Develop Reference

hasPairsWithSum Google Interview Question

I solved this problem by iterating through the array then find the item when the sum equals to array[i] + item returning true otherwise returning false.
My Question is => How I can return the indices of those numbers that add up to sum not just true? Using the same code below:
function hasPairsWithSum(array,sum) {
for (let i = 0; i < array.length; i++) {
if (array.find((item) => {return sum === array[i] + item}
));
return true;
};
return false;
};
console.log(hasPairsWithSum([1,2,4,4],8))
Note: Time complexity must be less than O(n ^ 2).

JavaScript O(n) Solution.
function hasPairsWithSum(array, sum) {
const map = new Map ();
for(let i = 0; i < array.length; i++) {
let currVal = array[i];
if (map.has(currVal)) {
return [map.get(currVal),i]
}
// difference value = sum - current value
let diff = sum - currVal
map.set(diff,i)
}
};
console.log(hasPairsWithSum([2,2,4,4], 8))

Please refer this code.
function hasPairsWithSum(array,sum) {
let result = [];
for (let i = 0; i < array.length; i++) {
if (array.some((item, index) => {return i === index ? false : sum === array[i] + item}))
result.push(i);
};
return result;
};
console.log(hasPairsWithSum([1,2,4,4],8))
console.log(hasPairsWithSum([3,2,4],6))
console.log(hasPairsWithSum([0,4,3,0],0))

O(n) Soln ... using math concept a+b = n then if a is present in our array then need to find b = n - a is present or not ..
def hasPairsWithSum(array,sum):
d = {}
for i in range(len(array)):
if(array[i] in d):
d[array[i]].append(i)
else:
d[array[i]] = [i]
ans = []
for i in range(len(array)):
val = sum - array[i]
if(val in d):
if(d[val][0] == i):
if(len(d[val]) > 1):
ans.append((i,d[val][1]))
break
else:
continue
else:
ans.append((i,d[val][0]))
break
return ans
print(hasPairsWithSum([4, 4, 4, 4], 8))
O(nlogn) soln ....just store the index with elements .. then sort it by their values .. next step run a loop with complexity of O(n) [concept : Two pointers]
def hasPairsWithSum(array,sum):
arr = []
for i in range(len(array)):
arr.append((array[i],i))
arr.sort()
i = 0
j = len(array)-1
ans = []
while(i<j):
tmp_sum = arr[i][0] + arr[j][0]
if(tmp_sum == sum):
ans.append((arr[i][1] , arr[j][1]))
#add your logic if you want to find all possible indexes instead of break
break
elif(tmp_sum < sum):
i = i + 1
elif(tmp_sum > sum):
j = j - 1
return ans
print(hasPairsWithSum([1,2,4,4],8))
note : if you want to find all possible soln then these approaches will not work either add you own logic in while loop or another approach is use binary search with traversal on every element and store the indexes in set (worst case this will be O(n^2) as we have to find all possible values) Eg: [4,4,4,4,4,4] , sum = 8 and you want to print all possible indexes then we end up running it upto n^2 (why? reason: total possible solns. are 5+4+3+2+1 = n*(n-1)/2 ≈ n^2)

You have to iterate over the array elements checking at every iteration for every element of the array (except the last one) all the elements at the right of it like below:
function findIndexes(array, sum) {
const result = [];
for (let i = 0; i < array.length -1; ++i) {
for (let j = i + 1; j < array.length; ++j) {
if ((array[i] + array[j]) === sum) {
result.push([i, j]);
}
}
}
return result;
}
console.log(findIndexes([1, 2, 4, 4], 8));
console.log(findIndexes([3, 2, 4], 6));
Update:
It is possible to obtain a linear O(n) complexity using an auxiliary Map structure associating an integer value as key with as a value the list containing all the indexes of the elements in the array equal to the integer key like below:
function findIndexes(array, sum) {
const map = new Map();
const result = [];
for (let i = 0; i < array.length; ++i) {
const a = array[i];
const b = sum - a;
if (map.has(b)) {
for (const index of map.get(b)) {
result.push([index, i]);
}
}
const l = map.has(a) ? map.get(a) : [];
l.push(i);
map.set(a, l);
}
return result;
}
console.log(findIndexes([1, 2, 4, 4], 8));
console.log(findIndexes([3, 2, 4], 6));
console.log(findIndexes([1, 1, 1], 2));

Is there any any other way to find in array pair of numbers whose sum are k?

