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looking for an optimal solution to finding pairs in an array base on certain condition in Javascript [duplicate]

Given array of n integers and given a number X, find all the unique pairs of elements (a,b), whose summation is equal to X.
The following is my solution, it is O(nLog(n)+n), but I am not sure whether or not it is optimal.
int main(void)
{
int arr [10] = {1,2,3,4,5,6,7,8,9,0};
findpair(arr, 10, 7);
}
void findpair(int arr[], int len, int sum)
{
std::sort(arr, arr+len);
int i = 0;
int j = len -1;
while( i < j){
while((arr[i] + arr[j]) <= sum && i < j)
{
if((arr[i] + arr[j]) == sum)
cout << "(" << arr[i] << "," << arr[j] << ")" << endl;
i++;
}
j--;
while((arr[i] + arr[j]) >= sum && i < j)
{
if((arr[i] + arr[j]) == sum)
cout << "(" << arr[i] << "," << arr[j] << ")" << endl;
j--;
}
}
}

There are 3 approaches to this solution:
Let the sum be T and n be the size of array
Approach 1:
The naive way to do this would be to check all combinations (n choose 2). This exhaustive search is O(n2).
Approach 2:
A better way would be to sort the array. This takes O(n log n)
Then for each x in array A,
use binary search to look for T-x. This will take O(nlogn).
So, overall search is O(n log n)
Approach 3 :
The best way
would be to insert every element into a hash table (without sorting). This takes O(n) as constant time insertion.
Then for every x,
we can just look up its complement, T-x, which is O(1).
Overall the run time of this approach is O(n).
You can refer more here.Thanks.

# Let arr be the given array.
# And K be the give sum
for i=0 to arr.length - 1 do
# key is the element and value is its index.
hash(arr[i]) = i
end-for
for i=0 to arr.length - 1 do
# if K-th element exists and it's different then we found a pair
if hash(K - arr[i]) != i
print "pair i , hash(K - arr[i]) has sum K"
end-if
end-for

Implementation in Java : Using codaddict's algorithm (Maybe slightly different)
import java.util.HashMap;
public class ArrayPairSum {
public static void main(String[] args) {
int []a = {2,45,7,3,5,1,8,9};
printSumPairs(a,10);
}
public static void printSumPairs(int []input, int k){
Map<Integer, Integer> pairs = new HashMap<Integer, Integer>();
for(int i=0;i<input.length;i++){
if(pairs.containsKey(input[i]))
System.out.println(input[i] +", "+ pairs.get(input[i]));
else
pairs.put(k-input[i], input[i]);
}
}
}
For input = {2,45,7,3,5,1,8,9} and if Sum is 10
Output pairs:
3,7
8,2
9,1
Some notes about the solution :
We iterate only once through the array --> O(n) time
Insertion and lookup time in Hash is O(1).
Overall time is O(n), although it uses extra space in terms of hash.

Solution in java. You can add all the String elements to an ArrayList of strings and return the list. Here I am just printing it out.
void numberPairsForSum(int[] array, int sum) {
HashSet<Integer> set = new HashSet<Integer>();
for (int num : array) {
if (set.contains(sum - num)) {
String s = num + ", " + (sum - num) + " add up to " + sum;
System.out.println(s);
}
set.add(num);
}
}

Python Implementation:
import itertools
list = [1, 1, 2, 3, 4, 5,]
uniquelist = set(list)
targetsum = 5
for n in itertools.combinations(uniquelist, 2):
if n[0] + n[1] == targetsum:
print str(n[0]) + " + " + str(n[1])
Output:
1 + 4
2 + 3

C++11, run time complexity O(n):
#include <vector>
#include <unordered_map>
#include <utility>
std::vector<std::pair<int, int>> FindPairsForSum(
const std::vector<int>& data, const int& sum)
{
std::unordered_map<int, size_t> umap;
std::vector<std::pair<int, int>> result;
for (size_t i = 0; i < data.size(); ++i)
{
if (0 < umap.count(sum - data[i]))
{
size_t j = umap[sum - data[i]];
result.push_back({data[i], data[j]});
}
else
{
umap[data[i]] = i;
}
}
return result;
}

Here is a solution witch takes into account duplicate entries. It is written in javascript and assumes array is sorted. The solution runs in O(n) time and does not use any extra memory aside from variable.
var count_pairs = function(_arr,x) {
if(!x) x = 0;
var pairs = 0;
var i = 0;
var k = _arr.length-1;
if((k+1)<2) return pairs;
var halfX = x/2;
while(i<k) {
var curK = _arr[k];
var curI = _arr[i];
var pairsThisLoop = 0;
if(curK+curI==x) {
// if midpoint and equal find combinations
if(curK==curI) {
var comb = 1;
while(--k>=i) pairs+=(comb++);
break;
}
// count pair and k duplicates
pairsThisLoop++;
while(_arr[--k]==curK) pairsThisLoop++;
// add k side pairs to running total for every i side pair found
pairs+=pairsThisLoop;
while(_arr[++i]==curI) pairs+=pairsThisLoop;
} else {
// if we are at a mid point
if(curK==curI) break;
var distK = Math.abs(halfX-curK);
var distI = Math.abs(halfX-curI);
if(distI > distK) while(_arr[++i]==curI);
else while(_arr[--k]==curK);
}
}
return pairs;
}
I solved this during an interview for a large corporation. They took it but not me.
So here it is for everyone.
Start at both side of the array and slowly work your way inwards making sure to count duplicates if they exist.
It only counts pairs but can be reworked to
find the pairs
find pairs < x
find pairs > x
Enjoy!

O(n)
def find_pairs(L,sum):
s = set(L)
edgeCase = sum/2
if L.count(edgeCase) ==2:
print edgeCase, edgeCase
s.remove(edgeCase)
for i in s:
diff = sum-i
if diff in s:
print i, diff
L = [2,45,7,3,5,1,8,9]
sum = 10
find_pairs(L,sum)
Methodology: a + b = c, so instead of looking for (a,b) we look for a = c -
b

Implementation in Java : Using codaddict's algorithm:
import java.util.Hashtable;
public class Range {
public static void main(String[] args) {
// TODO Auto-generated method stub
Hashtable mapping = new Hashtable();
int a[]= {80,79,82,81,84,83,85};
int k = 160;
for (int i=0; i < a.length; i++){
mapping.put(a[i], i);
}
for (int i=0; i < a.length; i++){
if (mapping.containsKey(k - a[i]) && (Integer)mapping.get(k-a[i]) != i){
System.out.println(k-a[i]+", "+ a[i]);
}
}
}
}
Output:
81, 79
79, 81
If you want duplicate pairs (eg: 80,80) also then just remove && (Integer)mapping.get(k-a[i]) != i from the if condition and you are good to go.

Just attended this question on HackerRank and here's my 'Objective C' Solution:
-(NSNumber*)sum:(NSArray*) a andK:(NSNumber*)k {
NSMutableDictionary *dict = [NSMutableDictionary dictionary];
long long count = 0;
for(long i=0;i<a.count;i++){
if(dict[a[i]]) {
count++;
NSLog(#"a[i]: %#, dict[array[i]]: %#", a[i], dict[a[i]]);
}
else{
NSNumber *calcNum = #(k.longLongValue-((NSNumber*)a[i]).longLongValue);
dict[calcNum] = a[i];
}
}
return #(count);
}
Hope it helps someone.

this is the implementation of O(n*lg n) using binary search implementation inside a loop.
#include <iostream>
using namespace std;
bool *inMemory;
int pairSum(int arr[], int n, int k)
{
int count = 0;
if(n==0)
return count;
for (int i = 0; i < n; ++i)
{
int start = 0;
int end = n-1;
while(start <= end)
{
int mid = start + (end-start)/2;
if(i == mid)
break;
else if((arr[i] + arr[mid]) == k && !inMemory[i] && !inMemory[mid])
{
count++;
inMemory[i] = true;
inMemory[mid] = true;
}
else if(arr[i] + arr[mid] >= k)
{
end = mid-1;
}
else
start = mid+1;
}
}
return count;
}
int main()
{
int arr[] = {1, 2, 3, 4, 5, 6, 7, 8, 9, 10};
inMemory = new bool[10];
for (int i = 0; i < 10; ++i)
{
inMemory[i] = false;
}
cout << pairSum(arr, 10, 11) << endl;
return 0;
}

In python
arr = [1, 2, 4, 6, 10]
diff_hash = {}
expected_sum = 3
for i in arr:
if diff_hash.has_key(i):
print i, diff_hash[i]
key = expected_sum - i
diff_hash[key] = i

Nice solution from Codeaddict. I took the liberty of implementing a version of it in Ruby:
def find_sum(arr,sum)
result ={}
h = Hash[arr.map {|i| [i,i]}]
arr.each { |l| result[l] = sum-l if h[sum-l] && !result[sum-l] }
result
end
To allow duplicate pairs (1,5), (5,1) we just have to remove the && !result[sum-l] instruction

