# Linked List Cycle II
### Source
- leetcode: [Linked List Cycle II | LeetCode OJ](https://leetcode.com/problems/linked-list-cycle-ii/)
- lintcode: [(103) Linked List Cycle II](http://www.lintcode.com/en/problem/linked-list-cycle-ii/)
~~~
Given a linked list, return the node where the cycle begins. If there is no cycle, return null.
Example
Given -21->10->4->5, tail connects to node index 1,return node 10
Challenge
Follow up:
Can you solve it without using extra space?
~~~
### 题解 - 快慢指针
题 [Linked List Cycle | Data Structure and Algorithm](http://algorithm.yuanbin.me/zh-cn/linked_list/linked_list_cycle.html) 的升级版,题目要求不适用额外空间,则必然还是使用快慢指针解决问题。首先设组成环的节点个数为 rrr, 链表中节点个数为 nnn. 首先我们来分析下在链表有环时都能推出哪些特性:
1. 快慢指针第一次相遇时快指针比慢指针多走整数个环, 这个容易理解,相遇问题。
1. 每次相遇都在同一个节点。第一次相遇至第二次相遇,快指针需要比慢指针多走一个环的节点个数,而快指针比慢指针多走的步数正好是慢指针自身移动的步数,故慢指针恰好走了一圈回到原点。
从以上两个容易得到的特性可知,在仅仅知道第一次相遇时的节点还不够,相遇后如果不改变既有策略则必然找不到环的入口。接下来我们分析下如何从第一次相遇的节点走到环的入口节点。还是让我们先从实际例子出发,以下图为例。
![Linked List Cycle II](https://box.kancloud.cn/2015-10-24_562b1f4ae20b6.png)
`slow`和`fast`节点分别初始化为节点`1`和`2`,假设快慢指针第一次相遇的节点为`0`, 对应于环中的第`i`个节点 CiC_iCi, 那么此时慢指针正好走了 n−r−1+in - r - 1 + in−r−1+i 步,快指针则走了 2⋅(n−r−1+i)2 \cdot (n - r - 1 + i)2⋅(n−r−1+i) 步,且存在[1](#): n−r−1+i+1=l⋅rn - r - 1 + i + 1= l \cdot rn−r−1+i+1=l⋅r. (之所以在`i`后面加1是因为快指针初始化时多走了一步) 快慢指针第一次相遇时慢指针肯定没有走完整个环,且慢指针走的步数即为整数个环节点个数,由性质1和性质2可联合推出。
现在分析下相遇的节点和环的入口节点之间的关联,要从环中第`i`个节点走到环的入口节点,则按照顺时针方向移动[2](#): (l⋅r−i+1)(l \cdot r - i + 1)(l⋅r−i+1) 个节点 (lll 为某个非负整数) 即可到达。现在来看看式[1](#)和式[2](#)间的关系。由式[1](#)可以推知 n−r=l⋅r−in - r = l \cdot r - in−r=l⋅r−i. 从头节点走到环的入口节点所走的步数可用 n−rn - rn−r 表示,故在快慢指针第一次相遇时让另一节点从头节点出发,慢指针仍从当前位置迭代,第二次相遇时的位置即为环的入口节点!
****> 由于此题快指针初始化为头节点的下一个节点,故分析起来稍微麻烦些,且在第一次相遇后需要让慢指针先走一步,否则会出现死循环。
对于该题来说,快慢指针都初始化为头节点会方便很多,故以下代码使用头节点对快慢指针进行初始化。
### C++
~~~
/**
* Definition of ListNode
* class ListNode {
* public:
* int val;
* ListNode *next;
* ListNode(int val) {
* this->val = val;
* this->next = NULL;
* }
* }
*/
class Solution {
public:
/**
* @param head: The first node of linked list.
* @return: The node where the cycle begins.
* if there is no cycle, return null
*/
ListNode *detectCycle(ListNode *head) {
if (NULL == head || NULL == head->next) {
return NULL;
}
ListNode *slow = head, *fast = head;
while (NULL != fast && NULL != fast->next) {
fast = fast->next->next;
slow = slow->next;
if (slow == fast) {
fast = head;
while (slow != fast) {
fast = fast->next;
slow = slow->next;
}
return slow;
}
}
return NULL;
}
};
~~~
### 源码分析
1. 异常处理。
1. 找第一次相遇的节点。
1. 将`fast`置为头节点,并只走一步,直至快慢指针第二次相遇,返回慢指针所指的节点。
### 复杂度分析
第一次相遇的最坏时间复杂度为 O(n)O(n)O(n), 第二次相遇的最坏时间复杂度为 O(n)O(n)O(n). 故总的时间复杂度近似为 O(n)O(n)O(n), 空间复杂度 O(1)O(1)O(1).
