void testLargeMidValue() {
            long largeMid = Long.MAX_VALUE;
            testMessage.setMid(largeMid);
            assertEquals(largeMid, testMessage.getMid());

            // HashCode should handle overflow correctly
            int hash = testMessage.hashCode();
            assertEquals((int) largeMid, hash);
        }

        @Test
        @DisplayName("Should handle negative status codes")

   * 1}, this method has the identical effect to {@link #add(Object)}. This method is functionally
   * equivalent (except in the case of overflow) to the call {@code
   * addAll(Collections.nCopies(element, occurrences))}, which would presumably perform much more
   * poorly.
   *

      /*
       * It speeds things up considerably to unconditionally add count to totalCount here,
       * but that destroys failure atomicity in the case of count overflow. =(
       */
      int cmp = comparator.compare(e, getElement());
      if (cmp < 0) {
        AvlNode<E> initLeft = left;
        if (initLeft == null) {
          result[0] = 0;

      int adjust = size() - 1;
      for (int i = 0; i < axes.size(); i++) {
        adjust *= 31;
        adjust = ~~adjust;
        // in GWT, we have to deal with integer overflow carefully
      }
      int hash = 1;
      for (Set<E> axis : axes) {
        hash = 31 * hash + (size() / axis.size() * axis.hashCode());

        hash = ~~hash;
      }
      hash += adjust;

  }

  /** There's no reason for the queueSize to ever be more than maxSize + 1 */
  private static int capAtMaximumSize(int queueSize, int maximumSize) {
    return min(queueSize - 1, maximumSize) + 1; // don't overflow
  }

    i = 1 << 30;
    assertFalse(MinMaxPriorityQueue.isEvenLevel(i - 2));
    assertTrue(MinMaxPriorityQueue.isEvenLevel(i - 1));
    assertTrue(MinMaxPriorityQueue.isEvenLevel(i));

    // 1 << 31 is negative because of overflow, 1 << 31 - 1 is positive
    // since isEvenLevel adds 1, we need to do - 2.
    assertTrue(MinMaxPriorityQueue.isEvenLevel((1 << 31) - 2));
    assertTrue(MinMaxPriorityQueue.isEvenLevel(Integer.MAX_VALUE - 1));

n=this._element.scrollHeight>document.documentElement.clientHeight;n||(this._element.style.overflowY="hidden"),this._element.classList.add(ht);var i=d.getTransitionDurationFromElement(this._dialog);o.default(this._element).off(d.TRANSITION_END),o.default(this._element).one(d.TRANSITION_END,(function(){t._element.classList.remove(ht),n||o.default(t._element).one(d.TRANSITION_END,(function(){t._element.style.overflowY=""})).emulateTransitionEnd(t._element,i)})).emulateTransitionEnd(i),this._element.foc...

      int adjust = size() - 1;
      for (int i = 0; i < axes.size(); i++) {
        adjust *= 31;
        adjust = ~~adjust;
        // in GWT, we have to deal with integer overflow carefully
      }
      int hash = 1;
      for (Set<E> axis : axes) {
        hash = 31 * hash + (size() / axis.size() * axis.hashCode());

        hash = ~~hash;
      }
      hash += adjust;

  }

  /**
   * Any object can be the result of a Future, and not every object has a reasonable toString()
   * implementation. Using a reconstruction of the default Object.toString() prevents OOMs and stack
   * overflows, and helps avoid sensitive data inadvertently ending up in exception messages.
   */
  private void appendResultObject(StringBuilder builder, @Nullable Object o) {
    if (o == null) {
      builder.append("null");

   *       tasks -- even tasks that are not themselves {@code directExecutor} tasks.
   *   <li>If many such tasks are chained together (such as with {@code
   *       future.transform(...).transform(...).transform(...)....}), they may overflow the stack.
   *       (In simple cases, callers can avoid this by registering all tasks with the same {@link
   *       MoreExecutors#newSequentialExecutor} wrapper around {@code directExecutor()}. More