Here is Java code for three approaches:
1. Using Map O(n), HashSet can also be used here.
2. Sort array and then use BinarySearch to look for complement O(nLog(n))
3. Traditional BruteForce two loops O(n^2)
public class PairsEqualToSum {
public static void main(String[] args) {
int a[] = {1,10,5,8,2,12,6,4};
findPairs1(a,10);
findPairs2(a,10);
findPairs3(a,10);
}
//Method1 - O(N) use a Map to insert values as keys & check for number's complement in map
static void findPairs1(int[]a, int sum){
Map<Integer, Integer> pairs = new HashMap<Integer, Integer>();
for(int i=0; i<a.length; i++){
if(pairs.containsKey(sum-a[i]))
System.out.println("("+a[i]+","+(sum-a[i])+")");
else
pairs.put(a[i], 0);
}
}
//Method2 - O(nlog(n)) using Sort
static void findPairs2(int[]a, int sum){
Arrays.sort(a);
for(int i=0; i<a.length/2; i++){
int complement = sum - a[i];
int foundAtIndex = Arrays.binarySearch(a,complement);
if(foundAtIndex >0 && foundAtIndex != i) //to avoid situation where binarySearch would find the original and not the complement like "5"
System.out.println("("+a[i]+","+(sum-a[i])+")");
}
}
//Method 3 - Brute Force O(n^2)
static void findPairs3(int[]a, int sum){
for(int i=0; i<a.length; i++){
for(int j=i; j<a.length;j++){
if(a[i]+a[j] == sum)
System.out.println("("+a[i]+","+a[j]+")");
}
}
}
}

A Simple program in java for arrays having unique elements:
import java.util.*;
public class ArrayPairSum {
public static void main(String[] args) {
int []a = {2,4,7,3,5,1,8,9,5};
sumPairs(a,10);
}
public static void sumPairs(int []input, int k){
Set<Integer> set = new HashSet<Integer>();
for(int i=0;i<input.length;i++){
if(set.contains(input[i]))
System.out.println(input[i] +", "+(k-input[i]));
else
set.add(k-input[i]);
}
}
}

A simple Java code snippet for printing the pairs below:
public static void count_all_pairs_with_given_sum(int arr[], int S){
if(arr.length < 2){
return;
}
HashSet values = new HashSet(arr.length);
for(int value : arr)values.add(value);
for(int value : arr){
int difference = S - value;
if(values.contains(difference) && value<difference){
System.out.printf("(%d, %d) %n", value, difference);
}
}
}

Another solution in Swift: the idea is to create an hash that store values of (sum - currentValue) and compare this to the current value of the loop. The complexity is O(n).
func findPair(list: [Int], _ sum: Int) -> [(Int, Int)]? {
var hash = Set<Int>() //save list of value of sum - item.
var dictCount = [Int: Int]() //to avoid the case A*2 = sum where we have only one A in the array
var foundKeys = Set<Int>() //to avoid duplicated pair in the result.
var result = [(Int, Int)]() //this is for the result.
for item in list {
//keep track of count of each element to avoid problem: [2, 3, 5], 10 -> result = (5,5)
if (!dictCount.keys.contains(item)) {
dictCount[item] = 1
} else {
dictCount[item] = dictCount[item]! + 1
}
//if my hash does not contain the (sum - item) value -> insert to hash.
if !hash.contains(sum-item) {
hash.insert(sum-item)
}
//check if current item is the same as another hash value or not, if yes, return the tuple.
if hash.contains(item) &&
(dictCount[item] > 1 || sum != item*2) // check if we have item*2 = sum or not.
{
if !foundKeys.contains(item) && !foundKeys.contains(sum-item) {
foundKeys.insert(item) //add to found items in order to not to add duplicated pair.
result.append((item, sum-item))
}
}
}
return result
}
//test:
let a = findPair([2,3,5,4,1,7,6,8,9,5,3,3,3,3,3,3,3,3,3], 14) //will return (8,6) and (9,5)

My Solution - Java - Without duplicates
public static void printAllPairSum(int[] a, int x){
System.out.printf("printAllPairSum(%s,%d)\n", Arrays.toString(a),x);
if(a==null||a.length==0){
return;
}
int length = a.length;
Map<Integer,Integer> reverseMapOfArray = new HashMap<>(length,1.0f);
for (int i = 0; i < length; i++) {
reverseMapOfArray.put(a[i], i);
}
for (int i = 0; i < length; i++) {
Integer j = reverseMapOfArray.get(x - a[i]);
if(j!=null && i<j){
System.out.printf("a[%d] + a[%d] = %d + %d = %d\n",i,j,a[i],a[j],x);
}
}
System.out.println("------------------------------");
}

This prints the pairs and avoids duplicates using bitwise manipulation.
public static void findSumHashMap(int[] arr, int key) {
Map<Integer, Integer> valMap = new HashMap<Integer, Integer>();
for(int i=0;i<arr.length;i++)
valMap.put(arr[i], i);
int indicesVisited = 0;
for(int i=0;i<arr.length;i++) {
if(valMap.containsKey(key - arr[i]) && valMap.get(key - arr[i]) != i) {
if(!((indicesVisited & ((1<<i) | (1<<valMap.get(key - arr[i])))) > 0)) {
int diff = key-arr[i];
System.out.println(arr[i] + " " +diff);
indicesVisited = indicesVisited | (1<<i) | (1<<valMap.get(key - arr[i]));
}
}
}
}

I bypassed the bit manuplation and just compared the index values. This is less than the loop iteration value (i in this case). This will not print the duplicate pairs and duplicate array elements also.
public static void findSumHashMap(int[] arr, int key) {
Map<Integer, Integer> valMap = new HashMap<Integer, Integer>();
for (int i = 0; i < arr.length; i++) {
valMap.put(arr[i], i);
}
for (int i = 0; i < arr.length; i++) {
if (valMap.containsKey(key - arr[i])
&& valMap.get(key - arr[i]) != i) {
if (valMap.get(key - arr[i]) < i) {
int diff = key - arr[i];
System.out.println(arr[i] + " " + diff);
}
}
}
}

in C#:
int[] array = new int[] { 1, 5, 7, 2, 9, 8, 4, 3, 6 }; // given array
int sum = 10; // given sum
for (int i = 0; i <= array.Count() - 1; i++)
if (array.Contains(sum - array[i]))
Console.WriteLine("{0}, {1}", array[i], sum - array[i]);

One Solution can be this, but not optimul (The complexity of this code is O(n^2)):
public class FindPairsEqualToSum {
private static int inputSum = 0;
public static List<String> findPairsForSum(int[] inputArray, int sum) {
List<String> list = new ArrayList<String>();
List<Integer> inputList = new ArrayList<Integer>();
for (int i : inputArray) {
inputList.add(i);
}
for (int i : inputArray) {
int tempInt = sum - i;
if (inputList.contains(tempInt)) {
String pair = String.valueOf(i + ", " + tempInt);
list.add(pair);
}
}
return list;
}
}

A simple python version of the code that find a pair sum of zero and can be modify to find k:
def sumToK(lst):
k = 0 # <- define the k here
d = {} # build a dictionary
# build the hashmap key = val of lst, value = i
for index, val in enumerate(lst):
d[val] = index
# find the key; if a key is in the dict, and not the same index as the current key
for i, val in enumerate(lst):
if (k-val) in d and d[k-val] != i:
return True
return False
The run time complexity of the function is O(n) and Space: O(n) as well.

public static int[] f (final int[] nums, int target) {
int[] r = new int[2];
r[0] = -1;
r[1] = -1;
int[] vIndex = new int[0Xfff];
for (int i = 0; i < nums.length; i++) {
int delta = 0Xff;
int gapIndex = target - nums[i] + delta;
if (vIndex[gapIndex] != 0) {
r[0] = vIndex[gapIndex];
r[1] = i + 1;
return r;
} else {
vIndex[nums[i] + delta] = i + 1;
}
}
return r;
}

less than o(n) solution will be=>
function(array,k)
var map = {};
for element in array
map(element) = true;
if(map(k-element))
return {k,element}

Solution in Python using list comprehension
f= [[i,j] for i in list for j in list if j+i==X];
O(N2)
also gives two ordered pairs- (a,b) and (b,a) as well

I can do it in O(n). Let me know when you want the answer. Note it involves simply traversing the array once with no sorting, etc... I should mention too that it exploits commutativity of addition and doesn't use hashes but wastes memory.
using System;
using System.Collections.Generic;
/*
An O(n) approach exists by using a lookup table. The approach is to store the value in a "bin" that can easily be looked up(e.g., O(1)) if it is a candidate for an appropriate sum.
e.g.,
for each a[k] in the array we simply put the it in another array at the location x - a[k].
Suppose we have [0, 1, 5, 3, 6, 9, 8, 7] and x = 9
We create a new array,
indexes value
9 - 0 = 9 0
9 - 1 = 8 1
9 - 5 = 4 5
9 - 3 = 6 3
9 - 6 = 3 6
9 - 9 = 0 9
9 - 8 = 1 8
9 - 7 = 2 7
THEN the only values that matter are the ones who have an index into the new table.
So, say when we reach 9 or equal we see if our new array has the index 9 - 9 = 0. Since it does we know that all the values it contains will add to 9. (note in this cause it's obvious there is only 1 possible one but it might have multiple index values in it which we need to store).
So effectively what we end up doing is only having to move through the array once. Because addition is commutative we will end up with all the possible results.
For example, when we get to 6 we get the index into our new table as 9 - 6 = 3. Since the table contains that index value we know the values.
This is essentially trading off speed for memory.
*/
namespace sum
{
class Program
{
static void Main(string[] args)
{
int num = 25;
int X = 10;
var arr = new List<int>();
for(int i = 0; i <= num; i++) arr.Add((new Random((int)(DateTime.Now.Ticks + i*num))).Next(0, num*2));
Console.Write("["); for (int i = 0; i < num - 1; i++) Console.Write(arr[i] + ", "); Console.WriteLine(arr[arr.Count-1] + "] - " + X);
var arrbrute = new List<Tuple<int,int>>();
var arrfast = new List<Tuple<int,int>>();
for(int i = 0; i < num; i++)
for(int j = i+1; j < num; j++)
if (arr[i] + arr[j] == X)
arrbrute.Add(new Tuple<int, int>(arr[i], arr[j]));
int M = 500;
var lookup = new List<List<int>>();
for(int i = 0; i < 1000; i++) lookup.Add(new List<int>());
for(int i = 0; i < num; i++)
{
// Check and see if we have any "matches"
if (lookup[M + X - arr[i]].Count != 0)
{
foreach(var j in lookup[M + X - arr[i]])
arrfast.Add(new Tuple<int, int>(arr[i], arr[j]));
}
lookup[M + arr[i]].Add(i);
}
for(int i = 0; i < arrbrute.Count; i++)
Console.WriteLine(arrbrute[i].Item1 + " + " + arrbrute[i].Item2 + " = " + X);
Console.WriteLine("---------");
for(int i = 0; i < arrfast.Count; i++)
Console.WriteLine(arrfast[i].Item1 + " + " + arrfast[i].Item2 + " = " + X);
Console.ReadKey();
}
}
}

