leetcode
  • LeetCode Problems
  • Array
    • Array Partition I
    • Toeplitz Matrix
    • Find All Numbers Disappeared in an Array
    • Max Area of Island
    • Move Zeros
    • Two Sum II - Input array is sorted
    • Degree of an Array
    • Image Smoother
    • Positions of Large Groups
    • Missing Number
    • Maximum Product of Three Numbers
    • Min Cost Climbing Stairs
    • Longest Continuous Increasing Subsequence
    • Remove Element
    • Pascal's Triangle
    • Maximum Subarray
    • Largest Number At Least Twice of Others
    • Search Insert Position
    • Plus One
    • Find Pivot Index
    • Pascal's Triangle II
    • Two Sum
    • Maximize Distance to Closest Person
    • Maximum Average Subarray I
    • Remove Duplicates from Sorted Array
    • Magic Squares In Grid
    • Contains Duplicate II
    • Merge Sorted Array
    • Can Place Flowers
    • Shortest Unsorted Continuous Subarray
    • K-diff Pairs in an Array
    • Third Maximum Number
    • Rotate Array
    • Non-decreasing Array
    • Find All Duplicates in an Array
    • Teemo Attacking
    • Beautiful Arrangement II
    • Product of Array Except Self
    • Max Chunks To Make Sorted
    • Subsets
    • Best Time to Buy and Sell Stock with Transaction Fee
    • Combination Sum III
    • Find the Duplicate Number
    • Unique Paths
    • Rotate Image
    • My Calendar I
    • Spiral Matrix II
    • Combination Sum
    • Task Scheduler
    • Valid Triangle Number
    • Minimum Path Sum
    • Number of Subarrays with Bounded Maximum
    • Insert Delete GetRandom O(1)
    • Find Minimum in Rotated Sorted Array
    • Sort Colors
    • Find Peak Element
    • Subarray Sum Equals K
    • Subsets II
    • Maximum Swap
    • Remove Duplicates from Sorted Array II
    • Maximum Length of Repeated Subarray
    • Image Overlap
    • Length of Longest Fibonacci Subsequence
  • Contest
    • Binary Gap
    • Advantage Shuffle
    • Minimum Number of Refueling Stops
    • Reordered Power of 2
  • Dynamic Programming
    • Climbing Stairs
    • Range Sum Query - Immutable
    • Counting Bits
    • Arithmetic Slices
    • Palindromic Substrings
    • Minimum ASCII Delete Sum for Two Strings
    • Maximum Length of Pair Chain
    • Integer Break
    • Shopping Offers
    • Count Numbers with Unique Digits
    • 2 Keys Keyboard
    • Predict the Winner
    • Stone Game
    • Is Subsequence
    • Delete and Earn
    • Longest Palindromic Subsequence
    • Target Sum
    • Unique Binary Search Trees
    • Minimum Path Sum
    • Combination Sum IV
    • Best Time to Buy and Sell Stock with Cooldown
    • Largest Sum of Averages
    • Largest Plus Sign
    • Untitled
  • Invert Binary Tree
  • Intersection of Two Arrays
  • Surface Area of 3D Shapes
  • K Closest Points to Origin
  • Rotting Oranges
  • Smallest Integer Divisible by K
  • Duplicate Zeros
  • DI String Match
  • Implement Queue using Stacks
  • Increasing Order Search Tree
  • Reveal Cards In Increasing Order
  • Reshape the Matrix
  • Partition List
  • Total Hamming Distance
  • Validate Binary Search Tree
  • Decode Ways
  • Construct Binary Tree from Preorder and Inorder Traversal
  • Construct Binary Search Tree from Preorder Traversal
  • Design Circular Queue
  • Network Delay Time
  • Most Frequent Subtree Sum
  • Asteroid Collision
  • Binary Tree Inorder Traversal
  • Check If Word Is Valid After Substitutions
  • Construct Binary Tree from Preorder and Postorder Traversal
  • K-Concatenation Maximum Sum
Powered by GitBook
On this page
  • Description
  • Solutions
  • My solution
  • A better solution
  1. Array

Find All Numbers Disappeared in an Array

Description

Given an array of integers where 1 ≤ a[i] ≤ n (n = size of array), some elements appear twice and others appear once.

Find all the elements of [1, n] inclusive that do not appear in this array.

Could you do it without extra space and in O(n) runtime? You may assume the returned list does not count as extra space.

Example:

Input:
[4,3,2,7,8,2,3,1]

Output:
[5,6]

Solutions

My solution

class Solution {
public:
    vector<int> findDisappearedNumbers(vector<int>& nums) {
        int n = nums.size();
        int i = 0;
        while(i < n){
            if(nums[i] == i + 1 || nums[nums[i] - 1] == nums[i]){
                ++i;
            }else{
                swap(nums[i], nums[nums[i] - 1]);
            }
        }
        vector<int> ans;
        for(int j = 0; j < n; ++j){
            if(nums[j] != j + 1)
                ans.push_back(j + 1);
        }
        return ans;
    }
};

The running time is O(n). Proof:

We say that a number nums[i] is at its correct position if nums[i] == i + 1. After each swap statement, at least one number, i.e., nums[i], is put to its correct position. Since we can put at most n numbers to their correct positions and once a number is put to its correct position, it no longer moves. Thus, the swap statement is executed at most n times. And the ++i statement is also executed at most n times. So the running time of the while loop is O(n). The remaining is trivial.

A better solution

This solution is more efficient, though the time complexity is the same. It also modifies the input array, but the modification can be revert.

The idea to mark the numbers that appears in the array with negative values. Another similar idea is to mark these numbers by adding n(but overflow may occur).

class Solution {
public:
    vector<int> findDisappearedNumbers(vector<int>& nums) {
        int n = nums.size();
        // nums[i] < 0 <=> i+1 is in the array
        for(int i = 0; i < n; ++i){
            int idx = abs(nums[i]) - 1;
            if(nums[idx] > 0)
                nums[idx] = -nums[idx];
        }
        vector<int> ans;
        for(int i = 0; i < n; ++i){
            if(nums[i] > 0)
                ans.push_back(i + 1);
        }
        return ans;
    }
};
PreviousToeplitz MatrixNextMax Area of Island

Last updated 6 years ago