Sort List

Sort List

Question

Leetcode: Sort List | LeetCode OJ Lintcode: (98) Sort List

Sort a linked list in O(n log n) time using constant space complexity.

题解思路

链表的排序操作,对于常用的排序算法,能达到O(nlogn)的复杂度有快速排序(平均情况),归并排序,堆排序。

对于数组,归并排序一般需要使用O(n)的额外空间,虽然也有原地的实现方法。但对于链表这样的数据结构,排序是指针next值的变化,所以只需要常数级的额外空间。

归并排序的核心思想在于,根据分治思想,可以按照左、右、合并的顺序,实现递归模型,也就是先找出左右链表,最后进行归并。

三个主要步骤

  1. 找到链表中点:可以通过快慢指针的方法

  2. 合并两个有序链表:链表的基本问题

  3. 分治递归

源代码

/**
 * Definition for ListNode.
 * public class ListNode {
 *     int val;
 *     ListNode next;
 *     ListNode(int val) {
 *         this.val = val;
 *         this.next = null;
 *     }
 * }
 */

public class Solution {
    private ListNode findMiddle(ListNode head) {
        ListNode slow = head;
        ListNode fast = head.next;
        while (fast != null && fast.next != null) {
            fast = fast.next.next;
            slow = slow.next;
        }
        return slow;
    }

    private ListNode merge(ListNode head1, ListNode head2) {
        ListNode dummy = new ListNode(0);
        ListNode pointer = dummy;

        while (head1 != null && head2 != null) {
            if (head1.val < head2.val) {
                pointer.next = head1;
                head1 = head1.next;
            } else {
                pointer.next = head2;
                head2 = head2.next;
            }
            pointer = pointer.next;
        }

        if (head1 != null) {
            pointer.next = head1;
        } else {
            pointer.next = head2;
        }

        return dummy.next;
    }

    /**
     * @param head: The head of linked list.
     * @return: You should return the head of the sorted linked list,
                    using constant space complexity.
     */
    public ListNode sortList(ListNode head) {
        if (head == null || head.next == null) {
            return head;
        }
        ListNode mid = findMiddle(head);
        ListNode right = sortList(mid.next);
        mid.next = null;
        ListNode left = sortList(head);

        return merge(left, right);
    }
}

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