I implemented logic in Scala with out a Map. It gives duplicate pairs since the counter loops thru entire elements of the array. If duplicate pairs are needed, you can simply return the value pc
val arr = Array[Int](8, 7, 2, 5, 3, 1, 5)
val num = 10
var pc = 0
for(i <- arr.indices) {
if(arr.contains(Math.abs(arr(i) - num))) pc += 1
}
println(s"Pairs: ${pc/2}")
It is working with duplicates values in the array as well.

GOLANG Implementation
func findPairs(slice1 []int, sum int) [][]int {
pairMap := make(map[int]int)
var SliceOfPairs [][]int
for i, v := range slice1 {
if valuei, ok := pairMap[v]; ok {
//fmt.Println("Pair Found", i, valuei)
SliceOfPairs = append(SliceOfPairs, []int{i, valuei})
} else {
pairMap[sum-v] = i
}
}
return SliceOfPairs
}

function findPairOfNumbers(arr, targetSum) {
arr = arr.sort();
var low = 0, high = arr.length - 1, sum, result = [];
while(low < high) {
sum = arr[low] + arr[high];
if(sum < targetSum)
low++;
else if(sum > targetSum)
high--;
else if(sum === targetSum) {
result.push({val1: arr[low], val2: arr[high]});
high--;
}
}
return (result || false);
}
var pairs = findPairOfNumbers([1,2,3,4,5,6,7,8,9,0], 7);
if(pairs.length) {
console.log(pairs);
} else {
console.log("No pair of numbers found that sums to " + 7);
}

The algorithm problem: Unique Paths III. Using backtracing pattern in javascript and not work

On a 2-dimensional grid, there are 4 types of squares:
1 represents the starting square.  There is exactly one starting square.
2 represents the ending square.  There is exactly one ending square.
0 represents empty squares we can walk over.
-1 represents obstacles that we cannot walk over.
Return the number of 4-directional walks from the starting square to the ending square, that walk over every non-obstacle square exactly once.
source：力扣（LeetCode）
link：https://leetcode-cn.com/problems/unique-paths-iii
i'm trying to use backtrack pattern to solve this problem
here is my code
/**
* #param {number[][]} grid
* #return {number}
*/
var uniquePathsIII = function(grid) {
let m = grid.length,
n = grid[0].length;
let start, targetIndex1,targetIndex2;
let res = 0;
let zero_counts = 0;
for(let i = 0; i < m; i++){
for(let j = 0; j < n; j++){
if(grid[i][j] == 1){
start = [i,j]
}
else if(grid[i][j] == 0){
zero_counts += 1;
}
else if(grid[i][j] == 2){
targetIndex1 = i;
targetIndex2 = j;
}
}
}
const backtrace = (i, j, zero_count) => {
if( i < 0 || i >= m ||
j < 0 || j >= n ||
grid[i][j] == -1 || zero_count < 0)
{
return;
}
if(i == targetIndex1 && j == targetIndex2 ){
if(zero_count == 0)
{
console.log("yes")
res += 1;
}
return
}
grid[i][j] = -1;
backtrace(i+1, j, zero_count - 1)
backtrace(i-1, j, zero_count - 1)
backtrace(i, j+1, zero_count - 1)
backtrace(i, j-1, zero_count - 1)
grid[i][j] = 0;
}
backtrace(start[0], start[1], zero_counts);
return res;
};
test sample:
[[1,0,0,0],[0,0,0,0],[0,0,2,-1]]
expect result:
2
acutal result:
0

Perhaps a simpler solution is to use Depth First Search to solve Unique Paths III, as shown here.
The concept is that you take a point and then traverse in all directions until you hit an obstacle.
The guts are as follows:
int totalPaths = dfs(grid, x+1, y, zero) +
dfs(grid, x, y+1, zero) +
dfs(grid, x-1, y, zero) +
dfs(grid, x, y-1, zero);

Trying to multiply the first two numbers that results to a particular number, is there way i can do this without using nested loops?

Here is the full solution, please is there much better ways to go about this
the question is getting total number of squares in a box but in the inverse way, for example the normal question is 2,9 and the total number of available squares will be 26. but i was given the question in another way such that 26 will be given and im to find all the possible ways m and n can be arranged so the total number of squares will be the given question, which is 26
The code actually works but i need a faster way to do this.
const n = 26;
function count(m, n) {
if (n < m) {
const temp = n;
n = m;
m = temp;
}
return m * (m + 1) * (2 * m + 1) /
6 + (n - m) * m * (m + 1) / 2;
}
const arr = [];
const len = n + 1;
for (let i = 1; i < len; i++) {
if(i<len/2) {
}
for (let b = 1; b < len; b++) {
if (i === 1) {
arr.push(`${i} ${n}`);
break;
} else if (i === n) {
arr.push(`${n} 1`);
break;
} else {
const sum = count(i, b);
if (sum == n) {
arr.push(`${i} ${b}`);
break;
}
}
}
}
const arrLength = arr.length;
console.log(arrLength); //shows the length of the array
for (let g = 0; g < arrLength; g++) {
console.log(arr[g]); // shows each ways it can be arranged to give 26
}

Find the largest palindrome made from the product of two 3-digit numbers - Javascript

Can anyone tell me what's wrong with the code. Find the largest palindrome made from the product of two 3-digit numbers.
function largestPalindrome(){
for(var i =999; i>100; i--){
for(var j = 999; j>100; j--){
var mul = j*i;
if(isPalin(mul)){
return i * j;
}
}
}
}
function isPalin(i){
return i.toString() == i.toString().split("").reverse().join("");
}
console.log(largestPalindrome());
This answer was close to my question
but still i feel the way i am doing the loop it should return me the largest product.

Yours doesn't work properly since it checks 999*999, then 999*998, then 999*997 until it reaches about 999*583. While it doesn't check 997*995 or something closer to the top
which generates a larger number
function largestPalindrome(){
var arr = [];
for(var i =999; i>100; i--){
for(var j = 999; j>100; j--){
var mul = j*i;
if(isPalin(mul)){
arr.push(j * i);
}
}
}
return Math.max.apply(Math, arr);
}
function isPalin(i){
return i.toString() == i.toString().split("").reverse().join("");
}
console.log(largestPalindrome());
Here is another approach, store all palindrome generated by 3 numbers in an array, then use Math.max on the array to get the largest palindrome

I think if you apply maths to the problem you can decrease the guesswork really significantly.
I will write the three digit numbers as 1000 - a and 1000 - b which means the palindrome is 1 000 000 - 1000(a+b) + ab.
First, let's find solutions where ab < 1000. Then the three leftmost digits are 1000 - (a+b) and the three rightmost digits are ab.
Then I will say this is a palindrome with digits x,y,z:
100x+10y+z=ab
100z+10y+x=1000-a-b
thus
99x-99z = ab+a+b-1000
x-z = 1/99(ab+a+b-10)-10
So then (ab+a+b-10) is divisible by 99 and we also know that x and z being digits the left side is between -9 and 0 (the whole shebang is symmetrical so we can presume x <= z) so then 1/99(ab+a+b-10) is between 1 and 9. We can rewrite ab+a+b-10 as ab+a+b+1-11=99p so (a+1)(b+1)=99p+11=11*(9p+1) where p runs between 1 and 9. That's really easy:
for ($p = 1; $p <= 9; $p++) {
$n = 9 * $p + 1;
// This could be vastly optimized further.
for ($j = 1; $j <= $n; $j++) {
if ($n % $j === 0) {
$a = 1001 - $n / $j;
$b = 1001 - 11 * $j;
$test = $a * $b;
if (strrev($test) === (string) $test) {
print "$a $b " . $a * $b . "\n";
}
}
}
}
Now this prints only one solution which is the correct one.
Now we know 906609 is a solution so then is there a solution where ab > 1000 and 1000(a+b) - ab < 93391 ? There is not :)

As explained in #VisioN's comment:
995*583 = 580085 is a palindrome.
993*913 = 906609 is also a (larger) palindrome.
Your code checks 995*583 before 993*913 and exits at the first palindrome found, so it doesn't return the largest palindrome.
Solution: get the largest palindromes starting from 999*999 = 998001 downwards and check if they can be written as xyz*abc.
Or simply use the accepted solution from the question you linked :). Your solution, but instead of returning when you find the first palindrome, check if it is larger than the largest one already found, in which case you need to replace it. You can stop as soon as the largest palindrome is larger than i*999.