I have an array of integers and a number k. Is it necessary to determine whether there are two numbers in the array whose sum is k?
function findPairs(nums, k) {
var s = [];
var length = nums.length;
for (var i = 0; i < length; i++) {
if (s[nums[i]] === k - nums[i]) {
console.log(nums[i], k - nums[i])
return true;
} else {
s[k - nums[i]] = nums[i];
}
}
return false;
}
var nums = [10, 15, 3, 7]
var k = 17
console.log(findPairs(nums, k))
why my code is not working?

My guess is that you had a syntax error or forgot to actually declare a function, since the code in the current version of your question appears to work as expected.
As an aside, I would suggest using an object or a Set instead of an array to store the other pair, because for large values of k, your s array may consume a lot of memory on some JavaScript engines as a result.
function findPairs(nums, k) {
var s = {};
var length = nums.length;
for (var i = 0; i < length; i++) {
if (s[nums[i]] === k - nums[i]) {
console.log(nums[i], k - nums[i]);
return true;
}
s[k - nums[i]] = nums[i];
console.log(s); // see the lookup table after each iteration
}
return false;
}
var nums = [10, 15, 3, 7];
var k = 17;
console.log(findPairs(nums, k));

Functional solution
const findPairs = (nums, k) =>
nums
.flatMap((v, i, arr) => arr.slice(i + 1).map(w => [v, w]))
.filter(pair => pair[0] + pair[1] === k);
console.log(findPairs([1, 2, 3, 4, 5, 6], 5));

Loop from 0 to a number and loop through all numbers in array (javascript)

Here is the idea:
var a = [4, 5, 6];
for (var m = 0; m < a[0]; m++)
for (var n = 0; n < a[1]; n++)
for (var p = 0; p < a[2]; p++)
console.log(`${m} + ${n} + ${p} = ${m+n+p}`);
Live Copy:
// This just tells the Stack Snippets in-snippet console not
// to throw away entries once it reaches a max (the default max
// is just the last 50 logs).
console.config({maxEntries: Infinity});
var a = [4, 5, 6];
for (var m = 0; m < a[0]; m++)
for (var n = 0; n < a[1]; n++)
for (var p = 0; p < a[2]; p++)
console.log(`${m} + ${n} + ${p} = ${m+n+p}`);
/* This just makes the console take up the full output area */
.as-console-wrapper {
max-height: 100% !important;
}
The code would get longer if the array a has more indexes. Could the code be shorten using Array.map or filter or a function?

