# Two Strings Are Anagrams
### Source
- CC150: [(158) Two Strings Are Anagrams](http://www.lintcode.com/en/problem/two-strings-are-anagrams/)
~~~
Write a method anagram(s,t) to decide if two strings are anagrams or not.
Example
Given s="abcd", t="dcab", return true.
Challenge
O(n) time, O(1) extra space
~~~
### 题解1 - hashmap 统计字频
判断两个字符串是否互为变位词,若区分大小写,考虑空白字符时,直接来理解可以认为两个字符串的拥有各不同字符的数量相同。对于比较字符数量的问题常用的方法为遍历两个字符串,统计其中各字符出现的频次,若不等则返回`false`. 有很多简单字符串类面试题都是此题的变形题。
### C++
~~~
class Solution {
public:
/**
* @param s: The first string
* @param b: The second string
* @return true or false
*/
bool anagram(string s, string t) {
if (s.empty() || t.empty()) {
return false;
}
if (s.size() != t.size()) {
return false;
}
int letterCount[256] = {0};
for (int i = 0; i != s.size(); ++i) {
++letterCount[s[i]];
--letterCount[t[i]];
}
for (int i = 0; i != t.size(); ++i) {
if (letterCount[t[i]] != 0) {
return false;
}
}
return true;
}
};
~~~
### 源码分析
1. 两个字符串长度不等时必不可能为变位词(需要注意题目条件灵活处理)。
1. 初始化含有256个字符的计数器数组。
1. 对字符串 s 自增,字符串 t 递减,再次遍历判断`letterCount`数组的值,小于0时返回`false`.
在字符串长度较长(大于所有可能的字符数)时,还可对第二个`for`循环做进一步优化,即`t.size() > 256`时,使用256替代`t.size()`, 使用`i`替代`t[i]`.
### 复杂度分析
两次遍历字符串,时间复杂度最坏情况下为 O(2n)O(2n)O(2n), 使用了额外的数组,空间复杂度 O(256)O(256)O(256).
### 题解2 - 排序字符串
另一直接的解法是对字符串先排序,若排序后的字符串内容相同,则其互为变位词。题解1中使用 hashmap 的方法对于比较两个字符串是否互为变位词十分有效,但是在比较多个字符串时,使用 hashmap 的方法复杂度则较高。
### C++
~~~
class Solution {
public:
/**
* @param s: The first string
* @param b: The second string
* @return true or false
*/
bool anagram(string s, string t) {
if (s.empty() || t.empty()) {
return false;
}
if (s.size() != t.size()) {
return false;
}
sort(s.begin(), s.end());
sort(t.begin(), t.end());
if (s == t) {
return true;
} else {
return false;
}
}
};
~~~
### 源码分析
对字符串 s 和 t 分别排序,而后比较是否含相同内容。对字符串排序时可以采用先统计字频再组装成排序后的字符串,效率更高一点。
### 复杂度分析
C++的 STL 中 sort 的时间复杂度介于 O(n)O(n)O(n) 和 O(n2)O(n^2)O(n2)之间,判断`s == t`时间复杂度最坏为 O(n)O(n)O(n).
### Reference
- *CC150 Chapter 9.1* 中文版 p109
- 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