A bit more optimized version with comments included. Notice, there is no need of fast return, just store the max and optimize the cycles to not recalculate j*i if i*j has already been checked.
function largestPalindrome() {
var max = 0;
// not using i >= 100 since 100*100 is not palindrome! :)
for (var i = 999; i > 100; i--) {
// because i * j === j * i, no need of both i and j
// to count down from 999
for (var j = i; j > 100; j--) {
var mul = j * i;
if (isPalin(mul) && mul > max) {
max = i * j;
}
}
}
return max;
}
function isPalin(i) {
// adding empty string to i instead using of .toString
// avoids unnecessary wrapping in String object on the left side
i = '' + i;
// don't rely on ==, use === instead
return i === i.split("").reverse().join("");
}
console.log(largestPalindrome());

Suggesting a solution using underscore.js. First, find all palindromes and then loop through them starting from the largest one and return the one which has two 3-digit prime factors.
function isPalindrome(num) {
var str = num.toString();
return str.split('').reverse().join('') === str;
}
function palindromes() {
var max = 999 * 999;
var min = 100 * 100;
return _.select(_.range(max, min, -1), isPalindrome);
}
palindromes().find(function (x) {
if (_.find(_.range(999, 100, -1), function (y) {
return (x % y === 0 && y != x / y && x / y < 1000) ? true : false;
})) return true;
})

#define MAX(a, b) ((a) > (b) ? (a) : (b))
int largestPalindrome()
{
int ret = 0;
for (int i = 999; i > 100; --i)
{
int jLimit = MAX(ret / i, 100);
for (int j = i; j > jLimit; --j)
{
int ans = i * j;
if (isPalin(ans))
{
ret = MAX(ans, ret);
}
}
}
return ret;
}
Reasons explained above.
We can recompute the range of j when we find a palindrome product.This should be faster.

The above solution will work perfectly fine but we will have issue ONLY when we try to find-out what are those 2 numbers (i = 913 and j = 993)
I will just modify the solution proposed by Azder
int max = 0;
int no1 = 0;
int no2 = 0;
// not using i >= 100 since 100*100 is not palindrome! :)
for (var i = 999; i > 100; i--) {
// because i * j === j * i, no need of both i and j
// to count down from 999
for (var j = i; j > 100; j--) {
var mul = j * i;
if (isPalin(mul)) {
if ((i+j) > max) {
max = i+j;
no1 = i; no2 = j;
}
}
}
}
//Now we can get the 2 numbers (no1=993 and no2=913)
return (no1*no2);

This is how I did it. I used the old fashioned way to check for a palindrome. It appears to run faster on my computer but I may be wrong. Pushing to an array, as in the above post, was definitely very slow on my computer. Noticeable lag at the console. I would recommend just checking to see if your product is greater than your current max, if it is, store that instead of pushing everything to an array. Please feel free to correct me if I'm wrong. Much appreciated.
//should find the largest palindrome made from the product of two 3 digit numbers
var largestPalindrome = function() {
var max = 0,
product = 0;
for (var num1 = 999; num1 >= 100; num1--) {
for (var num2 = 999; num2 >= 100; num2--) {
product = num1 * num2;
product > max && isPalindrome(product.toString()) ? max = product : 0;
}
}
return max;
};
//check to see if product is a palindrome
var isPalindrome = function(product) {
var palindromeCheck = true;
for (var i = 0; i < product.length / 2; i++) {
if (product[i] != product[product.length - i - 1])
palindromeCheck = false;
}
return palindromeCheck;
//return product === product.split("").reverse().join("");
};

I think you can go for code given at this link
http://www.mathblog.dk/project-euler-problem-4/
As this save your CPU cycle from multiplication, which is quite costly operation.
Well even in this you can make some more to make to make it more like, you can modify its while loop a bit
while (!found) {
firstHalf--;
palin = makePalindrome(firstHalf);
for (int i = 999; i > 99; i--) {
if ((palin / i) > 999 || i*i < palin) {
break;
}
if ((palin % i == 0)) {
found = true;
factors[0] = palin / i;
factors[1] = i;
break;
}
}
}
So here instead of moving from i=999 : 100, we can write it as i=sqrt(palin):100, as you can find factorial of number within its square root. Refer link How to find Number is prime number or not!
And also you can change if(condition) to if(!(palin%i)) as comparing with zero is usually not considered a good practice also comparing takes more CPU cycle compared to your simple negating bits.

instead of creating an Array or ArrayList to store all palindromes, I just created another variable max and stored highest valued palindrome in it.
My code is in Java, but you can understand the logic from it.
Here is my code to better explain what I said (read comments):
package euler;
import java.util.ArrayList; import java.util.Collections;
public class Problem4 {
public static void main (String[] args)
{
int product=0;
int max=0;
for(int i=999;i>100;i--)
{
for (int j=i;j>100;j--)
{
product=i*j;
if(isPalindrome(product))
{
//Just store maximum value of product.
//Following if loop is required in your code,in place of return i*j;
if(product>max)
{ max=product; }
}
}
}
System.out.println(max);
}
//might be inefficient to create StringBuilder and again String to compare.
public static boolean isPalindrome(int product)
{
boolean isPalindrome=false;
StringBuilder temp = new StringBuilder(Integer.toString(product)).reverse();
if(temp.toString().equals(Integer.toString(product)))
{
isPalindrome=true;
}
return isPalindrome;
}
}
What you are doing is returning and breaking out of the loop as soon as you get the first palindrome. Which in your case is not the maximum value palindrome.
Instead use an if condition and keep a track of maximum values and let the loop continue till end.
I have added the if condition that lets the loop running and registers the value.
Got the correct answer from this code.
PS. Thanks Xan for your input. I guess I could've explained it better first time.

I have seen a lot of posts for this question, this is the solution that i have come up with:
Smallest number that is multiple of two 3 digits number is 10000(100*100)
Largest number that is multiple of two 3 digits number is 998001(999*999)
Our palindrome lies between these two number, write a program to loop through these number and whenever you get a palindrome check whether its perfectly divisible by a 3 digit number and quotient is also a 3 digit number.
Below is my program in C#, the last number that it prints is our required answer, enjoy.
using System;
using System.Collections.Generic;
using System.Linq;
using System.Text.RegularExpressions;
using System.Collections;
namespace E
{
public class Program
{
public static void Main(string[] args)
{
//Your code goes here
for(int i=10000;i<=998001;i++)
{
string s1 = i.ToString();
char[] array = s1.ToCharArray();
Array.Reverse(array);
string s2 = new String(array);
if(s1==s2)
{
for(int j=100;j<=999;j++)
{
if(i%j==0 && i/j <= 999)
{
System.Console.WriteLine(i);
continue;
}
}
}
}
System.Console.WriteLine("done");
}
}
}

I believe this should be optimal
#include <functional>
#include <algorithm>
#include <iostream>
using namespace std;
template <typename T>
bool IsPalindrome(const T num) {
T reverse = 0;
T n = num;
while (n > 0) {
reverse = (reverse * 10) + n % 10;
n /= 10;
}
return reverse == num;
}
template <typename T = long long int>
T LongestPalindromeFromProductOfNDigitNums(int n) {
T result = 0, val = 0, max_n_digit_num = std::pow(10, n)-1,
least_n_digit_num = std::pow(10, n-1);
int n_checks = 0;
for (T i = max_n_digit_num; i >= least_n_digit_num; --i) {
if ((i*i) < result) {//found the highest palindrome
break;
}
for (T j = i; j >= least_n_digit_num; --j) {
val = i*j;
++n_checks;
if (val < result) // any product i*j for the value of 'j' after this will be less than result
break;
if (IsPalindrome(val)) {
if (val > result)
result = val;
break; // whenever a palindrome is found break since we only need highest one
}
}
}
std::cout << " Total num of checks = " << n_checks << std::endl;
return result;
}
int main() {
int n = 3;
std::cout << " LongestPalindromeFromProductOfNDigitNums for n = "
<< n << " is " << LongestPalindromeFromProductOfNDigitNums(n) << std::endl;
n = 4;
std::cout << " LongestPalindromeFromProductOfNDigitNums for n = "
<< n << " is " << LongestPalindromeFromProductOfNDigitNums(n) << std::endl;
return 0;
}
http://ideone.com/WoNSJP

Swift 3:
// my approach is to make 6-digit palindrome first and then
// check if I can divide it by 3-digit number
// (you can see some visual listing at the end of the code)
// execution time on my laptop is around: 2.75409698486328 sec
import Foundation
func maxPalindrom() -> Int {
var result = 999999
var i = 9
var j = 9
var k = 9
while true {
while true {
while true {
print("in K loop: \(result) k = \(k)")
if isDivisible(number: result) {
return result
}
if k <= 0 {
k = 9
result += 9900
break
}
result -= 1100
k -= 1
}
print("in J loop: \(result)")
if isDivisible(number: result) {
return result
}
if j < 0 {
j = 9
result += 90090
break
}
result -= 10010
j -= 1
}
print("in I loop: \(result)")
if isDivisible(number: result) {
return result
}
if i < 0 {
break
}
result -= 100001
i -= 1
}
if result == 100001 {
return -1
}
return -1
}
func isDivisible(number: Int) -> Bool {
var i = 999
while true {
if number % i == 0 && number / i < 999 {
return true
}
if i < 500 {
return false
}
i -= 1
}
}
let start = NSDate()
print(maxPalindrom()) // 906609
let end = NSDate()
print("executio time: \(end.timeIntervalSince(start as Date)) sec") // ~ execution time: 2.75409698486328 sec
//in K loop: 999999 k = 9
//in K loop: 998899 k = 8
//in K loop: 997799 k = 7
//in K loop: 996699 k = 6
//in K loop: 995599 k = 5
//in K loop: 994499 k = 4
//in K loop: 993399 k = 3
//in K loop: 992299 k = 2
//in K loop: 991199 k = 1
//in K loop: 990099 k = 0
//in J loop: 999999
//in K loop: 989989 k = 9
//in K loop: 988889 k = 8
//in K loop: 987789 k = 7
//in K loop: 986689 k = 6
//in K loop: 985589 k = 5
//in K loop: 984489 k = 4
//in K loop: 983389 k = 3
.....

