# Convert Sorted Array to Binary Search Tree
### Source
- leetcode: [Convert Sorted Array to Binary Search Tree | LeetCode OJ](https://leetcode.com/problems/convert-sorted-array-to-binary-search-tree/)
- lintcode: [(177) Convert Sorted Array to Binary Search Tree With Minimal Height](http://www.lintcode.com/en/problem/convert-sorted-array-to-binary-search-tree-with-minimal-height/)
~~~
Given an array where elements are sorted in ascending order,
convert it to a height balanced BST.
Given a sorted (increasing order) array,
Convert it to create a binary tree with minimal height.
Example
Given [1,2,3,4,5,6,7], return
4
/ \
2 6
/ \ / \
1 3 5 7
Note
There may exist multiple valid solutions, return any of them.
~~~
### 题解 - 折半取中
将二叉搜索树按中序遍历即可得升序 key 这个容易实现,但反过来由升序 key 逆推生成二叉搜索树呢?按照二叉搜索树的定义我们可以将较大的 key 链接到前一个树的最右侧节点,这种方法实现极其简单,但是无法达到本题「树高平衡-左右子树的高度差绝对值不超过1」的要求,因此只能另辟蹊径以达到「平衡二叉搜索树」的要求。
要达到「平衡二叉搜索树」这个条件,我们首先应从「平衡二叉搜索树」的特性入手。简单起见,我们先考虑下特殊的满二叉搜索树,满二叉搜索树的一个重要特征就是各根节点的 key 不小于左子树的 key ,而小于右子树的所有 key;另一个则是左右子树数目均相等,那么我们只要能将所给升序序列分成一大一小的左右两半部分即可满足题目要求。又由于此题所给的链表结构中仅有左右子树的链接而无指向根节点的链接,故我们只能从中间的根节点进行分析逐层往下递推直至取完数组中所有 key, 数组中间的索引自然就成为了根节点。由于 OJ 上方法入口参数仅有升序序列,方便起见我们可以另写一私有方法,加入`start`和`end`两个参数,至此递归模型初步建立。
### C++
~~~
/**
* Definition for binary tree
* struct TreeNode {
* int val;
* TreeNode *left;
* TreeNode *right;
* TreeNode(int x) : val(x), left(NULL), right(NULL) {}
* };
*/
class Solution {
public:
TreeNode *sortedArrayToBST(vector<int> &num) {
if (num.empty()) {
return NULL;
}
return middleNode(num, 0, num.size() - 1);
}
private:
TreeNode *middleNode(vector<int> &num, const int start, const int end) {
if (start > end) {
return NULL;
}
TreeNode *root = new TreeNode(num[start + (end - start) / 2]);
root->left = middleNode(num, start, start + (end - start) / 2 - 1);
root->right = middleNode(num, start + (end - start) / 2 + 1, end);
return root;
}
};
~~~
### Java
~~~
/**
* Definition of TreeNode:
* public class TreeNode {
* public int val;
* public TreeNode left, right;
* public TreeNode(int val) {
* this.val = val;
* this.left = this.right = null;
* }
* }
*/
public class Solution {
/**
* @param A: an integer array
* @return: a tree node
*/
public TreeNode sortedArrayToBST(int[] A) {
if (A == null || A.length == 0) return null;
return helper(A, 0, A.length - 1);
}
private TreeNode helper(int[] nums, int start, int end) {
if (start > end) return null;
int mid = start + (end - start) / 2;
TreeNode root = new TreeNode(nums[mid]);
root.left = helper(nums, start, mid - 1);
root.right = helper(nums, mid + 1, end);
return root;
}
}
~~~
### 源码分析
从题解的分析中可以看出中间根节点的建立至关重要!由于数组是可以进行随机访问的,故可取数组中间的索引为根节点,左右子树节点可递归求解。虽然这种递归的过程和「二分搜索」的模板非常像,但是切记本题中根据所给升序序列建立平衡二叉搜索树的过程中需要做到**不重不漏**,故边界处理需要异常小心,不能再套用`start + 1 < end`的模板了。
### 复杂度分析
递归调用`middleNode`方法时每个`key`被访问一次,故时间复杂度可近似认为是 O(n)O(n)O(n).
### Reference
- [Convert Sorted Array to Binary Search Tree | 九章算法](http://www.jiuzhang.com/solutions/convert-sorted-array-to-binary-search-tree/)
- 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