We can do this without taking up massive amounts of memory, and fairly simply, by using recursion:
const process = (array, n, numbers) => {
if (n < array.length) {
// Not done yet, recurse once for each number at this level
const max = array[n];
for (let i = 0; i < max; ++i) {
process(array, n + 1, [...numbers, i]);
}
} else {
// Done with this level, process the numbers we got
console.log(`${numbers.join(" + ")} = ${numbers.reduce((s, e) => s + e)}`);
}
}
process([4, 5, 6], 0, []);
Live Copy, with cross-checking against your results to ensure the above does the same thing:
// This just tells the Stack Snippets in-snippet console not
// to throw away entries once it reaches a max (the default max
// is just the last 50 logs).
console.config({maxEntries: Infinity});
function thisSolution() {
const results = [];
const process = (array, n, numbers) => {
if (n < array.length) {
// Not done yet, recurse once for each number at this level
const max = array[n];
for (let i = 0; i < max; ++i) {
process(array, n + 1, [...numbers, i]);
}
} else {
// Done with this level, process the numbers we got
const result = numbers.reduce((s, e) => s + e);
results.push(result);
console.log(`${numbers.join(" + ")} = ${result}`);
}
}
process([4, 5, 6], 0, []);
return results;
}
function yourSolution() {
const results = [];
var a = [4, 5, 6];
for (var m = 0; m < a[0]; m++)
for (var n = 0; n < a[1]; n++)
for (var p = 0; p < a[2]; p++)
results.push(m + n + p);
return results;
}
const thisResult = thisSolution();
const yourResult = yourSolution();
if (thisResult.some((entry, index) => entry !== yourResult[index])) {
console.log("WRONG");
} else {
console.log("RIGHT");
}
/* This just makes the console take up the full output area */
.as-console-wrapper {
max-height: 100% !important;
}
This never goes deep into the stack (a.length + 1 stack frames, to be precise, so four in the example case). It builds up a number of temporary arrays (145 in the example case) that max out at a.length entries, releasing them as soon as they aren't needed anymore (a max of four are retained at any given time). Here's the quick and dirty metrics on that:
let maxStack = 0;
let stack = 0;
let totalArrays = 0;
let maxArrays = 0;
let arrays = 0;
// A wrapper for counting stack frames
const process = (...args) => {
if (++stack > maxStack) {
maxStack = stack;
}
const result = process2(...args);
--stack;
return result;
};
const process2 = (array, n, numbers) => {
if (n < array.length) {
// Not done yet, recurse once for each number at this level
const max = array[n];
for (let i = 0; i < max; ++i) {
++totalArrays;
if (++arrays > maxArrays) {
maxArrays = arrays;
}
process(array, n + 1, [...numbers, i]);
--arrays;
}
} else {
// Done with this level, process the numbers we got
//console.log(`${numbers.join(" + ")} = ${numbers.reduce((s, e) => s + e)}`);
}
}
process([4, 5, 6], 0, []);
++maxArrays; // To account for the one in the last argument above
++totalArrays; // "
console.log(`Max stack: ${maxStack}, max arrays: ${maxArrays}, total arrays: ${totalArrays}`);

It's easier if you break it down. First, you need to create a series per every element of your array.
let series = num => Array.from({ length: num + 1 }, (n, i) => i); //creates an array with nums from 0 to num.
That's the first part of your question. Then you need to do a cross product of your series.
Basically for two series [1, 2, 3] and [1, 2, 3, 4] you'll end up with a set of 12 elements:
[2, 3, 4, 5, 3, 4, 5, 6, 4, 5, 6, 7]
And for that you could do:
let crossProduct = (a1, a2) => Array.prototype.concat.call(...a1.map(n1 => a2.map(n2 => n1 + n2)));
Now all you need to do is have a crossProduct for every series.
let final = numbers.map(series).reduce(crossProduct);
And there you have it:
let numbers = [4, 5, 6];
let series = num => Array.from({ length: num + 1 }, (n, i) => i);
let crossProduct = (a1, a2) => Array.prototype.concat.call(...a1.map(n1 => a2.map(n2 => n1 + n2)));
let final = numbers.map(series).reduce(crossProduct);
console.log(final);
Edit: If it's from 0 to the number before (e.g. 4 is [0, 1, 2, 3]) then just take the + 1 in the series function.
2nd Edit: Less objects created for your crossProduct:
let crossProduct = (a1, a2) => {
let resultingSet = [];
for(let i = 0; i < a1.length; i++)
for(let j = 0; j < a2.length; j++)
resultingSet.push(a1[i] + a2[j]);
return resultingSet;
} //only one array is created
And if you want to avoid having the series on memory all the time:
let numbers = [4, 5, 6];
let series = function* (num){
for(let i = 0; i < num; i++){
yield i;
}
}
let crossProduct = (set, num) => {
let resultingSet = [];
for(let i = 0; i < set.length; i++){
for(let j of series(num)){
resultingSet.push(set[i] + j);
}
}
return resultingSet;
}
let final = numbers.reduce(crossProduct, [0]);
console.log(final);