Most of the answers here are correct. If you want to save going through 900*900 loops, you can just loop through all palindromes between 10000 and 998001 and find if they are divisible by 3 digit number.
static void largestpalindromeproduct(){
int a=999,b=999,c=a*b,loopcounter=0;
while(c>10000){
loopcounter++;
c--;
if(isPalindrome(c))
if(isDivisible(c))
break;
}
System.out.println(" largest : " + c+ "\nloops:"+ loopcounter);
}
static boolean isDivisible(int n){
int a=999;
while(a>=100){
if(n%a==0){
if(secondDividerIs3Digit(n,a))
return true;
}
a--;
}
return false;
}
static boolean secondDividerIs3Digit(int n, int a){
Integer b=n/a;
if(b.toString().length()==3)
return true;
return false;
}
static boolean isPalindrome(int n){
Integer i=new Integer(n);
String p=i.toString();
StringBuffer s=new StringBuffer(i.toString());
s.reverse();
if(p.equals(s.toString()))
return true;
return false;
}

As a very simple solution, this one works
public class LargestPallendrome {
public static void main(String[] args) {
int a = 999;
int b = 999;
long max = 0;
while (a > 100) {
long num = a * b;
if (checkPallendrome(num)) {
if (num > max)
max = num;
}
if (b >= 100)
b--;
else {
a--;
b = 999;
}
}
System.out.println(max);
}
public static boolean checkPallendrome(long num) {
String a = num + "";
String b = new StringBuffer(num + "").reverse().toString();
if (a.equals(b))
return true;
return false;
}
}

Another Simple Solution in JavaScript
function reverseNumber(n)
{
n = n + "";
return n.split("").reverse().join("");
}
function palindrom(){
var r= 1 , y =1;
var largest = 0;
while(r <= 1000){
var num1 = r;
var num2 = 0;
while(num1 <= 1000 && num2 <= num1){
product = num1 * num2;
if (product == reverseNumber(product)){
console.log(`${num1} x ${num2} = ${product}`);
if(product > largest){
largest = product;
}
}
num1 = num1 + 1;
num2= num2 + 1;
}
r++;
}
console.log(``)
console.log(`The largest is ${largest}`);
}
console.log(palindrom());

public static void main(String[] args) {
int tempAns = 0;
int max = 999;
for (int i = 100; i <= max; i++) {
for (int j = max; j >= i; j--) {
if (findPalindrome(i * j) && (i * j) > tempAns) {
System.out.println("Palindrome: " + j + " * " + i + " = " + j * i);
tempAns = i * j;
}
}
}
}
private static boolean findPalindrome(int n) {
String nString = String.valueOf(n);
int j = 0;
int stringLength = nString.length() - 1;
for (int i = stringLength; i >= 0; i--) {
if (nString.charAt(j) == nString.charAt(i)) {
if (i == 0) {
return true;
}
j++;
} else if (nString.charAt(j) != nString.charAt(i)) {
return false;
}
}
return false;
}

This is better because its using O(N) time complexity to find all the palindrome (As calculating palindrome of a six digit no is constant) and O(N2) nearly to find the actual palindrome that too worst case the moment its finding its first no we don't have to do any more calculation and here we are actually using the worst case on possible palindromic no. So I think its better
package ProjectEuler;
import java.util.ArrayList;
import java.util.Arrays;
public class Largest_Palindrome_Product {
public static void main(String[] args) {
int count=0;
for(int i=10000;i<998002;i++) {
int x=i,c=0;
while(x!=0) {
c=c*10+x%10;
x/=10;
}
if(c==i) {
count++;
}
}
int a[]=new int[count],count1=0;
for(int i=10000;i<998002;i++) {
int x=i,c=0;
while(x!=0) {
c=c*10+x%10;
x/=10;
}
if(c==i) {
a[count1]=i;
count1++;
}
}
Arrays.sort(a);
tp:for(int i=count-1;i>=0;i--)
{
for(int j=999;j>100;j--)
if(a[i]%j==0&&a[i]/j<=999) {
System.out.println(a[i]+" "+j+" "+a[i]/j);
break tp;
}
}
}
}

This is how I did it in Javascript. Simple & easy!
let num1 = 999;
let num2 = 999;
let arr = [];
function check(x, y)
{
if(String(x*y) == String(x*y).split("").reverse().join(""))
{
return true;
}
return false;
}
for(let i=0; i<999999; i++)
{
if(check(num1, num2))
{
arr.push(num1*num2);
num1--;
num2 = num1+1;
}
num2--;
}
console.log(arr.sort((x, y) => y-x)[0]);

I check it some times with random.randint. In python 3.7.1, you should run it with CMD and after 20 sec you will get the right answer.
import random
x,y,z,a,b=100,100,' ','',0
while 100<=x<=999 and 100<=y<=999:
a=x*y
x=random.randint(900,999)
y=random.randint(900,999)
print(x,' x ',y,'=')
z=len(str(a))
if z==6:
if str(a)[0] == str(a)[5]:
if str(a)[1] == str(a)[4]:
if str(a)[2] == str(a)[3]:
print(a,'yes')
exit(a)
else:
pass
#906609

Readable option:
function maxPalindrome(num) {
let maxPalindrome = 1;
for (let i = num; i > 0; i--) {
for (let j = num; j > 0; j--) {
const product = i * j;
if (
product.toString() === product.toString().split("").reverse().join("")
&& product > maxPalindrome
) {
maxPalindrome = product;
}
}
}
return maxPalindrome;
}
console.log(maxPalindrome(999));

This is how I have done with C#:
public static void maxPali() {
int max = 0;
for (int i = 99; i >= 10; i--) {
for (int j = 99; j >= 10; j--) {
if (i*j == reverse(i*j))
max = max >= (i*j) ? max : (i*j);
}
}
Console.WriteLine(max);
}
public static int reverse(int num) {
int rev = 0;
while (num > 0) {
int rem = num % 10;
rev = (rev * 10) + rem;
num /= 10;
}
return rev;
}
JavaScript solution:
(function main() {
let start = 100,
stop = 999,
step = 1;
let arr = Array(Math.ceil((stop + step - start) /
step)).fill(start).map((x, y) => x + y * step);
let max = 0;
arr.slice(0).reverse().map(function(i) {
arr.slice(0).reverse().map(function(j) {
if (i*j == (i*j).toString().split('').reverse().join(''))
if (max < (i*j))
max = i*j;
});
});
console.log(max); }());

How to find prime numbers between 0 - 100?

Want to improve this post? Provide detailed answers to this question, including citations and an explanation of why your answer is correct. Answers without enough detail may be edited or deleted.
In Javascript how would i find prime numbers between 0 - 100? i have thought about it, and i am not sure how to find them. i thought about doing x % x but i found the obvious problem with that.
this is what i have so far:
but unfortunately it is the worst code ever.
var prime = function (){
var num;
for (num = 0; num < 101; num++){
if (num % 2 === 0){
break;
}
else if (num % 3 === 0){
break;
}
else if (num % 4=== 0){
break;
}
else if (num % 5 === 0){
break;
}
else if (num % 6 === 0){
break;
}
else if (num % 7 === 0){
break;
}
else if (num % 8 === 0){
break;
}
else if (num % 9 === 0){
break;
}
else if (num % 10 === 0){
break;
}
else if (num % 11 === 0){
break;
}
else if (num % 12 === 0){
break;
}
else {
return num;
}
}
};
console.log(prime());

Here's an example of a sieve implementation in JavaScript:
function getPrimes(max) {
var sieve = [], i, j, primes = [];
for (i = 2; i <= max; ++i) {
if (!sieve[i]) {
// i has not been marked -- it is prime
primes.push(i);
for (j = i << 1; j <= max; j += i) {
sieve[j] = true;
}
}
}
return primes;
}
Then getPrimes(100) will return an array of all primes between 2 and 100 (inclusive). Of course, due to memory constraints, you can't use this with large arguments.
A Java implementation would look very similar.

