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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);
}

How to encode letter from string into numbers

what I am trying to do is encode numbers in a string into numbers acording to the alphabet an leave the numbers still. so "abc123" would be "123123". Found the solution in javascript but cannot seem to fit into java. any help would be great, thanks.
The java function would be something like
import java.util.*;
import java.io.*;
class Main {
public static String NumberEncoding(String str) {
***call javascript function or translate it into java
}
public static void main (String[] args) {
// keep this function call here
Scanner s = new Scanner(System.in);
System.out.print(NumberEncoding(s.nextLine()));
}
}
The jasvascript function is
function NumberEncoding(str) {
str = str.toLowerCase();
var obj = {};
var alpha = "abcdefghijklmnopqrstuvwxyz";
var result = "";
for (var i = 1; i <= alpha.length; i++) {
obj[alpha[i-1]] = i;
}
for (var j = 0; j < str.length; j++) {
if (str[j].match(/[a-z]/)) {
result += obj[str[j]];
} else {
result += str[j];
}
}
return result;
}

Step one, create a variable to accumulate the String result; I would use a StringBuilder. Step two, iterate the input String one character at a time. Step three, convert that character to lower-case. Step four, check that the character is not a digit. Step five, if the character is a digit pass it through unchanged otherwise the value is easy to determine because Java characters are an integral type (e.g. 'a' + 1 = 'b' and 'b' - 1 = 'a'). Step six, return the result as a String. Finally, Java naming convention is camel case (starting with a lower case letter). Like,
public static String encodeNumber(String str) {
StringBuilder result = new StringBuilder();
for (int j = 0; j < str.length(); j++) {
char c = Character.toLowerCase(str.charAt(j));
if (c < 'a' || c > 'z') {
result.append(c);
} else {
result.append(1 + c - 'a');
}
}
return result.toString();
}
But, if you really wanted to, you can indeed directly call the JavaScript function from Java using Nashorn. Like,
String f = "function NumberEncoding(str) { str = str.toLowerCase();\n"
+ "var obj = {};\n"
+ "var alpha = \"abcdefghijklmnopqrstuvwxyz\";\n"
+ "var result = \"\";\n"
+ "for (var i = 1; i <= alpha.length; i++) {\n"
+ " obj[alpha[i-1]] = i;\n" + "}\n" + "\n"
+ "for (var j = 0; j < str.length; j++) {\n"
+ " if (str[j].match(/[a-z]/)) {\n"
+ " result += obj[str[j]];\n"
+ " } else {\n" + " result += str[j];" + " }\n" + "}\n"
+ "return result;\n" + "}";
ScriptEngine se = new ScriptEngineManager().getEngineByName("js");
try {
se.eval(f);
Invocable invocable = (Invocable) se;
Object result = invocable.invokeFunction("NumberEncoding", "zabc123");
System.out.println(result);
} catch (Exception e) {
e.printStackTrace();
}
For the same result.

One way to do it is to use StringBuilder.
List<String> strings = Arrays.asList("abc123", "e2f3g4");
for (String s : strings) {
StringBuilder sb = new StringBuilder(s);
for (int i = 0; i < sb.length(); i++) {
char c = sb.charAt(i);
if (Character.isAlphabetic(c)) {
sb.replace(i, i + 1, Integer.toString(c - 'a' + 1));
}
}
System.out.println(sb.toString());
}
And the there's the Stream version.
List<String> strings = Arrays.asList("123abc", "e1f2g3", "xyz123");
List<String> converted = strings.stream().map(str -> str.chars().map(
chr -> Character.isAlphabetic(chr) ? chr - 'a' + 1
: chr - '0').mapToObj(String::valueOf).collect(
Collectors.joining())).collect(Collectors.toList());
System.out.println(converted);

Steps to solve it can be
Fill up an int[] of size, 26 (number of alphabets) with the values 1 to 26, corresponding to the position of letters in the alphabets.
Traverse through all characters of the input string and append its position from the int[] to a StringBuilder. If the character is not an alphabet, append it as it is.
Demo:
public class Main {
public static void main(String[] args) {
System.out.println(numberEncoding("abc123"));// Expected: 123123
}
static String numberEncoding(String str) {
str = str.toLowerCase();
String alpha = "abcdefghijklmnopqrstuvwxyz";
int[] obj = new int[alpha.length()];
StringBuilder result = new StringBuilder();
for (int i = 1; i <= obj.length; i++) {
obj[i - 1] = i;
}
for (int j = 0; j < str.length(); j++) {
if (str.charAt(j) >= 'a' && str.charAt(j) <= 'z') {
result.append(String.valueOf(obj[j]));
} else {
result.append(str.charAt(j));
}
}
return result.toString();
}
}
Output:
123123