Another solution that doesn't consume alot of memory and fairly efficient is by using an array that represnt the value of the indexes and update it each iteration.
first you create an array that represent in each element the amount of iterations you need to run in order to update the indexes respectively for example for this array [1, 2, 3 ,4 ,5] you will get:
[280, 140, 20, 5, 1] this means that index[0] will be updated each 280 iterations, index[1] will be updated each 140 iterations and so on..
totally you will run arr[n] * arr[n-1] * arr[n-2] * .... * arr[0] iterations as you did with ordinary nested for loop.
var arr = [1, 2, 7, 4, 5];
var indexes = Array.from({length: arr.length}, () => 0);
iterationsPerElement = arr.map((_, i) => arr.slice(i+1).reduce((acc, elem) => acc * elem, 1));
var totalIterations = iterationsPerElement[0] * arr[0];
for(var iteration = 1; iteration <= totalIterations; iteration++) {
// sum those indexes
console.log(`sum = ${indexes.reduce((acc, index) => acc + index, 0)}`);
// update indexes
for(i = 0; i < indexes.length; i++) {
if(iteration % iterationsPerElement[i] == 0) {
indexes[i]++;
// empty the indexes on the right
for(var j=i+1; j <indexes.length; j++) {
indexes[j] = 0;
}
}
}
}

Find the N'th highest number in unsorted array

Today in a interview, I was told to write a program which will output the nth highest number in the unsorted array,
I solved this using javascript, the program is as follows,
var fn50 = function(){
var reverseSort = function(myArray,highest){
var x = 0,
y = 0,
z = 0,
temp = 0,
totalNum = myArray.length, // total numbers in array
flag = false, // is the numbers sorted in reverse while iteration
isAchieved = false; // whether we achieved the nth highest
while(x < totalNum){
y = x + 1; // start comparing 'yth' number which is next to 'xth' number.
if(y < totalNum){
// start comparing 'xth' with the next number, and if 'xth' number less than its next position number, just swipe them
for(z = y; z < totalNum; z++){
if(myArray[x] < myArray[z]){
temp = myArray[z];
myArray[z] = myArray[x];
myArray[x] = temp;
flag = true; // if number swiping done ?
}else{
continue;
}
}
}
if(flag){
flag = false;
}else{
x++; // x holds the max number in series, now move to next position to find next highest number
if(x > highest){ // if x is what the desired max number which we want flag it and break the loop to escape further iteration.
isAchieved = true;
}
}
if(isAchieved){
break;
}
}
print(myArray[(highest - 1)]);
};
reverseSort([12,56,78,34,11,100,95],4); // passing the unsorted array of number's, and finding the 4th highest number
};
fn50();
I got the desired output i.e the answer is 56 from the above array which is the 4th highest number.
But the interviewer told for a better solution.
Can you tell me or give me a hint, how can there be a better solution.
Some data structure technique ?

Sorting and selecting the kth highest number needs O(n log(n)) time, where n is the number of elements. In the bibliography, there is the medians of medians algorithm, that allows us to select the kth highest or smallest in linear time, no matter what value k has. You could find out if the interviewer had this kind of algorithm in mind, if you asked if the desired element could be the median of the array. The median is the element at position n / 2, which is considered the hardest case.
But for an interview, it's a complicated algorithm. If k is in general small, you can apply the following algorithm, based on the structure of a heap. You convert the array into a heap in linear time. Then you extract k times the largest element. This will take O(n + k * log(n)) time, which for small k = ο(n / log(n) is linear.
Having k be as small as a constant number, like 4, has an even simpler linear algorithm. Every time we scan the array and remove the largest. This will take O(k * n) time and because k is constant, O(k * n) = O(n).