Here's how I solved it. Rewrote it from Java to JavaScript, so excuse me if there's a syntax error.
function isPrime (n)
{
if (n < 2) return false;
/**
* An integer is prime if it is not divisible by any prime less than or equal to its square root
**/
var q = Math.floor(Math.sqrt(n));
for (var i = 2; i <= q; i++)
{
if (n % i == 0)
{
return false;
}
}
return true;
}
A number, n, is a prime if it isn't divisible by any other number other than by 1 and itself. Also, it's sufficient to check the numbers [2, sqrt(n)].

Here is the live demo of this script: http://jsfiddle.net/K2QJp/
First, make a function that will test if a single number is prime or not. If you want to extend the Number object you may, but I decided to just keep the code as simple as possible.
function isPrime(num) {
if(num < 2) return false;
for (var i = 2; i < num; i++) {
if(num%i==0)
return false;
}
return true;
}
This script goes through every number between 2 and 1 less than the number and tests if there is any number in which there is no remainder if you divide the number by the increment. If there is any without a remainder, it is not prime. If the number is less than 2, it is not prime. Otherwise, it is prime.
Then make a for loop to loop through the numbers 0 to 100 and test each number with that function. If it is prime, output the number to the log.
for(var i = 0; i < 100; i++){
if(isPrime(i)) console.log(i);
}

Whatever the language, one of the best and most accessible ways of finding primes within a range is using a sieve.
Not going to give you code, but this is a good starting point.
For a small range, such as yours, the most efficient would be pre-computing the numbers.

I have slightly modified the Sieve of Sundaram algorithm to cut the unnecessary iterations and it seems to be very fast.
This algorithm is actually two times faster than the most accepted #Ted Hopp's solution under this topic. Solving the 78498 primes between 0 - 1M takes like 20~25 msec in Chrome 55 and < 90 msec in FF 50.1. Also #vitaly-t's get next prime algorithm looks interesting but also results much slower.
This is the core algorithm. One could apply segmentation and threading to get superb results.
"use strict";
function primeSieve(n){
var a = Array(n = n/2),
t = (Math.sqrt(4+8*n)-2)/4,
u = 0,
r = [];
for(var i = 1; i <= t; i++){
u = (n-i)/(1+2*i);
for(var j = i; j <= u; j++) a[i + j + 2*i*j] = true;
}
for(var i = 0; i<= n; i++) !a[i] && r.push(i*2+1);
return r;
}
var primes = [];
console.time("primes");
primes = primeSieve(1000000);
console.timeEnd("primes");
console.log(primes.length);
The loop limits explained:
Just like the Sieve of Erasthotenes, the Sieve of Sundaram algorithm also crosses out some selected integers from the list. To select which integers to cross out the rule is i + j + 2ij ≤ n where i and j are two indices and n is the number of the total elements. Once we cross out every i + j + 2ij, the remaining numbers are doubled and oddified (2n+1) to reveal a list of prime numbers. The final stage is in fact the auto discounting of the even numbers. It's proof is beautifully explained here.
Sieve of Sundaram is only fast if the loop indices start and end limits are correctly selected such that there shall be no (or minimal) redundant (multiple) elimination of the non-primes. As we need i and j values to calculate the numbers to cross out, i + j + 2ij up to n let's see how we can approach.
i) So we have to find the the max value i and j can take when they are equal. Which is 2i + 2i^2 = n. We can easily solve the positive value for i by using the quadratic formula and that is the line with t = (Math.sqrt(4+8*n)-2)/4,
j) The inner loop index j should start from i and run up to the point it can go with the current i value. No more than that. Since we know that i + j + 2ij = n, this can easily be calculated as u = (n-i)/(1+2*i);
While this will not completely remove the redundant crossings it will "greatly" eliminate the redundancy. For instance for n = 50 (to check for primes up to 100) instead of doing 50 x 50 = 2500, we will do only 30 iterations in total. So clearly, this algorithm shouldn't be considered as an O(n^2) time complexity one.
i j v
1 1 4
1 2 7
1 3 10
1 4 13
1 5 16
1 6 19
1 7 22 <<
1 8 25
1 9 28
1 10 31 <<
1 11 34
1 12 37 <<
1 13 40 <<
1 14 43
1 15 46
1 16 49 <<
2 2 12
2 3 17
2 4 22 << dupe #1
2 5 27
2 6 32
2 7 37 << dupe #2
2 8 42
2 9 47
3 3 24
3 4 31 << dupe #3
3 5 38
3 6 45
4 4 40 << dupe #4
4 5 49 << dupe #5
among which there are only 5 duplicates. 22, 31, 37, 40, 49. The redundancy is around 20% for n = 100 however it increases to ~300% for n = 10M. Which means a further optimization of SoS bears the potentital to obtain the results even faster as n grows. So one idea might be segmentation and to keep n small all the time.
So OK.. I have decided to take this quest a little further.
After some careful examination of the repeated crossings I have come to the awareness of the fact that, by the exception of i === 1 case, if either one or both of the i or j index value is among 4,7,10,13,16,19... series, a duplicate crossing is generated. Then allowing the inner loop to turn only when i%3-1 !== 0, a further cut down like 35-40% from the total number of the loops is achieved. So for instance for 1M integers the nested loop's total turn count dropped to like 1M from 1.4M. Wow..! We are talking almost O(n) here.
I have just made a test. In JS, just an empty loop counting up to 1B takes like 4000ms. In the below modified algorithm, finding the primes up to 100M takes the same amount of time.
I have also implemented the segmentation part of this algorithm to push to the workers. So that we will be able to use multiple threads too. But that code will follow a little later.
So let me introduce you the modified Sieve of Sundaram probably at it's best when not segmented. It shall compute the primes between 0-1M in about 15-20ms with Chrome V8 and Edge ChakraCore.
"use strict";
function primeSieve(n){
var a = Array(n = n/2),
t = (Math.sqrt(4+8*n)-2)/4,
u = 0,
r = [];
for(var i = 1; i < (n-1)/3; i++) a[1+3*i] = true;
for(var i = 2; i <= t; i++){
u = (n-i)/(1+2*i);
if (i%3-1) for(var j = i; j < u; j++) a[i + j + 2*i*j] = true;
}
for(var i = 0; i< n; i++) !a[i] && r.push(i*2+1);
return r;
}
var primes = [];
console.time("primes");
primes = primeSieve(1000000);
console.timeEnd("primes");
console.log(primes.length);
Well... finally I guess i have implemented a sieve (which is originated from the ingenious Sieve of Sundaram) such that it's the fastest JavaScript sieve that i could have found over the internet, including the "Odds only Sieve of Eratosthenes" or the "Sieve of Atkins". Also this is ready for the web workers, multi-threading.
Think it this way. In this humble AMD PC for a single thread, it takes 3,300 ms for JS just to count up to 10^9 and the following optimized segmented SoS will get me the 50847534 primes up to 10^9 only in 14,000 ms. Which means 4.25 times the operation of just counting. I think it's impressive.
You can test it for yourself;
console.time("tare");
for (var i = 0; i < 1000000000; i++);
console.timeEnd("tare");
And here I introduce you to the segmented Seieve of Sundaram at it's best.
"use strict";
function findPrimes(n){
function primeSieve(g,o,r){
var t = (Math.sqrt(4+8*(g+o))-2)/4,
e = 0,
s = 0;
ar.fill(true);
if (o) {
for(var i = Math.ceil((o-1)/3); i < (g+o-1)/3; i++) ar[1+3*i-o] = false;
for(var i = 2; i < t; i++){
s = Math.ceil((o-i)/(1+2*i));
e = (g+o-i)/(1+2*i);
if (i%3-1) for(var j = s; j < e; j++) ar[i + j + 2*i*j-o] = false;
}
} else {
for(var i = 1; i < (g-1)/3; i++) ar[1+3*i] = false;
for(var i = 2; i < t; i++){
e = (g-i)/(1+2*i);
if (i%3-1) for(var j = i; j < e; j++) ar[i + j + 2*i*j] = false;
}
}
for(var i = 0; i < g; i++) ar[i] && r.push((i+o)*2+1);
return r;
}
var cs = n <= 1e6 ? 7500
: n <= 1e7 ? 60000
: 100000, // chunk size
cc = ~~(n/cs), // chunk count
xs = n % cs, // excess after last chunk
ar = Array(cs/2), // array used as map
result = [];
for(var i = 0; i < cc; i++) result = primeSieve(cs/2,i*cs/2,result);
result = xs ? primeSieve(xs/2,cc*cs/2,result) : result;
result[0] *=2;
return result;
}
var primes = [];
console.time("primes");
primes = findPrimes(1000000000);
console.timeEnd("primes");
console.log(primes.length);
Here I present a multithreaded and slightly improved version of the above algorithm. It utilizes all available threads on your device and resolves all 50,847,534 primes up to 1e9 (1 Billion) in the ballpark of 1.3 seconds on my trash AMD FX-8370 8 core desktop.
While there exists some very sophisticated sublinear sieves, I believe the modified Segmented Sieve of Sundaram could only be stretced this far to being linear in time complexity. Which is not bad.
class Threadable extends Function {
constructor(f){
super("...as",`return ${f.toString()}.apply(this,as)`);
}
spawn(...as){
var code = `self.onmessage = m => self.postMessage(${this.toString()}.apply(null,m.data));`,
blob = new Blob([code], {type: "text/javascript"}),
wrkr = new Worker(window.URL.createObjectURL(blob));
return new Promise((v,x) => ( wrkr.onmessage = m => (v(m.data), wrkr.terminate())
, wrkr.onerror = e => (x(e.message), wrkr.terminate())
, wrkr.postMessage(as)
));
}
}
function pi(n){
function scan(start,end,tid){
function sieve(g,o){
var t = (Math.sqrt(4+8*(g+o))-2)/4,
e = 0,
s = 0,
a = new Uint8Array(g),
c = 0,
l = o ? (g+o-1)/3
: (g-1)/3;
if (o) {
for(var i = Math.ceil((o-1)/3); i < l; i++) a[1+3*i-o] = 0x01;
for(var i = 2; i < t; i++){
if (i%3-1) {
s = Math.ceil((o-i)/(1+2*i));
e = (g+o-i)/(1+2*i);
for(var j = s; j < e; j++) a[i + j + 2*i*j-o] = 0x01;
}
}
} else {
for(var i = 1; i < l; i++) a[1+3*i] = 0x01;
for(var i = 2; i < t; i++){
if (i%3-1){
e = (g-i)/(1+2*i);
for(var j = i; j < e; j++) a[i + j + 2*i*j] = 0x01;
}
}
}
for (var i = 0; i < g; i++) !a[i] && c++;
return c;
}
end % 2 && end--;
start % 2 && start--;
var n = end - start,
cs = n < 2e6 ? 1e4 :
n < 2e7 ? 2e5 :
4.5e5 , // Math.floor(3*n/1e3), // chunk size
cc = Math.floor(n/cs), // chunk count
xs = n % cs, // excess after last chunk
pc = 0;
for(var i = 0; i < cc; i++) pc += sieve(cs/2,(start+i*cs)/2);
xs && (pc += sieve(xs/2,(start+cc*cs)/2));
return pc;
}
var tc = navigator.hardwareConcurrency,
xs = n % tc,
cs = (n-xs) / tc,
st = new Threadable(scan),
ps = Array.from( {length:tc}
, (_,i) => i ? st.spawn(i*cs+xs,(i+1)*cs+xs,i)
: st.spawn(0,cs+xs,i)
);
return Promise.all(ps);
}
var n = 1e9,
count;
console.time("primes");
pi(n).then(cs => ( count = cs.reduce((p,c) => p+c)
, console.timeEnd("primes")
, console.log(count)
)
)
.catch(e => console.log(`Error: ${e}`));
So this is as far as I could take the Sieve of Sundaram.

