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JavaScript初学者需求领会12个小技巧

四月 10th, 2019  |  www.hg888.com

解释下 Prototypal Inheritance 与 Classical Inheritance 的区别

在类继承中,类是不可变的,区别的语言中对此多三番五次的支撑也不平等,有个别语言中还补助接口、final、abstract
的定义。而原型继承则越来越灵活,原型自身是足以可变的,并且对象或者再三再四自八个原型。

15# Leetcode 81. Search in Rotated Sorted Array II

Follow up for “Search in Rotated Sorted Array”:
What if duplicates are allowed?

Would this affect the run-time complexity? How and why?
Suppose an array sorted in ascending order is rotated at some pivot
unknown to you beforehand. (i.e., 0 1 2 4 5 6 7 might become 4 5 6 7 0
1 2).

Write a function to determine if a given target is in the array.

The array may contain duplicates.

public class Solution {
    // 这个问题在面试中不会让实现完整程序
    // 只需要举出能够最坏情况的数据是 [1,1,1,1... 1] 里有一个0即可。
    // 在这种情况下是无法使用二分法的,复杂度是O(n)
    // 因此写个for循环最坏也是O(n),那就写个for循环就好了
    //  如果你觉得,不是每个情况都是最坏情况,你想用二分法解决不是最坏情况的情况,那你就写一个二分吧。
    //  反正面试考的不是你在这个题上会不会用二分法。这个题的考点是你想不想得到最坏情况。
    public boolean search(int[] nums, int target) {
        for (int i = 0; i < nums.length; i ++) {
            if (nums[i] == target) {
                return true;
            }
        }
        return false;
    }
}

Increasing Triplet Subsequence

Given an unsorted array return whether an increasing subsequence of
length 3 exists or not in the array.

Formally the function should:
Return true if there exists i, j, k
such that arr[i] < arr[j] < arr[k] given 0 ≤ i < j < k
≤ n-1 else return false.
Your algorithm should run in O(n) time complexity and O(1) space
complexity.

Examples:
Given [1, 2, 3, 4, 5],
return true.

Given [5, 4, 3, 2, 1],
return false.
用整数最大值去比较,x1记录第一个数,x2记录第二大的数,当出现第三大的数,则return true。

public class Solution {
    public boolean increasingTriplet(int[] nums) {
        int x1=Integer.MAX_VALUE;
        int x2=Integer.MAX_VALUE;

        for(int x: nums){
            if(x<=x1) x1=x;
            else if(x<=x2) x2=x;
            else return true;
        }
        return false;
    }
}

复制代码 代码如下:

二分查找

JavaScript

function recursiveBinarySearch(array, value, leftPosition,
rightPosition) { // Value DNE if (leftPosition > rightPosition)
return -1; var middlePivot = Math.floor((leftPosition + rightPosition) /
2); if (array[middlePivot] === value) { return middlePivot; } else if
(array[middlePivot] > value) { return recursiveBinarySearch(array,
value, leftPosition, middlePivot – 1); } else { return
recursiveBinarySearch(array, value, middlePivot + 1, rightPosition); } }

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function recursiveBinarySearch(array, value, leftPosition, rightPosition) {
  // Value DNE
  if (leftPosition > rightPosition) return -1;
 
  var middlePivot = Math.floor((leftPosition + rightPosition) / 2);
  if (array[middlePivot] === value) {
    return middlePivot;
  } else if (array[middlePivot] > value) {
    return recursiveBinarySearch(array, value, leftPosition, middlePivot – 1);
  } else {
    return recursiveBinarySearch(array, value, middlePivot + 1, rightPosition);
  }
}

21# Leetcode 162. Find Peak Element

做的部分题的解题思路

Array.prototype.max = function(){
return Math.max.apply(”,this);
}

递归

11# Leetcode 350. Intersection of Two Arrays II

Given two arrays, write a function to compute their intersection.

Example:
Given nums1 = [1, 2, 2, 1], nums2 = [2, 2], return [2, 2].