I tried to implement this with quickselect as JuniorCompressor suggested.
But I wonder if that is really the fastest possible way. I guess the calculation of the pivot could be made more efficient.
var nthLargest = function(list, n) {
var i, a = 0, b = list.length, m, pivot;
if(n < 1) throw new Error("n too small");
if(list.length < n) throw new Error("n too large");
list = list.slice(0);
var swap = function(list, a, b) {
var temp = list[a];
list[a] = list[b];
list[b] = temp;
}
//returns the index of the first element in the right sublist
var partition = function(list, pivot, a, b) {
b--;
while(a <= b) {
if(list[a] <= pivot) a++;
else if(list[b] > pivot) b--;
else swap(list, a, b);
}
return a;
}
while(b - a > 1) {
for(i = a, pivot = 0; i < b; i++) {
pivot += list[i];
}
pivot /= b-a;
m = partition(list, pivot, a, b);
if(b - m >= n) a = m; // select right sublist
else { // select left sublist
if(m === b) return list[a]; // all elements in sublist are identical
n -= b - m;
b = m;
}
}
if(n !== 1) throw new Error();
return list[a];
}

<script>
function nthlargest(array, highest) {
array.sort();
l=array.length;
if(highest>l)
return("undefined");
else
return(array[l-highest+1]);
}
document.write(nthlargest([23, 652, 43, 89, 23, 90, 99, 88], 2));
</script>

Sorting is the simplest way I can think of.
But it appears you created your own sorting implementation.
Why not use the Array.sort function?
function nthHighest(numbers, n) {
var sorted = numbers.sort(function (a, b) {
return a - b;
});
return sorted[sorted.length - n];
}
You could simplify the arithmetic by doing a reverse sort, which just means b - a instead of a - b, then you don't need to pull from the back, which is just a cosmetic improvement.
function nthHighest(numbers, n) {
var sorted = numbers.sort(function (a, b) {
return b - a;
});
return sorted[n - 1];
}
You could also iterate over the array once, copying each element into a new array in sorted order and again, taking the Nth to last element, using underscore to implement a binary search.
function nthHighest(numbers, n) {
var sorted = [];
numbers.forEach(function (number) {
sorted.splice(_.sortedIndex(sorted, number), 0, number);
});
return sorted[numbers.length - n];
}
But this is basically a spin on the same concept: sort and take N. This approach would also perform better with a linked list than a pure array due to the restructuring, but that can be a separate exercise.

I came up with my own solution as it goes:
const nthlargest = (arr, n) => {
let newArr = [arr[0]];
for (let index = 1; index < arr.length; index++) {
const element = arr[index];
// push to end
if (element > newArr[index - 1]) {
newArr.push(element);
} else {
let insertPos = 0;
// if greater than first and less than last
if (newArr[0] < element && element < newArr[index - 1]) {
for (let j = 0; j < newArr.length; j++) {
if (newArr[j] > element) {
insertPos = j;
}
}
}
//insert at specified pos
newArr.splice(insertPos, 0, element);
}
}
return newArr[n];
}
console.log(nthlargest([43, 56, 23, 89, 88, 90, 99, 652], 4));
// counting from 0
// 89
This is without sorting the original array else it would be much easier.

using the sort array method
function nthLargest(array, n){
array.sort(function(a, b) {
return b - a; //organises the array in descending organises
});
let i = n - 1; //i is the index of the nth largest number
console.log(array[i]);
}

def funcc(arr, n):
max=0
k=0
while (n>0):
n-=1
for i in arr:
if (i>max):
max=i
if(n>0):
arr.remove(max)
max=0
return max
a = [1,2,3,4,19,10,5,11,22,8]
k = funcc(a, 3)
print(k)

const data = [30, 8, 2, 350, 4, 63, 98];
let max = 0;
var nth = 5;
for (let i = 0; i < nth; i++) {
max = 0;
for (let j = 0; j < data.length; j++) {
if (data[j] > max) {
max = data[j];
}
}
var ind = data.indexOf(max);
console.log(data);
const key = data.slice(ind, ind + 1);
}
console.log(nth + " largest number is ", max);