How to "round" number, by putting zeros after the 2nd digit in javascript

I would like to "round" an integer number, by swapping all the digits after the 2nd digit to zeros. Additionally, if the number has only 1 digit, then don't do anything, and if the number has 2 digits, then swap the 2nd digit to a 0.
Example:
3 => 3
22 => 20
754 => 750
8912 => 8900
Can this be achieved without truncating the number as a string, and then rebuilding the number with zeros?

You don't need to truncate the number as a string, it can be easily achieved via mathematical calculation. Also, changing number to string and then doing any operation will be an added overhead which is not required in this case.
Refer the code below, it's quite straight forward.
Hope this helps.
function changeNumber(num){
if(Math.floor(num/10) == 0){
return num;
} else if(Math.floor(num/1000) == 0){
return Math.floor(num/10)*10;
}
else{
return Math.floor(num/100)*100
}
}
console.log(changeNumber(3));
console.log(changeNumber(22));
console.log(changeNumber(754));
console.log(changeNumber(8923));

That will work with every base-10 number.
All is about a simple math operation: number - [rest of (number / base-10 of number)]
function round(n) {
if(n < 10) return n;
var d = getTenBase(n.toString().length - 1);
return n - (n % (10 * d));
}
function getTenBase(l) {
var d = 1;
for(var i = 2; i < l; i++) {
d *= 10;
}
return d;
}
console.log(round(3));
console.log(round(22));
console.log(round(768));
console.log(round(1657));

you can just find length and first two character after that take zero with valid length and concat both
var str = '8912';
var n = str.length;
if(n == 1)
{
print(str);
} else if(n==2) {
var strFirst = str.substring(0,1);
var str2 = '0';
var res = strFirst.concat(str2);
} else if(n>2) {
var strFirst = str.substring(0,2);
var i;
var strsec ='0';
for (i = 0; i < n-3; i++) {
strsec += 0 ;
}
var res = strFirst.concat(strsec);
}
print(res);

I need to validate an input string using checksum for alphanumerics

I have the following function that validates a digits input consisted of only numbers based on Luhn Algorithm:
function isCheckdigitCorrect(value) {
// accept only digits, dashes or spaces
if (/[^0-9-\s]+/.test(value)) return false;
var nCheck = 0, nDigit = 0, bEven = false;
value = value.replace(/\D/g, "");
for (var n = value.length - 1; n >= 0; n--) {
var cDigit = value.charAt(n),
nDigit = parseInt(cDigit, 10);
if (bEven) {
if ((nDigit *= 2) > 9) nDigit -= 9;
}
nCheck += nDigit;
bEven = !bEven;
}
return (nCheck % 10) == 0;
}
Is there anyway that I can validate also alphanumerics, so let's suppose I have a valid ID: AC813(6) , () is the checksum. So is there a way that I can prevent users having to type mistakenly AF813(6) so this would tell user incorrect ID.
I appreciate your help

