【242】Valid Anagram:

Given two strings s and t, write a function to determine if t is an anagram of s.

For example,
s = "anagram", t = "nagaram", return true.
s = "rat", t = "car", return false.

思路:看一个字符串是否是另一个字符串乱序形成的,这里面首先要考虑重复字母的情况,并且考虑时间空间复杂度,如果字符串很长的话。通过遍历其中一个字符串,逐个比较是否contains的方法不满足复杂度要求。所以考虑使用一个数组,索引是字母,值是这个字母出现的频率,两个字符串都指向这个数组,一个字符串增加频率,一个减小,然后for循环遍历这个数组,如果有非0值则返回FALSE

  public class Solution {
public boolean isAnagram(String s, String t) {
if(s.length()!=t.length()){
return false;
}
int[] count = new int[26];
for(int i=0;i<s.length();i++){
count[s.charAt(i)-'a']++;
count[t.charAt(i)-'a']--;
}
for(int i:count){
if(i!=0){
return false;
}
}
return true;
}
}

【235】Lowest Common Ancestor of a Binary Search Tree

可以先参考这篇博客:http://blog.csdn.net/beiyetengqing/article/details/7633651

Given a binary search tree (BST), find the lowest common ancestor (LCA) of two given nodes in the BST.

According to the definition of LCA on Wikipedia: “The lowest common ancestor is defined between two nodes v and w as the lowest node in T that has both v and w as descendants (where we allow a node to be a descendant of itself).”

        _______6______
/ \
___2__ ___8__
/ \ / \
0 _4 7 9
/ \
3 5

For example, the lowest common ancestor (LCA) of nodes 2 and 8 is 6. Another example is LCA of nodes 2 and 4 is 2, since a node can be a descendant of itself

思路:找最近公共祖先,二叉树一般用的都是递归,什么时候停止递归,由于这是二叉搜索树,所以当左右结点当一个比根节点小,一个比根节点大就停止,也就是对应以下代码中判断条件中的第三种情况,另外再比较都比根节点小或者都比根节点大的时候,用Math.max()或者Math.min()更优雅

/**
* Definition for a binary tree node.
* public class TreeNode {
* int val;
* TreeNode left;
* TreeNode right;
* TreeNode(int x) { val = x; }
* }
*/
public class Solution {
public TreeNode lowestCommonAncestor(TreeNode root, TreeNode p, TreeNode q) {
if(root==null||p==null||q==null)return null;
if(Math.max(p.val,q.val)<root.val)return lowestCommonAncestor(root.left, p, q);//both lower than root
if(Math.min(p.val,q.val)>root.val)return lowestCommonAncestor(root.right, p, q);//both higher than root
return root;//the third cosition }
}

【191】Number of 1 Bits

Write a function that takes an unsigned integer and returns the number of ’1' bits it has (also known as the Hamming weight).

For example, the 32-bit integer ’11' has binary representation 00000000000000000000000000001011, so the function should return 3.

思路:

求一个数中1的个数,也就是汉明距离,起初打算转换用string来处理,但是显然这样很慢,还有一种是按位处理,通过按位与1相与,然后记录次数,然后让这个数逻辑右移(算数右移和逻辑右移的区别:运算符“>>”执行算术右移,它使用最高位填充移位后左侧的空位,这样可以保证符号不变。右移的结果为:每移一位,第一个操作数被2除一次,移动的次数由第二个操作数确定。逻辑右移或叫无符号右移运算符“>>>“只对位进行操作,没有算术含义,它用0填充左侧的空位,不保证符号。)

public class Solution {
// you need to treat n as an unsigned value
public int hammingWeight(int n) { String str = Integer.toBinaryString(n);//先把数转换成二进制
return (str.replace("0","").length());
}
}
public class Solution {
// you need to treat n as an unsigned value
public int hammingWeight(int n) {
return Integer.bitCount(n);//直接算一个整数的非0个数
}
}
public int hammingWeight(int n) {
int result = 0;
while (n != 0) {
if ((n & 1) == 1) {
result++;
}
n >>>= 1;
}
return result;
}

【169】Majority Element

Given an array of size n, find the majority element. The majority element is the element that appears more than ⌊ n/2 ⌋ times.

You may assume that the array is non-empty and the majority element always exist in the array.

找超过数组长度一半的高频元素

思路:用字符串来处理永远不是最优的方法呀,字符串只能用来转换运算,不能实现逻辑功能。想象一下木桶原则的逆原则。

public class Solution {
public int majorityElement(int[] nums) {
int major = nums[0];//以第一个元素当探针
int count = 1;
for(int i=1;i<nums.length;i++){//注意从1开始,即第二个元素开始
if(count==0){//如果出现了和这个探针的元素频率相同的数字,则探针元素重新赋值,并且次数为1,接下来进行下一循环,不再执行后面 的判断
count = 1;
major = nums[i];
}else if(major ==nums[i]){
count++;
}else if(major != nums[i]){
count--;
} }
return major;
/*String numsStr = Arrays.toString(nums);
int size = nums.length;
int[] freq = new int[size];
int max = 0;
for(int i=0;i<size;i++){
freq[i] = size-numsStr.replace(numsStr.charAt(i)+"","").length();
if(max<freq[i]) max = freq[i];
}
return max;*/
}
}

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