A number is a prime if it is not divisible by other primes lower than the number in question.
So this builds up a primes array. Tests each new odd candidate n for division against existing found primes lower than n. As an optimization it does not consider even numbers and prepends 2 as a final step.
var primes = [];
for(var n=3;n<=100;n+=2) {
if(primes.every(function(prime){return n%prime!=0})) {
primes.push(n);
}
}
primes.unshift(2);

To find prime numbers between 0 to n. You just have to check if a number x is getting divisible by any number between 0 - (square root of x). If we pass n and to find all prime numbers between 0 and n, logic can be implemented as -
function findPrimeNums(n)
{
var x= 3,j,i=2,
primeArr=[2],isPrime;
for (;x<=n;x+=2){
j = (int) Math.sqrt (x);
isPrime = true;
for (i = 2; i <= j; i++)
{
if (x % i == 0){
isPrime = false;
break;
}
}
if(isPrime){
primeArr.push(x);
}
}
return primeArr;
}

var n=100;
var counter = 0;
var primeNumbers = "Prime Numbers: ";
for(var i=2; i<=n; ++i)
{
counter=0;
for(var j=2; j<=n; ++j)
{
if(i>=j && i%j == 0)
{
++counter;
}
}
if(counter == 1)
{
primeNumbers = primeNumbers + i + " ";
}
}
console.log(primeNumbers);

Luchian's answer gives you a link to the standard technique for finding primes.
A less efficient, but simpler approach is to turn your existing code into a nested loop. Observe that you are dividing by 2,3,4,5,6 and so on ... and turn that into a loop.
Given that this is homework, and given that the aim of the homework is to help you learn basic programming, a solution that is simple, correct but somewhat inefficient should be fine.

Using recursion combined with the square root rule from here, checks whether a number is prime or not:
function isPrime(num){
// An integer is prime if it is not divisible by any prime less than or equal to its square root
var squareRoot = parseInt(Math.sqrt(num));
var primeCountUp = function(divisor){
if(divisor > squareRoot) {
// got to a point where the divisor is greater than
// the square root, therefore it is prime
return true;
}
else if(num % divisor === 0) {
// found a result that divides evenly, NOT prime
return false;
}
else {
// keep counting
return primeCountUp(++divisor);
}
};
// start # 2 because everything is divisible by 1
return primeCountUp(2);
}

You can try this method also, this one is basic but easy to understand:
var tw = 2, th = 3, fv = 5, se = 7;
document.write(tw + "," + th + ","+ fv + "," + se + ",");
for(var n = 0; n <= 100; n++)
{
if((n % tw !== 0) && (n % th !==0) && (n % fv !==0 ) && (n % se !==0))
{
if (n == 1)
{
continue;
}
document.write(n +",");
}
}

I recently came up with a one-line solution that accomplishes exactly this for a JS challenge on Scrimba (below).
ES6+
const getPrimes=num=>Array(num-1).fill().map((e,i)=>2+i).filter((e,i,a)=>a.slice(0,i).every(x=>e%x!==0));
< ES6
function getPrimes(num){return ",".repeat(num).slice(0,-1).split(',').map(function(e,i){return i+1}).filter(function(e){return e>1}).filter(function(x){return ",".repeat(x).slice(0,-1).split(',').map(function(f,j){return j}).filter(function(e){return e>1}).every(function(e){return x%e!==0})})};
This is the logic explained:
First, the function builds an array of all numbers leading up to the desired number (in this case, 100) via the .repeat() function using the desired number (100) as the repeater argument and then mapping the array to the indexes+1 to get the range of numbers from 0 to that number (0-100). A bit of string splitting and joining magic going on here. I'm happy to explain this step further if you like.
We exclude 0 and 1 from the array as they should not be tested for prime, lest they give a false positive. Neither are prime. We do this using .filter() for only numbers > 1 (≥ 2).
Now, we filter our new array of all integers between 2 and the desired number (100) for only prime numbers. To filter for prime numbers only, we use some of the same magic from our first step. We use .filter() and .repeat() once again to create a new array from 2 to each value from our new array of numbers. For each value's new array, we check to see if any of the numbers ≥ 2 and < that number are factors of the number. We can do this using the .every() method paired with the modulo operator % to check if that number has any remainders when divided by any of those values between 2 and itself. If each value has remainders (x%e!==0), the condition is met for all values from 2 to that number (but not including that number, i.e.: [2,99]) and we can say that number is prime. The filter functions returns all prime numbers to the uppermost return, thereby returning the list of prime values between 2 and the passed value.
As an example, using one of these functions I've added above, returns the following:
getPrimes(100);
// => [2,3,5,7,11,13,17,19,23,29,31,37,41,43,47,53,59,61,67,71,73,79,83,89,97]

Here's a fast way to calculate primes in JavaScript, based on the previous prime value.
function nextPrime(value) {
if (value > 2) {
var i, q;
do {
i = 3;
value += 2;
q = Math.floor(Math.sqrt(value));
while (i <= q && value % i) {
i += 2;
}
} while (i <= q);
return value;
}
return value === 2 ? 3 : 2;
}
Test
var value = 0, result = [];
for (var i = 0; i < 10; i++) {
value = nextPrime(value);
result.push(value);
}
console.log("Primes:", result);
Output
Primes: [ 2, 3, 5, 7, 11, 13, 17, 19, 23, 29 ]
It is faster than other alternatives published here, because:
It aligns the loop limit to an integer, which works way faster;
It uses a shorter iteration loop, skipping even numbers.
It can give you the first 100,000 primes in about 130ms, or the first 1m primes in about 4 seconds.
function nextPrime(value) {
if (value > 2) {
var i, q;
do {
i = 3;
value += 2;
q = Math.floor(Math.sqrt(value));
while (i <= q && value % i) {
i += 2;
}
} while (i <= q);
return value;
}
return value === 2 ? 3 : 2;
}
var value, result = [];
for (var i = 0; i < 10; i++) {
value = nextPrime(value);
result.push(value);
}
display("Primes: " + result.join(', '));
function display(msg) {
document.body.insertAdjacentHTML(
"beforeend",
"<p>" + msg + "</p>"
);
}
UPDATE
A modern, efficient way of doing it, using prime-lib:
import {generatePrimes, stopWhen} from 'prime-lib';
const p = generatePrimes(); //=> infinite prime generator
const i = stopWhen(p, a => a > 100); //=> Iterable<number>
console.log(...i); //=> 2 3 5 7 11 ... 89 97

<code>
<script language="javascript">
var n=prompt("Enter User Value")
var x=1;
if(n==0 || n==1) x=0;
for(i=2;i<n;i++)
{
if(n%i==0)
{
x=0;
break;
}
}
if(x==1)
{
alert(n +" "+" is prime");
}
else
{
alert(n +" "+" is not prime");
}
</script>

Sieve of Eratosthenes. its bit look but its simple and it works!
function count_prime(arg) {
arg = typeof arg !== 'undefined' ? arg : 20; //default value
var list = [2]
var list2 = [0,1]
var real_prime = []
counter = 2
while (counter < arg ) {
if (counter % 2 !== 0) {
list.push(counter)
}
counter++
}
for (i = 0; i < list.length - 1; i++) {
var a = list[i]
for (j = 0; j < list.length - 1; j++) {
if (list[j] % a === 0 && list[j] !== a) {
list[j] = false; // assign false to non-prime numbers
}
}
if (list[i] !== false) {
real_prime.push(list[i]); // save all prime numbers in new array
}
}
}
window.onload=count_prime(100);