Implementing merge sort in Javascript

So I'm working on Khan Academy's Algorithms course, and am trying to implement a recursive merge sort in Javascript. Here is my code so far:
var mergeSort = function(array, p, r) {
if(r>p) {
var q = floor(r/2);
mergeSort(array, p, q);
mergeSort(array, q+1, r);
merge(array, p, q, r);
}
};
merge is a function provided by Khan Academy to merge the subarrays back together. It is giving me the error: 'Uncaught RangeError: Maximum call stack size exceeded'.
EDIT: More details: I am fairly sure the error is in my code, there code is purposefully obfuscated and unreadable because the user needs to implement it themselves in a later challenge.
Here is the code that actually calls the mergeSort function initially and declares the array:
var array = [14, 7, 3, 12, 9, 11, 6, 2];
mergeSort(array, 0, array.length-1);
println("Array after sorting: " + array);
Program.assertEqual(array, [2, 3, 6, 7, 9, 11, 12, 14]);
And here is the code for the merge function, although it is obfuscared as I mentioned above:
var merge = function(array, p, q, r) {
var a = [],
b = [],
c = p,
d, e;
for (d = 0; c <= q; d++, c++) {
a[d] = array[c];
}
for (e = 0; c <= r; e++, c++) {
b[e] = array[c];
}
c = p;
for (e = d = 0; d < a.length && e < b.length;) {
if (a[d] < b[e]) {
array[c] = a[d];
d++;
} else {
array[c] = b[e];
e++;
}
c++;
}
for (; d < a.length;) {
array[c] = a[d];
d++;
c++;
}
for (; e < b.length;) {
array[c] = b[e];
e++;
c++;
}
};
They also require my code inside of the mergeSort function be of the form:
if (____) {
var ____ = ____;
mergeSort(____,____,____);
mergeSort(____,____,____);
merge(____,____,____,____);
}

Mergesort is a divide and conquer algorithm which splits the range of indices to sort in two, sorts them separately, and then merges the results.
Therefore, middle variable should be the arithmetic mean of from and to, not the half of to.
I have renamed the variables to make it more understandable:
var mergeSort = function(array, from, to) {
if(to > from) {
var middle = Math.floor( (from+to)/2 ); // Arithmetic mean
mergeSort(array, from, middle);
mergeSort(array, middle+1, to);
merge(array, from, middle, to);
}
};

q is supposed to be the half way point between p and r, but you've failed to take into account that the starting point (i.e. p) might not be 0 when you do this:
var q = floor(r/2);
You need to do something like:
var q = floor((r-p)/2) + p;
Although as #Oriol points out the middle point is actually exactly the same as the arithmetic mean and so the calculation can be simplified.

Just for the sake of implementation of the merge sort in JS
function merge(arr){
if(arr.length <= 1) return arr;
let mid = Math.floor(arr.length/2);
let left = merge( arr.slice(0, mid));
let right = merge(arr.slice(mid))
function mergeSort(arr1, arr2) {
let result = [];
let i=0;
let j=0;
while(i< arr1.length && j < arr2.length) {
if(arr1[i] < arr2[j]){
result.push(arr1[i])
i++;
} else {
result.push(arr2[j])
j++;
}
}
while(i < arr1.length) {
result.push(arr1[i])
i++;
}
while(j < arr2.length){
result.push(arr2[j])
j++;
}
return result
}
return mergeSort(left,right)
}
console.log(merge([1,4,3,6,2,11,100,44]))

