Develop Reference

Persistent Bugger - Help to get rid of some 0

I need some help with a task which is about creating a function that only accepts integer numbers to then multiply each other until getting only one digit. The answer would be the times:
Example: function(39) - answer: 3
Because 3 * 9 = 27, 2 * 7 = 14, 1 * 4 = 4 and 4 has only one digit
Example2: function(999) - answer: 4
Because 9 * 9 * 9 = 729, 7 * 2 * 9 = 126, 1 * 2 * 6 = 12, and finally 1 * 2 = 2
Example3: function(4) - answer: 0
Because it has one digit already
So trying to figure out how to solve this after many failures, I ended up coding this:
function persistence(num) {
let div = parseInt(num.toString().split(""));
let t = 0;
if(Number.isInteger(num) == true){
if(div.length > 1){
for(let i=0; i<div.length; i++){
div = div.reduce((acc,number) => acc * number);
t += 1;
div = parseInt(div.toString().split(""))
if(div.length == 1){
return t } else {continue}
} return t
} else { return t }
} else { return false }
}
console.log(persistence(39),3);
console.log(persistence(4),0);
console.log(persistence(25),2);
console.log(persistence(999),4);
/*
output: 0 3
0 0
0 2
0 4
*/
It seems I could solve it, but the problem is I don't know why those 0s show up. Besides I'd like to receive some feedback and if it's possible to improve those codes or show another way to solve it.
Thanks for taking your time to read this.
///EDIT///
Thank you all for helping and teaching me new things, I could solve this problem with the following code:
function persistence(num){
let t = 0;
let div;
if(Number.isInteger(num) == true){
while(num >= 10){
div = (num + "").split("");
num = div.reduce((acc,val) => acc * val);
t+=1;
} return t
}
}
console.log(persistence(39));
console.log(persistence(4));
console.log(persistence(25));
console.log(persistence(999));
/*output: 3
0
2
4
*/

You've got a few issues here:
let div = parseInt(num.toString().split("")); You're casting an array to a number, assuming you're trying to extract the individual numbers into an array, you were close but no need for the parseInt.
function persistence(input, count = 0) {
var output = input;
while (output >= 10) {
var numbers = (output + '').split('');
output = numbers.reduce((acc, next) {
return Number(next) * acc;
}, 1);
count += 1;
}
​
return count;
};
For something that needs to continually check, you're better off using a recurssive function to check the conditions again and again, this way you won't need any sub loops.
Few es6 features you can utilise here to achieve the same result! Might be a little too far down the road for you to jump into es6 now but here's an example anyways using recursion!
function recursive(input, count = 0) {
// convert the number into an array for each number
const numbers = `${input}`.split('').map(n => Number(n));
// calculate the total of the values
const total = numbers.reduce((acc, next) => next * acc, 1);
// if there's more than 1 number left, total them up and send them back through
return numbers.length > 1 ? recursive(total, count += 1) : count;
};
console.log(recursive(39),3);
console.log(recursive(4),0);
console.log(recursive(25),2);
console.log(recursive(999),4);

function persistance (num) {
if (typeof num != 'number') throw 'isnt a number'
let persist = 0
while(num >= 10) {
let size = '' + num
size = size.length
// Get all number of num
const array = new Array(size).fill(0).map((x, i) => {
const a = num / Math.pow(10, i)
const b = parseInt(a, 10)
return b % 10
})
console.log('here', array)
// actualiser num
num = array.reduce((acc, current) => acc * current, 1)
persist++
}
return persist
}
console.log(persistance(39))
console.log(persistance(999))

console.log() can take many argument...
So for example, console.log("A", "B") will output "A" "B".
So all those zeros are the output of your persistence function... And the other number is just the number you provided as second argument.
So I guess you still have to "persist"... Because your function always returns 0.
A hint: You are making this comparison: div.length > 1...
But div is NOT an array... It is a number, stringified, splitted... And finally parsed as integer.
;) Good luck.
Side note, the calculation you are attempting is known as the Kaprekar's routine. So while learning JS with it... That history panel of the recreational mathematic wil not hurt you... And may be a good line in a job interview. ;)
My best hint
Use the console log within the function to help you degug it. Here is your unchanged code with just a couple of those.
function persistence(num) {
let div = parseInt(num.toString().split(""));
let t = 0;
console.log("div.length", div.length)
if (Number.isInteger(num) == true) {
if (div.length > 1) {
for (let i = 0; i < div.length; i++) {
div = div.reduce((acc, number) => acc * number);
t += 1;
div = parseInt(div.toString().split(""));
if (div.length == 1) {
console.log("return #1")
return t;
} else {
continue;
}
}
console.log("return #2")
return t;
} else {
console.log("return #3")
return t;
}
} else {
console.log("return #4")
return false;
}
}
console.log(persistence(39), 3);
console.log(persistence(4), 0);
console.log(persistence(25), 2);
console.log(persistence(999), 4);