Substituting digits for alphabetic characters to calculate a checksum severely reduces the robustness of the check, and the simplest suggestion I can come up with is to use the Luhn mod N algorithm described on Wikipedia.
Translating the algorithm into JavaScipt was relatively straight forward: the following is not my code but a translation from the wiki article - so I won't pretend it is optimal. It is intended to work with strings of case insensitive ASCII alphabetic characters and decimal digits. For documentation see the wiki.
// based on https://en.wikipedia.org/wiki/Luhn_mod_N_algorithm
var charset = "0123456789ABCDEFGHIJKLMNOPQRSTUVWXYZ";
function NumberOfValidInputCharacters () { return charset.length; }
function CodePointFromCharacter(character) { return charset.indexOf(character)};
function CharacterFromCodePoint( codePoint) { return charset[codePoint]};
function GenerateCheckCharacter (input) {
var factor = 2;
var sum = 0;
var n = NumberOfValidInputCharacters();
input = input.toUpperCase();
// Starting from the right and working leftwards is easier since
// the initial "factor" will always be "2"
for (var i = input.length - 1; i >= 0; i--) {
var codePoint = CodePointFromCharacter(input[i]);
if( codePoint < 0) {
return "";
}
var addend = factor * codePoint;
// Alternate the "factor" that each "codePoint" is multiplied by
factor = (factor == 2) ? 1 : 2;
// Sum the digits of the "addend" as expressed in base "n"
addend = Math.floor(addend / n) + (addend % n);
sum += addend;
}
// Calculate the number that must be added to the "sum"
// to make it divisible by "n"
var remainder = sum % n;
var checkCodePoint = (n - remainder) % n;
return CharacterFromCodePoint(checkCodePoint);
}
function ValidateCheckCharacter(input) {
var factor = 1;
var sum = 0;
var n = NumberOfValidInputCharacters();
input = input.toUpperCase();
// Starting from the right, work leftwards
// Now, the initial "factor" will always be "1"
// since the last character is the check character
for (var i = input.length - 1; i >= 0; i--) {
var codePoint = CodePointFromCharacter(input[i]);
if( codePoint < 0) {
return false;
}
var addend = factor * codePoint;
// Alternate the "factor" that each "codePoint" is multiplied by
factor = (factor == 2) ? 1 : 2;
// Sum the digits of the "addend" as expressed in base "n"
addend = Math.floor(addend / n) + (addend % n);
sum += addend;
}
var remainder = sum % n;
return (remainder == 0);
}
// quick test:
console.log ("check character for 'abcde234': %s",
GenerateCheckCharacter("abcde234"));
console.log( "validate 'abcde2349' : %s " ,
ValidateCheckCharacter( "abcde2349"));
console.log( "validate 'abcde234X' : %s" ,
ValidateCheckCharacter( "abcde234X"));

If you just want to do the Luhn algorithm with letters replacing some of the numbers, then include an additional step to convert letters to numbers within your function.
So if you wanted to allow say A, B, C, D that convert to 0, 1, 2, 3 then you could do:
function isCheckdigitCorrect(value) {
// Letter to number mapping
var letters = {a:'0', b:'1', c:'2', d:'3'};
// Convert letters to their number equivalents, if they have one
value = value.split('').reduce(function(s, c){
return s += letters[c.toLowerCase()] || c;
},'');
// Continue as currently
// accept only digits, dashes or spaces
if (/[^0-9-\s]+/.test(value)) return false;
var nCheck = 0, nDigit = 0, bEven = false;
value = value.replace(/\D/g, "");
for (var n = value.length - 1; n >= 0; n--) {
var cDigit = value.charAt(n),
nDigit = parseInt(cDigit, 10);
if (bEven) {
if ((nDigit *= 2) > 9) nDigit -= 9;
}
nCheck += nDigit;
bEven = !bEven;
}
return (nCheck % 10) == 0;
}
// In the following, A = 0 and D = 3
console.log(isCheckdigitCorrect('375767AA4D6AA21'));
You can implement other algorithms in a similar way.

need help converting C# code to javascript / reversing a function output

I'm working on a function that converts a number to string and string to a number.
the original c# code
public static string unhash(Int64 hash)
{
string originalString = "";
Int64 mod = 37;
string letters = "acdegilmnoprstuw";
while (hash != 7)
{
Int64 index = hash % mod;
originalString = letters[(Int32) index] + originalString; // need help converting this line to javascript
hash = (hash - index) / mod;
}
return originalString;
}
the javascript code
this is working correctly as it convert string into hash that I want
function hash (s) {
var h = 7;
var letters = "acdegilmnoprstuw";
for (i = 0; i < s.length; i++) {
h = (h * 37 + letters.indexOf(s[i]))
}
return h;
}
the code to reverse the process of hash to string, it not working correctly
function unhash (hash) {
var originalString = "";
var mod = 37;
var letters = "acdegilmnoprstuw";
while( hash != 7) {
var index = hash % mod;
originalString = letters[(Int32Array)index] + originalString; // I'm not sure what the javascript version of int32
hash = (hash - index) / mod;
}
}
alert(hash("leepadg")); // this is the correct output 680131659347
alert(unhash( 680131659347)); //output supposed to be leepadg but returning undefined