Note:
Each element in the result should appear as many times as it shows in
both arrays.
The result can be in any order.
Follow up:
What if the given array is already sorted? How would you optimize your
algorithm?
What if nums1’s size is small compared to nums2’s size? Which
algorithm is better?
What if elements of nums2 are stored on disk, and the memory is
limited such that you cannot load all elements into the memory at
once?

public class Solution {
    public int[] intersect(int[] nums1, int[] nums2) {
        Arrays.sort(nums1);
        Arrays.sort(nums2);
        int index1 = 0;
        int index2 = 0;
        List<Integer> list = new ArrayList<>();
        while(index1 < nums1.length && index2 < nums2.length) {
            if (nums1[index1] == nums2[index2]) {
                list.add(nums1[index1]);
                index1++;
                index2++;
            } else if (nums1[index1] < nums2[index2]) {
                index1++;
            } else if (nums1[index1] > nums2[index2]) {
                index2++;
            }
        }
        int[] result = new int[list.size()];
        int index = 0;
        for (int element: list) {
            result[index++] = element;
        }
        return result;
    }
}

Product of Array Except Self

除本人之外的数组之积
Given an array of n integers where n > 1, nums, return an array
output such that output[i] is equal to the product of all the elements
of nums except nums[i].
Solve it without division and in O(n).
For example, given [1,2,3,4], return [24,12,8,6].

解题思路:拆分法
[A_234 , A_134 , A_124 , A_123 ]=
[1 , A_1 , A_12 , A_123 ]*
[A_234 , A_34 , A_4 , 1 ]

/**
 * Created by Administrator on 2017/5/8.
 */
public class LeetCode {

    public static void main(String[] args) {
        // int [] nums={5, 7, 1, 8,3, 10};  //测试
        int[] nums = {1, 3, 5, 6};
        int k = 5;
        int [] res = productExceptSelf(nums);
        for (int i=0;i<res.length;i++) {
            System.out.print(res[i]+" ");
        }
    }

    public static int[] productExceptSelf(int[] nums) {
        final int [] result = new int [nums.length];
        final int [] right = new int [nums.length];
        final int [] left = new int [nums.length];
        left[0]=1;
        for(int i=1;i<nums.length;i++){
            left[i]=left[i-1]*nums[i-1];
        }
        right[nums.length-1]=1;
        for(int i=nums.length-2;i>=0;i--){
            right[i]=right[i+1]*nums[i+1];
        }

        for (int i=0;i<nums.length;i++){
            result[i]=right[i]*left[i];
        }
        return  result;
    }
}

复制代码 代码如下:

== 与 === 的界别是什么

=== 相当于所谓的严刻相比,关键的区分在于===
会同时相比较类型与值,而不是仅比较值。

JavaScript

// Example of comparators 0 == false; // true 0 === false; // false 2 ==
‘2’; // true 2 === ‘2’; // false

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// Example of comparators
0 == false; // true
0 === false; // false
 
2 == ‘2’; // true
2 === ‘2’; // false

16# Leetcode 34. Search for a Range

Given an array of integers sorted in ascending order, find the
starting and ending position of a given target value.

Your algorithm’s runtime complexity must be in the order of O(log n).

If the target is not found in the array, return [-1, -1].

For example,
Given [5, 7, 7, 8, 8, 10] and target value 8,
return [3, 4].

public class Solution {
    public int[] searchRange(int[] nums, int target) {
       if (nums.length == 0) {
            return new int[]{-1,-1};
        }
        int[] bound = new int[2];
        // search for left bound
        int start = 0;
        int end = nums.length - 1;
        while (start + 1 < end) {
            int mid = start + (end - start) / 2;
            if (nums[mid] == target) {
                end = mid;
            } else if (nums[mid] < target) {
                start = mid;
            } else {
                end = mid;
            }
        }
        if (nums[start] == target) {
            bound[0] = start;
        } else if (nums[end] == target) {
            bound[0] = end;
        } else {
            bound[0] = bound[1] = -1;
            return bound;
        }
        //search for right bound
        start = 0;
        end = nums.length - 1;
        while (start + 1 < end) {
            int mid = start + (end - start) / 2;
            if (nums[mid] == target) {
                start = mid;
            } else if (nums[mid] < target) {
                start = mid;
            } else {
                end = mid;
            }
        }
        if (nums[end] == target) {
            bound[1] = end;
        } else if (nums[start] == target) {
            bound[1] = start;
        } else {
            bound[0] = bound[1] = -1;
            return bound;
        }
        return bound;
    }
}

Add Two Numbers

You are given two non-empty linked lists representing two non-negative
integers. The digits are stored in reverse order and each of their nodes
contain a single digit. Add the two numbers and return it as a linked
list.

You may assume the two numbers do not contain any leading zero, except
the number 0 itself.