Optimizing and finding edge cases that I might have missed - 2 coding interview questions

Background - I took an online coding test and was presented with questions similar to this, I did rather poorly on it compared to the hidden grading criteria and I was hoping to get another pair of eyes to look at it and maybe help point out some of my mistakes.
Practice Test questions -
Task: Given an integer inject the number 5 into it to make the largest possible integer
Conditions: (-80000...80000) range needed to handle
Expected input: int
Expected output: int
Testcase: -999 -> -5999
80 -> 850
var lrgInt = function(num) {
var stringInt = num.toString();
for (let i = 0; i < stringInt.length; i++) {
if (stringInt.charAt(i) === "-") {
return parseInt([stringInt.slice(0, 1), '5', stringInt.slice(1)].join(''));
}else if (stringInt.charAt(i) < 5) {
return parseInt([stringInt.slice(0, i), '5', stringInt.slice(i)].join(''));
}
}
return parseInt([stringInt.slice(0, stringInt.length), '5', stringInt.slice(stringInt.length)].join(''));
};
Task: Determine the number of operations done on a number following the conditions to reduce it to 0.
Conditions:
- If the number is odd, subtract 1
- If the number is even, divide by 2
Expected input: int
Expected output: int
var operations = 0;
var numberOfSteps = function(num) {
if (num === 0){
return operations;
}else if (num % 2 == 0) {
operations++;
return numberOfSteps(num/2);
} else {
operations++;
return numberOfSteps(num-1);
}
};

For the second question, you could add one plus the result of recursion with the adjusted number without having a global counter.
function numberOfSteps(number) {
if (!number) return 0;
if (number % 2) return 1 + numberOfSteps(number - 1);
return 1 + numberOfSteps(number / 2);
}
console.log(numberOfSteps(5)); // 5 4 2 1 0

For the first question, we make the observation that if the number is positive, we want to inject the 5 before the first digit less than 5, but if it's negative then we want to inject it before the first digit greater than 5. For the second problem, we can just use a simple while loop.
function largestNum(num) {
if (num == 0) {
// this edge case is weird but I'm assuming this is what they want
return 50;
}
var negative = num < 0;
var numAsStr = Math.abs(num).toString();
var inj = -1;
for (var i = 0; i < numAsStr.length; i++) {
var cur = parseInt(numAsStr[i], 10);
if ((!negative && cur < 5) || (negative && cur > 5)) {
// we found a place to inject, break
inj = i;
break;
}
}
if (inj == -1) {
// didn't inject anywhere so inject at the end
inj = numAsStr.length;
}
return (
(negative ? -1 : 1) *
parseInt(numAsStr.substr(0, inj) + "5" + numAsStr.substr(inj))
);
}
function numSteps(num) {
var steps = 0;
while (num != 0) {
if (num % 2) {
// it's odd
num--;
} else {
num /= 2;
}
steps++;
}
return steps;
}

How to a count a specific digit in a number with javascript

I am trying to write a block of code which will separate digits (with modulus operator) in a number first and count how many digit "6" are there in the number.
I tried so many things but I think I have logic problem with the way I think.
output = [];
var count = 0;
while (a > 0){
output.push(a % 10);
a = Math.floor(a/10);
if(a == 6){
count++;
}
}
When I run this code on Safari, It shows the entered number as it is, but it shows "0" for the variable count.

Math.floor(a/10) doesn't give the current digit. a % 10 gives the current digit.
You have check if the current digit a % 10 is 6.
Live Example:
let output = [];
let count = 0;
let a = 1667;
while (a > 0) {
let digit = a % 10;
output.push(digit);
if (digit == 6) {
count++;
}
a = Math.floor(a / 10);
}
console.log(count);

You know the last digit, so you can subtract it and divide with 10, instead of using Math.floor.
let number = 1626364656; // has 5 sixes
let sixesCount = 0;
while (number > 0) {
const digit = number % 10;
if (digit === 6) {
sixesCount++;
}
number = (number - digit) / 10;
}
console.log('Found', sixesCount, 'sixes.'); // "Found 5 sixes."

