done. (e.g., close a file and flush buffers to disk). To
         * protect ourselves from this, we park ourselves and tell our interrupter that we did so.
         */
        if (state == PARKED || compareAndSet(state, PARKED)) {
          // Interrupting Cow Says:
          //  ______

        axesSizeProduct[i] = IntMath.checkedMultiply(axesSizeProduct[i + 1], axes.get(i).size());
      }
    } catch (ArithmeticException e) {
      throw new IllegalArgumentException(
          "Cartesian product too large; must have size at most Integer.MAX_VALUE");
    }
    this.axesSizeProduct = axesSizeProduct;
  }

  private int getAxisIndexForProductIndex(int index, int axis) {

   * contents.
   *
   * <p>We can only test this with a file system that supports SecureDirectoryStream, because it's
   * not possible to protect against this if the file system doesn't.
   */
  public void testDirectoryDeletion_directorySymlinkRace() throws IOException {
    int iterations = isAndroid() ? 100 : 5000;

 * href="https://github.com/ReactiveX/RxJava/wiki">RxJava</a> (supplemented with its <a
 * href="https://github.com/ReactiveX/RxAndroid">RxAndroid</a> extension if you are building for
 * Android) or <a href="https://projectreactor.io/">Project Reactor</a>. (For the basics of
 * translating code from using an event bus to using a reactive-streams framework, see these two
 * guides: <a href="https://blog.jkl.gg/implementing-an-event-bus-with-rxjava-rxbus/">1</a>, <a

   * This is a big deal - we're talking factors of 2-8 in microbenchmarks, not just 10-20%. (This is
   * a hotspot optimizer bug, which should be fixed, but that's a separate, big project).
   *
   * The coding pattern above is heavily used in java.util, e.g. in ArrayList. There is a
   * RangeCheckMicroBenchmark in the JDK that was used to test this.
   *