Input: (2 -> 4 -> 3) + (5 -> 6 -> 4)
Output: 7 -> 0 -> 8
主要学习怎么创建链表,怎么定义链表

public class LeetCode {
    public static void main(String[] args) {
        int[] inputl1=new int[]{2,4,3};
        int[] inputl2=new int[]{5,6,4};
        ListNode l1=buildListNode(inputl1);
        ListNode l2=buildListNode(inputl2);
        ListNode listNode =addTwoNumbers(l1,l2);
        while(listNode!=null){
            System.out.println("val "+listNode.val);
            listNode=listNode.next;
        }
    }
    //定义链表
   public static class ListNode{
        int val;
        ListNode next;
        ListNode(int val){
            this.val=val;
            this.next=null;
        }
    }
    //创建链表
    private static ListNode buildListNode(int[] input){
        ListNode first = null,last = null,newNode;
        int num;
        if(input.length>0){
            for(int i=0;i<input.length;i++){
                newNode=new ListNode(input[i]);
                newNode.next=null;
                if(first==null){
                    first=newNode;
                    last=newNode;
                }
                else{
                    last.next=newNode;
                    last=newNode;
                }
            }
        }
        return first;
    }

    /**
     * Definition for singly-linked list.
     * public class ListNode {
     *     int val;
     *     ListNode next;
     *     ListNode(int x) { val = x; }
     * }
     */
        public static ListNode addTwoNumbers(ListNode l1, ListNode l2) {
           ListNode dummy =new ListNode(-1);
           int carry = 0;
           ListNode prev = dummy;
           for(ListNode pa=l1 ,  pb=l2 ; pa!=null || pb!=null ;
            pa=pa==null?null : pa.next,
            pb=pb==null ? null : pb.next,
            prev=prev.next){
               final int ai=pa==null?0:pa.val;
               final int bi=pb==null?0:pb.val;
               final int value=(ai+bi+carry)%10;
               carry=(ai+bi+carry)/10;
               prev.next=new ListNode (value);
            }

            if(carry>0)
                prev.next=new ListNode (carry);
            return dummy.next;
    }
}

复制代码 代码如下:

会问字符串

看清有个别字符串是或不是为回文字符串,譬如racecarrace car都以回文字符串:

JavaScript

isPalindrome(“racecar”); // true isPalindrome(“race Car”); // true
function isPalindrome(word) { // Replace all non-letter chars with “”
and change to lowercase var lettersOnly =
word.toLowerCase().replace(/\s/g, “”); // Compare the string with the
reversed version of the string return lettersOnly ===
lettersOnly.split(“”).reverse().join(“”); }

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isPalindrome("racecar"); // true
isPalindrome("race Car"); // true
 
function isPalindrome(word) {
  // Replace all non-letter chars with "" and change to lowercase
  var lettersOnly = word.toLowerCase().replace(/\s/g, "");
 
  // Compare the string with the reversed version of the string
  return lettersOnly === lettersOnly.split("").reverse().join("");
}

36# Leetcode 302.Smallest Rectangle Enclosing Black Pixels

Evaluate Reverse Polish Notation

算算逆波兰(Poland)表明式(又叫后缀表明式)的值

” 2 ”,” 1 ”,” + ”, ”3”, ”* ” –>(2+1)*3–>9

用堆栈境遇运算符则把后面三个拿出来运算

public class Main {
    public static void main(String[] args) {
       String []tokens={"2", "1", "+", "3", "*"};
        System.out.print(evalRPN(tokens));
    }

    public static int evalRPN(String [] tokens){
        Stack<String> s = new Stack<>();
        if(tokens.length==1){
            return Integer.parseInt(tokens[0]);
        }
        for(String token:tokens){
            if(!isOperator(token)){
                s.push(token);
            }else {
                int y=Integer.parseInt(s.pop());
                int x=Integer.parseInt(s.pop());
                switch (token.charAt(0)){
                    case '+':x+=y;break;
                    case '-':x-=y;break;
                    case '*':x*=y;break;
                    case '/':x/=y;break;
                }
                s.push(String.valueOf(x));
            }
        }
        return Integer.parseInt(s.peek());
    }

    private static boolean isOperator(final String op){
        return op.length() == 1 && OPS.indexOf(op)!=-1;
    }

    private static String OPS = new String("+-*/");
}

今昔,要运用那一个函数12分的简便;大家得以用三种办法来发送数据:

诠释下怎么是 伊夫nt Bubbling 以及哪些防止

伊芙nt Bubbling
即指有个别事件不仅会接触当前因素,还会以嵌套顺序传递到父成分中。直观而言即是对此有些子元素的点击事件相同会被父成分的点击事件处理器捕获。幸免伊夫nt Bubbling 的格局能够行使event.stopPropagation() 或然 IE 9以下使用event.cancelBubble

40# LintCode: Maximum Number in Mountain Sequence

Given a mountain sequence of n integers which increase firstly and then
decrease, find the mountain top.