Check whether a number is divisible by another number If not make it divisable in Javascript

I want to check whether a number (7) is divisible by another number (5), If the number is divisible by the number then I need to return the same number. If the number is not divisible by another number I need to make it divisible and return the updated value.
var i =7;
if (i % 5 == 0) {
alert("divisible by 5");
} else {
alert("divisible not by 5");
}
Here if the condition satisfy then I need to return the same value. If the condition is not satisfied I need to add the required number and make it next divisible. (Like 7 is not divisible by 5 so I need add 3 to 7 and return the value 10 which is divisible by 5).
Are there any Math functions exists to implement the same?

What you want, it seems like, is this:
function roundTo(n, d) {
return Math.floor((n + d - 1) / d) * d;
}
For n 10 and d 5, you get 10 back. For n 7 and d 5, you also get 10. What the code does is add one less than the divisor to the input number, and then divides by the divisor. It then gets rid of any fractional part (Math.floor()) and multiplies by the divisor again.

You can do that by using a simple while loop:
function doThat(number, divider) {
while(number % divider !== 0) {
number++;
}
return number;
}
doThat(12, 5); // => returns 15
Here's a fiddle: https://jsfiddle.net/rdko8dmb/

You could use this algorithm:
i % n = r, where i = 7, n = 5, and r = 2.
Then, make i = i + (n - r). i.e. i = 7 + (5-2) → 10. Then you can use this for your division.

Try this
function divisible(dividend, divisor){
if (dividend % divisor == 0) {
return dividend;
} else {
var num = dividend + (divisor-(dividend % divisor));
return num;
}
}
var res = divisible(7, 5);
console.log(res);

Here is the fastest and cleanest way to do that:
function shift(number, divider)
{
return number + (divider - (number % divider)) % divider;
}
It takes number and moves it up by the difference from (our unit) divider to the remainder to make it divisible by the divider. The % divider makes sure that if there is no difference number doesn't get pushed up by a full unit of the divider.

I do not know if this will work for all numbers... But you might try this
7 % 5 = 2. If you subtract 2 from 5 you will get 3... This is the number you need to add to 7. 16 % 5 = 1 subtract 1 from 5 = 4 .. 4 + 16 = 20
Another example 16 % 13 = 3 ... 13-3 = 10 16+10 = 26 26/13 = 2

Here's an example of function that finds next higher natural number that is divisble by y
https://www.jschallenger.com/javascript-basics/find-next-higher-number
Option 1
while (x % y !== 0) x++;
return x;
}
Option 2
if(x % y == 0){
return x;
}
else{
for(i = x+1; i > x; i++){
if(i % y == 0){
return i;
}
}
}

Implementation of Luhn algorithm

I am trying to implement simple validation of credit card numbers. I read about the Luhn algorithm on Wikipedia:
Counting from the check digit, which is the rightmost, and moving
left, double the value of every second digit.
Sum the digits of the products (e.g., 10: 1 + 0 = 1, 14: 1 + 4 = 5)
together with the undoubled digits from the original number.
If the total modulo 10 is equal to 0 (if the total ends in zero)
then the number is valid according to the Luhn formula; else it is
not valid.
On Wikipedia, the description of the Luhn algorithm is very easily understood. However, I have also seen other implementations of the Luhn algorithm on Rosetta Code and elsewhere (archived).
Those implementations work very well, but I am confused about why they can use an array to do the work. The array they use seems to have no relation with Luhn algorithm, and I can't see how they achieve the steps described on Wikipedia.
Why are they using arrays? What is the significance of them, and how are they used to implement the algorithm as described by Wikipedia?