### Reference
- [Linked List Cycle II | 九章算法](http://www.jiuzhang.com/solutions/linked-list-cycle-ii/)
- Preface
- Part I - Basics
- Basics Data Structure
- String
- Linked List
- Binary Tree
- Huffman Compression
- Queue
- Heap
- Stack
- Set
- Map
- Graph
- Basics Sorting
- Bubble Sort
- Selection Sort
- Insertion Sort
- Merge Sort
- Quick Sort
- Heap Sort
- Bucket Sort
- Counting Sort
- Radix Sort
- Basics Algorithm
- Divide and Conquer
- Binary Search
- Math
- Greatest Common Divisor
- Prime
- Knapsack
- Probability
- Shuffle
- Basics Misc
- Bit Manipulation
- Part II - Coding
- String
- strStr
- Two Strings Are Anagrams
- Compare Strings
- Anagrams
- Longest Common Substring
- Rotate String
- Reverse Words in a String
- Valid Palindrome
- Longest Palindromic Substring
- Space Replacement
- Wildcard Matching
- Length of Last Word
- Count and Say
- Integer Array
- Remove Element
- Zero Sum Subarray
- Subarray Sum K
- Subarray Sum Closest
- Recover Rotated Sorted Array
- Product of Array Exclude Itself
- Partition Array
- First Missing Positive
- 2 Sum
- 3 Sum
- 3 Sum Closest
- Remove Duplicates from Sorted Array
- Remove Duplicates from Sorted Array II
- Merge Sorted Array
- Merge Sorted Array II
- Median
- Partition Array by Odd and Even
- Kth Largest Element
- Binary Search
- Binary Search
- Search Insert Position
- Search for a Range
- First Bad Version
- Search a 2D Matrix
- Search a 2D Matrix II
- Find Peak Element
- Search in Rotated Sorted Array
- Search in Rotated Sorted Array II
- Find Minimum in Rotated Sorted Array
- Find Minimum in Rotated Sorted Array II
- Median of two Sorted Arrays
- Sqrt x
- Wood Cut
- Math and Bit Manipulation
- Single Number
- Single Number II
- Single Number III
- O1 Check Power of 2
- Convert Integer A to Integer B
- Factorial Trailing Zeroes
- Unique Binary Search Trees
- Update Bits
- Fast Power
- Hash Function
- Count 1 in Binary
- Fibonacci
- A plus B Problem
- Print Numbers by Recursion
- Majority Number
- Majority Number II
- Majority Number III
- Digit Counts
- Ugly Number
- Plus One
- Linked List
- Remove Duplicates from Sorted List
- Remove Duplicates from Sorted List II
- Remove Duplicates from Unsorted List
- Partition List
- Two Lists Sum
- Two Lists Sum Advanced
- Remove Nth Node From End of List
- Linked List Cycle
- Linked List Cycle II
- Reverse Linked List
- Reverse Linked List II
- Merge Two Sorted Lists
- Merge k Sorted Lists
- Reorder List
- Copy List with Random Pointer
- Sort List
- Insertion Sort List
- Check if a singly linked list is palindrome
- Delete Node in the Middle of Singly Linked List
- Rotate List
- Swap Nodes in Pairs
- Remove Linked List Elements
- Binary Tree
- Binary Tree Preorder Traversal
- Binary Tree Inorder Traversal
- Binary Tree Postorder Traversal
- Binary Tree Level Order Traversal
- Binary Tree Level Order Traversal II
- Maximum Depth of Binary Tree
- Balanced Binary Tree
- Binary Tree Maximum Path Sum
- Lowest Common Ancestor
- Invert Binary Tree
- Diameter of a Binary Tree
- Construct Binary Tree from Preorder and Inorder Traversal
- Construct Binary Tree from Inorder and Postorder Traversal
- Subtree
- Binary Tree Zigzag Level Order Traversal
- Binary Tree Serialization
- Binary Search Tree
- Insert Node in a Binary Search Tree
- Validate Binary Search Tree
- Search Range in Binary Search Tree
- Convert Sorted Array to Binary Search Tree
- Convert Sorted List to Binary Search Tree
- Binary Search Tree Iterator
- Exhaustive Search
- Subsets
- Unique Subsets
- Permutations
- Unique Permutations
- Next Permutation
- Previous Permuation
- Unique Binary Search Trees II
- Permutation Index
- Permutation Index II
- Permutation Sequence
- Palindrome Partitioning
- Combinations
- Combination Sum
- Combination Sum II
- Minimum Depth of Binary Tree
- Word Search
- Dynamic Programming
- Triangle
- Backpack
- Backpack II
- Minimum Path Sum
- Unique Paths
- Unique Paths II
- Climbing Stairs
- Jump Game
- Word Break
- Longest Increasing Subsequence
- Palindrome Partitioning II
- Longest Common Subsequence
- Edit Distance
- Jump Game II
- Best Time to Buy and Sell Stock
- Best Time to Buy and Sell Stock II
- Best Time to Buy and Sell Stock III
- Best Time to Buy and Sell Stock IV
- Distinct Subsequences
- Interleaving String
- Maximum Subarray
- Maximum Subarray II
- Longest Increasing Continuous subsequence
- Longest Increasing Continuous subsequence II
- Graph
- Find the Connected Component in the Undirected Graph
- Route Between Two Nodes in Graph
- Topological Sorting
- Word Ladder
- Bipartial Graph Part I
- Data Structure
- Implement Queue by Two Stacks
- Min Stack
- Sliding Window Maximum
- Longest Words
- Heapify
- Problem Misc
- Nuts and Bolts Problem
- String to Integer
- Insert Interval
- Merge Intervals
- Minimum Subarray
- Matrix Zigzag Traversal
- Valid Sudoku
- Add Binary
- Reverse Integer
- Gray Code
- Find the Missing Number
- Minimum Window Substring
- Continuous Subarray Sum
- Continuous Subarray Sum II
- Longest Consecutive Sequence
- Part III - Contest
- Google APAC
- APAC 2015 Round B
- Problem A. Password Attacker
- Microsoft
- Microsoft 2015 April
- Problem A. Magic Box
- Problem B. Professor Q's Software
- Problem C. Islands Travel
- Problem D. Recruitment
- Microsoft 2015 April 2
- Problem A. Lucky Substrings
- Problem B. Numeric Keypad
- Problem C. Spring Outing
- Microsoft 2015 September 2
- Problem A. Farthest Point
- Appendix I Interview and Resume
- Interview
- Resume