Example
Given nums = [1, 2, 4, 8, 6, 3] return 8
Given nums = [10, 9, 8, 7], return 10

public int mountainSequence(int[] nums) {
    if (nums.length == 0 || nums == null) {
        return -1;
    }
    int start = 0;
    int end = nums.length - 1;
    while (start + 1 < end) {
        int mid = start + (end - start) / 2;
        if (nums[mid] > nums[mid + 1]) {
            end = mid;
        } else {
            start = mid;
        }
    }
    return Math.max(nums[start], nums[end]);
}

Contains Duplicate II

Given an array of integers and an integer k, find out whether there are
two distinct indices i and j in the array such that nums[i] =
nums[j] and the absolute difference between i and j is at most k.

维护一个HashMap,key为整数,value为下标,将数组中的元素不断添加到这个Hashmap中,遇到重复时,计算下标距离;
用Integer.MAX_VALUE 设置为比较的初始值;
学会用HashMap是非常关键的。

public class LeetCode {
    public static void main(String[] args) {
        int[] nums = {1, 3, 5, 1,6};
        int k=3;
        System.out.print(containsNearbyDuplicate(nums,k));
    }

    public static boolean containsNearbyDuplicate(int[] nums, int k) {
        final Map<Integer,Integer> map = new HashMap<>();
        int min=Integer.MAX_VALUE;

        for(int i=0;i<nums.length;i++){
            if(map.containsKey(nums[i])){
                final int preIndex=map.get(nums[i]);
                final int gap = i-preIndex;
                min = Math.min(min,gap);
            }
            map.put(nums[i],i);
        }
        return min<=k;
    }
}

复制代码 代码如下:

数组去重

给定某冬辰数组,供给删减数组中的重复数字并且重回新的无重复数组。

JavaScript

// ES6 Implementation var array = [1, 2, 3, 5, 1, 5, 9, 1, 2, 8];
Array.from(new Set(array)); // [1, 2, 3, 5, 9, 8] // ES5
Implementation var array = [1, 2, 3, 5, 1, 5, 9, 1, 2, 8];
uniqueArray(array); // [1, 2, 3, 5, 9, 8] function uniqueArray(array)
{ var hashmap = {}; var unique = []; for(var i = 0; i <
array.length; i++) { // If key returns null (unique), it is evaluated as
false. if(!hashmap.hasOwnProperty([array[i]])) {
hashmap[array[i]] = 1; unique.push(array[i]); } } return unique; }

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// ES6 Implementation
var array = [1, 2, 3, 5, 1, 5, 9, 1, 2, 8];
 
Array.from(new Set(array)); // [1, 2, 3, 5, 9, 8]
 
 
// ES5 Implementation
var array = [1, 2, 3, 5, 1, 5, 9, 1, 2, 8];
 
uniqueArray(array); // [1, 2, 3, 5, 9, 8]
 
function uniqueArray(array) {
  var hashmap = {};
  var unique = [];
  for(var i = 0; i < array.length; i++) {
    // If key returns null (unique), it is evaluated as false.
    if(!hashmap.hasOwnProperty([array[i]])) {
      hashmap[array[i]] = 1;
      unique.push(array[i]);
    }
  }
  return unique;
}

3# Leetcode 167 Two Sum II – Input array is sorted

/** 
 *  Method one: Two points 一刷
 *    时间复杂度为O(n), 空间复杂度为O(1)。
 */
public int[] twoSum(int[] numbers, int target) {
    int start = 0;
    int end = numbers.length - 1;
    while (start < end) {
        if (numbers[start] + numbers[end] < target) {
            start ++;
        }
        else if(numbers[start] + numbers[end] > target) {
            end --;
        }
        else {
            break;
        }
    }
    return new int[]{start + 1, end + 1};
}