Unfortunately none of the codes above worked for me. But I found on GitHub a working solution
// takes the form field value and returns true on valid number
function valid_credit_card(value) {
// accept only digits, dashes or spaces
if (/[^0-9-\s]+/.test(value)) return false;
// The Luhn Algorithm. It's so pretty.
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;
}

the array [0,1,2,3,4,-4,-3,-2,-1,0] is used as a look up array for finding the difference between a number in 0-9 and the digit sum of 2 times its value. For example, for number 8, the difference between 8 and (2*8) = 16 -> 1+6 = 7 is 7-8 = -1.
Here is graphical presentation, where {n} stand for sum of digit of n
[{0*2}-0, {1*2}-1, {2*2}-2, {3*2}-3, {4*2}-4, {5*2}-5, {6*2}-6, {7*2}-7....]
| | | | | | | |
[ 0 , 1 , 2 , 3 , 4 , -4 , -3 , -2 ....]
The algorithm you listed just sum over all the digit and for each even spot digit, look up the the difference using the array, and apply it to the total sum.

Compact Luhn validator:
var luhn_validate = function(imei){
return !/^\d+$/.test(imei) || (imei.split('').reduce(function(sum, d, n){
return sum + parseInt(((n + imei.length) %2)? d: [0,2,4,6,8,1,3,5,7,9][d]);
}, 0)) % 10 == 0;
};
Works fine for both CC and IMEI numbers. Fiddle: http://jsfiddle.net/8VqpN/

