深入探究TimSort对归并排序算法的优化及Java实现

void merge(int[] a, int lo, int mid, int hi, int[] aux) {
for (int k = lo; k <= mid; k++) {
  aux[k] = a[k];
}
for (int k = mid + 1;k <= hi; k++) {
  aux[k] = a[hi - k + mid + 1];
}
int i = lo, j = hi;   //从两端往中间
for (int k = lo; k <= hi; k++)
  if (aux[i] <= aux[j]) a[k] = aux[i++];
  else a[k] = aux[j--];
}

    if (nRemaining < MIN_MERGE) {
      int initRunLen = countRunAndMakeAscending(a, lo, hi);
      binarySort(a, lo, hi, lo + initRunLen);
      return;
    }

int minRun = minRunLength(nRemaining);
    do {
      //找出下一个分区的起始位置，同时也对反向序列做了翻转处理
      int runLen = countRunAndMakeAscending(a, lo, hi);

      //保证run stack中的run的都大于minRun ，如果当前分区太小，就从后面取出元素补足
      if (runLen < minRun) {
        int force = nRemaining <= minRun ? nRemaining : minRun;
        binarySort(a, lo, lo + force, lo + runLen);
        runLen = force;
      }

      //把run放入 run stack中
      ts.pushRun(lo, runLen);
      //判断是否应该合并，i是从栈顶开始的，知道不能合并为止
      //1. runLen[i - 3] > runLen[i - 2] + runLen[i - 1] 
      //2. runLen[i - 2] > runLen[i - 1]
      ts.mergeCollapse();


      lo += runLen;
      nRemaining -= runLen;
    } while (nRemaining != 0);

    // Merge all remaining runs to complete sort
    assert lo == hi;
    //合并剩下的run
    ts.mergeForceCollapse();
    assert ts.stackSize == 1;

/**
* 如果后2个run的长度加起来比前面一个长，则使用中间位置的run和前后长度更短的run一个合并
* 如果后2个run的长度加起来比前面一个短，则把后面2个run合并
*/
 private void mergeCollapse() {
    while (stackSize > 1) {
      int n = stackSize - 2;
      if (n > 0 && runLen[n-1] <= runLen[n] + runLen[n+1]) {
        if (runLen[n - 1] < runLen[n + 1])
          n--;
        mergeAt(n);
      } else if (runLen[n] <= runLen[n + 1]) {
        mergeAt(n);
      } else {
        break; // Invariant is established
      }
    }
  }