/**
 *     Method 2: Binary Search 一刷
 *     时间复杂度为O(logn), 空间复杂度为O(1)。
 */
public class Solution {
    public int[] twoSum(int[] numbers, int target) {
        int[] result = {0,0};
        int index1 = 0;
        int index2 = 0;

        for(int i = 0; i < numbers.length - 1; i++ ){
            index1 = i + 1;
            if(numbers[i] > target) {
                return result;
            }

            int gap = target - numbers[i];
            int start = i + 1;
            int end = numbers.length - 1;

            while(start + 1 < end){
                int mid = start + (end - start) / 2;
                if(numbers[mid] == gap) {
                    index2 = mid + 1;
                    result[0] = index1;
                    result[1] = index2;
                    return result;
                }
                if (numbers[mid] > gap) {
                    end = mid;
                }
                if (numbers[mid] < gap) {
                    start = mid;
                }
            }
            if (numbers[start] == gap) {
                result[0] = index1;
                result[1] = start + 1;
            }
            if (numbers[end] == gap) {
                result[0] = index1;
                result[1] = end + 1;
            }
        }
       return result;
    }
}

柒,把对象正是参数,来公司和改正函数
在现世Web开发中,对象最广泛的三个用途是把它们正是函数的参数。要铭记函数参数的那一个规则总是很窘迫的;可是,使用一个指标是老大有好处的,因为我们无需再担心参数的条条框框了。而且,它更有组织性,能够让用户更加好的知晓大家要做怎么样。那么些主意能够让您把目的正是参数,来公司和立异函数。例如:

数组交集

给定七个数组,须要求出三个数组的搅和,注意,交集中的元素应该是唯一的。

JavaScript

var firstArray = [2, 2, 4, 1]; var secondArray = [1, 2, 0, 2];
intersection(firstArray, secondArray); // [2, 1] function
intersection(firstArray, secondArray) { // The logic here is to create a
hashmap with the elements of the firstArray as the keys. // After that,
you can use the hashmap’s O(1) look up time to check if the element
exists in the hash // If it does exist, add that element to the new
array. var hashmap = {}; var intersectionArray = [];
firstArray.forEach(function(element) { hashmap[element] = 1; }); //
Since we only want to push unique elements in our case… we can
implement a counter to keep track of what we already added
secondArray.forEach(function(element) { if (hashmap[element] === 1) {
intersectionArray.push(element); hashmap[element]++; } }); return
intersectionArray; // Time complexity O(n), Space complexity O(n) }

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var firstArray = [2, 2, 4, 1];
var secondArray = [1, 2, 0, 2];
 
intersection(firstArray, secondArray); // [2, 1]
 
function intersection(firstArray, secondArray) {
  // The logic here is to create a hashmap with the elements of the firstArray as the keys.
  // After that, you can use the hashmap’s O(1) look up time to check if the element exists in the hash
  // If it does exist, add that element to the new array.
 
  var hashmap = {};
  var intersectionArray = [];
 
  firstArray.forEach(function(element) {
    hashmap[element] = 1;
  });
 
  // Since we only want to push unique elements in our case… we can implement a counter to keep track of what we already added
  secondArray.forEach(function(element) {
    if (hashmap[element] === 1) {
      intersectionArray.push(element);
      hashmap[element]++;
    }
  });
 
  return intersectionArray;
 
  // Time complexity O(n), Space complexity O(n)
}

27# Leetcode 50. Pow(x, n)

function sum_three_nums( ){
if(arguments.length!=3) throw new Error(‘received ‘ + arguments.length +
‘ parameters and should work with 3’);
}
sum_three_nums(23,43); //Return the error message
function sum_num(){
var total = 0;
for(var i=0;i<arguments .length;i++){
total+=arguments[i];
}
return total;
}
sum_num(2,34,45,56,56);

利用多个栈完成入队与出队

JavaScript

var inputStack = []; // First stack var outputStack = []; // Second
stack // For enqueue, just push the item into the first stack function
enqueue(stackInput, item) { return stackInput.push(item); } function
dequeue(stackInput, stackOutput) { // Reverse the stack such that the
first element of the output stack is the // last element of the input
stack. After that, pop the top of the output to // get the first element
that was ever pushed into the input stack if (stackOutput.length <=
0) { while(stackInput.length > 0) { var elementToOutput =
stackInput.pop(); stackOutput.push(elementToOutput); } } return
stackOutput.pop(); }

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var inputStack = []; // First stack
var outputStack = []; // Second stack
 
// For enqueue, just push the item into the first stack
function enqueue(stackInput, item) {
  return stackInput.push(item);
}
 
function dequeue(stackInput, stackOutput) {
  // Reverse the stack such that the first element of the output stack is the
  // last element of the input stack. After that, pop the top of the output to
  // get the first element that was ever pushed into the input stack
  if (stackOutput.length <= 0) {
    while(stackInput.length > 0) {
      var elementToOutput = stackInput.pop();
      stackOutput.push(elementToOutput);
    }
  }
 
  return stackOutput.pop();
}

35# Leetcode 410. Split Array Largest Sum

Given an array which consists of non-negative integers and an integer
m, you can split the array into m non-empty continuous subarrays.
Write an algorithm to minimize the largest sum among these m
subarrays.