High level strategy
the merge sort works on the principle that it's better to sort two numbers than to sort a large list of numbers. So what it does is that it breaks down two lists into their individual numbers then compares them one to the other then building the list back up. Given a list of say 1,3,2, it'll split the list into 1 and 3,2 then compare 3 to 2 to get 2,3 and then compare the list of 2,3 to 1. If 1 is less than the first element in list of 2,3 it simply places 1 in front of the list. Just like that, the list of 1,3,2 is sorted into 1,2,3.
pseudocode-steps
1.take first member of first array
2.compare to first member of second array
3.if first member of first array is less than first member
of second array
4.put first member into sorted array
5.now merge first array minus first element
with second array
6.else take first member of second array
merge first array with remaining portion of second array
7.return sorted array
function mergesorted(list1, list2) {
let sorted = [];
if (list1.length === 0 || list2.length === 0) {
return list1.length === 0 ? list2.length === 0 ? [] : list2 : list1;
}
if (list1[0] < list2[0]) {
sorted.push(list1[0])
return sorted.concat(mergesorted(list1.slice(1), list2))
} else {
sorted.push(list2[0])
return sorted.concat(mergesorted(list1, list2.slice(1)))
}
}
console.log(mergesorted([1, 2], [3, 4])) //should: [1,2,3,4]
console.log(mergesorted([1,2], [3])) //should: [1,2,3]

Merge sort implementation, stable and in place
function sort(arr, start, end) {
if (start >= end-1) return;
var mid = start + ~~((end-start)/2);
// after calling this
// left half and right half are both sorted
sort(arr, start, mid);
sort(arr, mid, end);
/**
* Now we can do the merging
*/
// holding merged array
// size = end-start
// everything here will be copied back to original array
var cache = Array(end-start).fill(0);
var k=mid;
// this is O(n) to arr[start:end]
for (var i=start, r=0;i<mid;r++,i++) {
while (k<end && arr[k] < arr[i]) cache[r++] = arr[k++];
cache[r] = arr[i];
}
// k marks the position of the element in the right half that is bigger than all elements in the left
// effectively it tells that we should only copy start~start+k element from cache to nums
// because the rests are the same
for (var i=0;i<k-start;i++) arr[i+start]=cache[i];
}

A nice solution:
const merge = (left, right) => {
const resArr = [];
let leftIdx = 0;
let rightIdx = 0;
while (leftIdx < left.length && rightIdx < right.length) {
left[leftIdx] < right[rightIdx]
? resArr.push(left[leftIdx++])
: resArr.push(right[rightIdx++]);
}
return [...resArr, ...left.slice(leftIdx), ...right.slice(rightIdx)];
};
const mergeSort = arr =>
arr.length <= 1
? arr
: merge(
mergeSort(arr.slice(0, Math.floor(arr.length / 2))),
mergeSort(arr.slice(Math.floor(arr.length / 2)))
);

try this
const mergeTwoSortedArr = (arr1 = [], arr2 = []) => {
let i = 0,
j = 0,
sortedArr = [];
while(i < arr1.length || j < arr2.length) {
if(arr1[i] <= arr2[j] || (i < arr1.length && j >= arr2.length)) {
sortedArr.push(arr1[i]);
i++;
}
if(arr2[j] <= arr1[i] || (j < arr2.length && i >= arr1.length)) {
sortedArr.push(arr2[j]);
j++;
}
}
return sortedArr;
}
const mergeSort = (arr) => {
if(arr.length === 0 || arr.length === 1) {
return arr;
}
var mid = Math.floor(arr.length / 2);
var left = mergeSort(arr.slice(0, mid));
var right = mergeSort(arr.slice(mid));
return mergeTwoSortedArr(left, right);
}
when trying this
mergeSort([5, 2, 1, 4]) //[1, 2, 4, 5]
Time Complexity O(nlogn)
logn --> decomposition
n comaprison
Time complexity O(nlogn)