And this famous code from a famous JS Ninja
var isPrime = n => Array(Math.ceil(Math.sqrt(n)+1)).fill().map((e,i)=>i).slice(2).every(m => n%m);
console.log(Array(100).fill().map((e,i)=>i+1).slice(1).filter(isPrime));

A list built using the new features of ES6, especially with generator.
Go to https://codepen.io/arius/pen/wqmzGp made in Catalan language for classes with my students. I hope you find it useful.
function* Primer(max) {
const infinite = !max && max !== 0;
const re = /^.?$|^(..+?)\1+$/;
let current = 1;
while (infinite || max-- ) {
if(!re.test('1'.repeat(current)) == true) yield current;
current++
};
};
let [...list] = Primer(100);
console.log(list);

Here's the very simple way to calculate primes between a given range(1 to limit).
Simple Solution:
public static void getAllPrimeNumbers(int limit) {
System.out.println("Printing prime number from 1 to " + limit);
for(int number=2; number<=limit; number++){
//***print all prime numbers upto limit***
if(isPrime(number)){
System.out.println(number);
}
}
}
public static boolean isPrime(int num) {
if (num == 0 || num == 1) {
return false;
}
if (num == 2) {
return true;
}
for (int i = 2; i <= num / 2; i++) {
if (num % i == 0) {
return false;
}
}
return true;
}

A version without any loop. Use this against any array you have. ie.,
[1,2,3...100].filter(x=>isPrime(x));
const isPrime = n => {
if(n===1){
return false;
}
if([2,3,5,7].includes(n)){
return true;
}
return n%2!=0 && n%3!=0 && n%5!=0 && n%7!=0;
}

Here's my stab at it.
Change the initial i=0 from 0 to whatever you want, and the the second i<100 from 100 to whatever to get primes in a different range.
for(var i=0; i<100000; i++){
var devisableCount = 2;
for(var x=0; x<=i/2; x++){
if (devisableCount > 3) {
break;
}
if(i !== 1 && i !== 0 && i !== x){
if(i%x === 0){
devisableCount++;
}
}
}
if(devisableCount === 3){
console.log(i);
}
}
I tried it with 10000000 - it takes some time but appears to be accurate.

Here are the Brute-force iterative method and Sieve of Eratosthenes method to find prime numbers upto n. The performance of the second method is better than first in terms of time complexity
Brute-force iterative
function findPrime(n) {
var res = [2],
isNotPrime;
for (var i = 3; i < n; i++) {
isNotPrime = res.some(checkDivisorExist);
if ( !isNotPrime ) {
res.push(i);
}
}
function checkDivisorExist (j) {
return i % j === 0;
}
return res;
}
Sieve of Eratosthenes method
function seiveOfErasthones (n) {
var listOfNum =range(n),
i = 2;
// CHeck only until the square of the prime is less than number
while (i*i < n && i < n) {
listOfNum = filterMultiples(listOfNum, i);
i++;
}
return listOfNum;
function range (num) {
var res = [];
for (var i = 2; i <= num; i++) {
res.push(i);
}
return res;
}
function filterMultiples (list, x) {
return list.filter(function (item) {
// Include numbers smaller than x as they are already prime
return (item <= x) || (item > x && item % x !== 0);
});
}
}

You can use this for any size of array of prime numbers. Hope this helps
function prime() {
var num = 2;
var body = document.getElementById("solution");
var len = arguments.length;
var flag = true;
for (j = 0; j < len; j++) {
for (i = num; i < arguments[j]; i++) {
if (arguments[j] % i == 0) {
body.innerHTML += arguments[j] + " False <br />";
flag = false;
break;
} else {
flag = true;
}
}
if (flag) {
body.innerHTML += arguments[j] + " True <br />";
}
}
}
var data = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10];
prime.apply(null, data);
<div id="solution">
</div>

public static void main(String[] args) {
int m = 100;
int a[] =new int[m];
for (int i=2; i<m; i++)
for (int j=0; j<m; j+=i)
a[j]++;
for (int i=0; i<m; i++)
if (a[i]==1) System.out.println(i);
}

Using Sieve of Eratosthenes, source on Rosettacode
fastest solution: https://repl.it/#caub/getPrimes-bench
function getPrimes(limit) {
if (limit < 2) return [];
var sqrtlmt = limit**.5 - 2;
var nums = Array.from({length: limit-1}, (_,i)=>i+2);
for (var i = 0; i <= sqrtlmt; i++) {
var p = nums[i]
if (p) {
for (var j = p * p - 2; j < nums.length; j += p)
nums[j] = 0;
}
}
return nums.filter(x => x); // return non 0 values
}
document.body.innerHTML = `<pre style="white-space:pre-wrap">${getPrimes(100).join(', ')}</pre>`;
// for fun, this fantasist regexp way (very inefficient):
// Array.from({length:101}, (_,i)=>i).filter(n => n>1&&!/^(oo+)\1+$/.test('o'.repeat(n))

Why try deleting by 4 (and 6,8,10,12) if we've already tried deleting by 2 ?
Why try deleting by 9 if we've already tried deleting by 3 ?
Why try deleting by 11 if 11 * 11 = 121 which is greater than 100 ?
Why try deleting any odd number by 2 at all?
Why try deleting any even number above 2 by anything at all?
Eliminate the dead tests and you'll get yourself a good code, testing for primes below 100.
And your code is very far from being the worst code ever. Many many others would try dividing 100 by 99. But the absolute champion would generate all products of 2..96 with 2..96 to test whether 97 is among them. That one really is astonishingly inefficient.
Sieve of Eratosthenes of course is much better, and you can have one -- under 100 -- with no arrays of booleans (and no divisions too!):
console.log(2)
var m3 = 9, m5 = 25, m7 = 49, i = 3
for( ; i < 100; i += 2 )
{
if( i != m3 && i != m5 && i != m7) console.log(i)
else
{
if( i == m3 ) m3 += 6
if( i == m5 ) m5 += 10
if( i == m7 ) m7 += 14
}
} "DONE"
This is the sieve of Eratosthenes, were we skip over the composites - and that's what this code is doing. The timing of generation of composites and of skipping over them (by checking for equality) is mixed into one timeline. The usual sieve first generates composites and marks them in an array, then sweeps the array. Here the two stages are mashed into one, to avoid having to use any array at all (this only works because we know the top limit's square root - 10 - in advance and use only primes below it, viz. 3,5,7 - with 2's multiples, i.e. evens, implicitly skipped over in advance).
In other words this is an incremental sieve of Eratosthenes and m3, m5, m7 form an implicit priority queue of the multiples of primes 3, 5, and 7.

I was searching how to find out prime number and went through above code which are too long. I found out a new easy solution for prime number and add them using filter. Kindly suggest me if there is any mistake in my code as I am a beginner.
function sumPrimes(num) {
let newNum = [];
for(let i = 2; i <= num; i++) {
newNum.push(i)
}
for(let i in newNum) {
newNum = newNum.filter(item => item == newNum[i] || item % newNum[i] !== 0)
}
return newNum.reduce((a,b) => a+b)
}
sumPrimes(10);

Here is an efficient, short solution using JS generators. JSfiddle
// Consecutive integers
let nats = function* (n) {
while (true) yield n++
}
// Wrapper generator
let primes = function* () {
yield* sieve(primes(), nats(2))
}
// The sieve itself; only tests primes up to sqrt(n)
let sieve = function* (pg, ng) {
yield ng.next().value;
let n, p = pg.next().value;
while ((n = ng.next().value) < p * p) yield n;
yield* sieve(pg, (function* () {
while (n = ng.next().value) if (n % p) yield n
})())
}
// Longest prefix of stream where some predicate holds
let take = function* (vs, fn) {
let nx;
while (!(nx = vs.next()).done && fn(nx.value)) yield nx.value
}
document.querySelectorAll('dd')[0].textContent =
// Primes smaller than 100
[...take(primes(), x => x < 100)].join(', ')
<dl>
<dt>Primes under 100</dt>
<dd></dd>
</dl>

First, change your inner code for another loop (for and while) so you can repeat the same code for different values.
More specific for your problem, if you want to know if a given n is prime, you need to divide it for all values between 2 and sqrt(n). If any of the modules is 0, it is not prime.
If you want to find all primes, you can speed it and check n only by dividing by the previously found primes. Another way of speeding the process is the fact that, apart from 2 and 3, all the primes are 6*k plus or less 1.

It would behoove you, if you're going to use any of the gazillion algorithms that you're going to be presented with in this thread, to learn to memoize some of them.
See Interview question : What is the fastest way to generate prime number recursively?

Use following function to find out prime numbers :
function primeNumbers() {
var p
var n = document.primeForm.primeText.value
var d
var x
var prime
var displayAll = 2 + " "
for (p = 3; p <= n; p = p + 2) {
x = Math.sqrt(p)
prime = 1
for (d = 3; prime && (d <= x); d = d + 2)
if ((p % d) == 0) prime = 0
else prime = 1
if (prime == 1) {
displayAll = displayAll + p + " "
}
}
document.primeForm.primeArea.value = displayAll
}