Note:
If n is the length of array, assume the following constraints are
satisfied:

1 ≤ n ≤ 1000

1 ≤ m ≤ min(50, n)
Examples:

Input:
nums = [7,2,5,10,8]
m = 2
Output:
18

Explanation:
There are four ways to split nums into two subarrays.
The best way is to split it into [7,2,5] and [10,8],
where the largest sum among the two subarrays is only 18.

10,Boolean
只顾它们中间的区分,因为那会节约你调试脚本的时间。

认清是不是为 二 的指数值

JavaScript

isPowerOfTwo(4); // true isPowerOfTwo(64); // true isPowerOfTwo(1); //
true isPowerOfTwo(0); // false isPowerOfTwo(-1); // false // For the
non-zero case: function isPowerOfTwo(number) { // `&` uses the bitwise
n. // In the case of number = 4; the expression would be identical to:
// `return (4 & 3 === 0)` // In bitwise, 4 is 100, and 3 is 011. Using
&, if two values at the same // spot is 1, then result is 1, else 0. In
this case, it would return 000, // and thus, 4 satisfies are expression.
// In turn, if the expression is `return (5 & 4 === 0)`, it would be
false // since it returns 101 & 100 = 100 (NOT === 0) return number &
(number – 1) === 0; } // For zero-case: function
isPowerOfTwoZeroCase(number) { return (number !== 0) && ((number &
(number – 1)) === 0); }

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isPowerOfTwo(4); // true
isPowerOfTwo(64); // true
isPowerOfTwo(1); // true
isPowerOfTwo(0); // false
isPowerOfTwo(-1); // false
 
// For the non-zero case:
function isPowerOfTwo(number) {
  // `&` uses the bitwise n.
  // In the case of number = 4; the expression would be identical to:
  // `return (4 & 3 === 0)`
  // In bitwise, 4 is 100, and 3 is 011. Using &, if two values at the same
  // spot is 1, then result is 1, else 0. In this case, it would return 000,
  // and thus, 4 satisfies are expression.
  // In turn, if the expression is `return (5 & 4 === 0)`, it would be false
  // since it returns 101 & 100 = 100 (NOT === 0)
 
  return number & (number – 1) === 0;
}
 
// For zero-case:
function isPowerOfTwoZeroCase(number) {
  return (number !== 0) && ((number & (number – 1)) === 0);
}

 

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图片 1

12# Leetcode 153. Find Minimum in Rotated Sorted Array

Suppose an array sorted in ascending order is rotated at some pivot
unknown to you beforehand. (i.e., 0 1 2 4 5 6 7 might become 4 5 6 7 0
1 2).

Find the minimum element.

You may assume no duplicate exists in the array.

public class Solution {
    public int findMin(int[] nums) {
        if (nums == null || nums.length == 0) {
            return -1;
        }
        int start = 0;
        int end = nums.length - 1;
        int target = nums[nums.length - 1];

        while (start + 1 < end) {
            int mid = start + (end - start) / 2;
            if (nums[mid] <= target) {
                end = mid;
            }
            else {
                start = mid;
            }
        }
        if (nums[start] <= target) {
            return nums[start];
        } else {
            return nums[end];
        }
    }
}

复制代码 代码如下:

数组

19# Leetcode 230. Kth Smallest Element in a BST

陆,使用“arguments”对象来明白三个函数接收到了有点个参数
其一技能能够让你使用“arguments”对象来打听一个函数接收到了不怎么个参数。例如:

数字

24# Leetcode 300. Longest Increasing Subsequence

Given an unsorted array of integers, find the length of longest
increasing subsequence.

For example,
Given [10, 9, 2, 5, 3, 7, 101, 18],
The longest increasing subsequence is [2, 3, 7, 101], therefore the
length is 4. Note that there may be more than one LIS combination, it
is only necessary for you to return the length.

Your algorithm should run in O(n2) complexity.
Follow up: Could you improve it to O(n log n) time complexity?

” == ‘0’ // false
0 == ” // true
0 == ‘0’ // true
false == ‘false’ // false
false == ‘0’ // true
false == undefined // false
false == null // false
null == undefined // true
true == 1 // true
” == null // false
false == ” // true

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