Lookup tables or arrays can simplify algorithm implementations - save many lines of code - and with that increase performance... if the calculation of the lookup index is simple - or simpler - and the array's memory footprint is affordable.
On the other hand, understanding how the particular lookup array or data structure came to be can at times be quite difficult, because the related algorithm implementation may look - at first sight - quite different from the original algorithm specification or description.
Indication to use lookup tables are number oriented algorithms with simple arithmetics, simple comparisons, and equally structured repetition patterns - and of course - of quite finite value sets.
The many answers in this thread go for different lookup tables and with that for different algorithms to implement the very same Luhn algorithm. Most implementations use the lookup array to avoid the cumbersome figuring out of the value for doubled digits:
var luhnArr = [0, 2, 4, 6, 8, 1, 3, 5, 7, 9];
//
// ^ ^ ^ ^ ^ ^ ^ ^ ^ ^
// | | | | | | | | | |
//
// - d-igit=index: 0 1 2 3 4 5 6 7 8 9
// - 1st
// calculation: 2*0 2*2 2*2 2*3 2*4 2*5 2*6 2*7 2*8 2*9
// - intermeduate
// value: = 0 = 2 = 4 = 6 = 8 =10 =12 =14 =16 =18
// - 2nd
// calculation: 1+0 1+2 1+4 1+6 1+8
//
// - final value: 0 2 4 6 8 =1 =3 =5 =7 =9
//
var luhnFinalValue = luhnArray[d]; // d is numeric value of digit to double
An equal implementation for getting the luhnFinalValue looks like this:
var luhnIntermediateValue = d * 2; // d is numeric value of digit to double
var luhnFinalValue = (luhnIntermediateValue < 10)
? luhnIntermediateValue // (d ) * 2;
: luhnIntermediateValue - 10 + 1; // (d - 5) * 2 + 1;
Which - with the comments in above true and false terms - is of course simplified:
var luhnFinalValue = (d < 5) ? d : (d - 5) * 2 + 1;
Now I'm not sure if I 'saved' anything at all... ;-) especially thanks the value-formed or short form of if-then-else. Without it, the code may look like this - with 'orderly' blocks
and embedded in the next higher context layer of the algorithm and therefore luhnValue:
var luhnValue; // card number is valid when luhn values for each digit modulo 10 is 0
if (even) { // even as n-th digit from the the end of the string of digits
luhnValue = d;
} else { // doubled digits
if (d < 5) {
luhnValue = d * 2;
} else {
lunnValue = (d - 5) * 2 + 1;
}
}
Or:
var luhnValue = (even) ? d : (d < 5) ? d * 2 : (d - 5) * 2 + 1;
Btw, with modern, optimizing interpreters and (just in time) compilers, the difference is only in the source code and matters only for readability.
Having come that far with explanation - and 'justification' - of the use of lookup tables and comparison to straight forward coding, the lookup table looks now a bit overkill to me. The algorithm without is now quite easy to finish - and it looks pretty compact too:
function luhnValid(cardNo) { // cardNo as a string w/ digits only
var sum = 0, even = false;
cardNo.split("").reverse().forEach(function(dstr){ d = parseInt(dstr);
sum += ((even = !even) ? d : (d < 5) ? d * 2 : (d - 5) * 2 + 1);
});
return (sum % 10 == 0);
}
What strikes me after going through the explanation exercise is that the initially most enticing implementation - the one using reduce() from #kalypto - just lost totally its luster for me... not only because it is faulty on several levels, but more so because it shows that bells and whistles may not always 'ring the victory bell'. But thank you, #kalypto, it made me actually use - and understand - reduce():
function luhnValid2(cardNo) { // cardNo as a string w/ digits only
var d = 0, e = false; // e = even = n-th digit counted from the end
return ( cardNo.split("").reverse().reduce(
function(s,dstr){ d = parseInt(dstr); // reduce arg-0 - callback fnc
return (s + ((e = !e) ? d : [0,2,4,6,8,1,3,5,7,9][d]));
} // /end of callback fnc
,0 // reduce arg-1 - prev value for first iteration (sum)
) % 10 == 0
);
}
To be true to this thread, some more lookup table options have to be mentioned:
how about just adjust varues for doubled digits - as posted by #yngum
how about just everything with lookup tables - as posted by #Simon_Weaver - where also the values for the non-doubled digits are taken from a look up table.
how about just everything with just ONE lookup table - as inspired by the use of an offset as done in the extensively discussed luhnValid() function.
The code for the latter - using reduce - may look like this:
function luhnValid3(cardNo) { // cardNo as a string w/ digits only
var d = 0, e = false; // e = even = n-th digit counted from the end
return ( cardNo.split("").reverse().reduce(
function(s,dstr){ d = parseInt(dstr);
return (s + [0,1,2,3,4,5,6,7,8,9,0,2,4,6,8,1,3,5,7,9][d+((e=!e)?0:10)]);
}
,0
) % 10 == 0
);
}
And for closing lunValid4() - very compact - and using just 'old fashioned' (compatible) JavaScript - with one single lookup table:
function luhnValid4(cardNo) { // cardNo as a string w/ digits only
var s = 0, e = false, p = cardNo.length; while (p > 0) { p--;
s += "01234567890246813579".charAt(cardNo.charAt(p)*1 + ((e=!e)?0:10)) * 1; }
return (s % 10 == 0);
}
Corollar: Strings can be looked at as lookup tables of characters... ;-)
A perfect example of a nice lookup table application is the counting of set bits in bits lists - bits set in a a (very) long 8-bit byte string in (an interpreted) high-level language (where any bit operations are quite expensive). The lookup table has 256 entries. Each entry contains the number of bits set in an unsigned 8-bit integer equal to the index of the entry. Iterating through the string and taking the unsigned 8-bit byte equal value to access the number of bits for that byte from the lookup table. Even for low-level language - such as assembler / machine code - the lookup table is the way to go... especially in an environment, where the microcode (instruction) can handle multiple bytes up to 256 or more in an (single CISC) instruction.
Some notes:
numberString * 1 and parseInt(numberStr) do about the same.
there are some superfluous indentations, parenthesis,etc... supporting my brain in getting the semantics quicker... but some that I wanted to leave out, are actually required... when
it comes to arithmetic operations with short-form, value-if-then-else expressions as terms.
some formatting may look new to you; for examples, I use the continuation comma with the
continuation on the same line as the continuation, and I 'close' things - half a tab - indented to the 'opening' item.
All formatting is all done for the human, not the computer... 'it' does care less.
algorithm datastructure luhn lookuptable creditcard validation bitlist

A very fast and elegant implementation of the Luhn algorithm following:
const isLuhnValid = function luhn(array) {
return function (number) {
let len = number ? number.length : 0,
bit = 1,
sum = 0;
while (len--) {
sum += !(bit ^= 1) ? parseInt(number[len], 10) : array[number[len]];
}
return sum % 10 === 0 && sum > 0;
};
}([0, 2, 4, 6, 8, 1, 3, 5, 7, 9]);
console.log(isLuhnValid("4112344112344113".split(""))); // true
console.log(isLuhnValid("4112344112344114".split(""))); // false
On my dedicated git repository you can grab it and retrieve more info (like benchmarks link and full unit tests for ~50 browsers and some node.js versions).
Or you can simply install it via bower or npm. It works both on browsers and/or node.
bower install luhn-alg
npm install luhn-alg

If you want to calculate the checksum, this code from this page is very concise and in my random tests seems to work.
NOTE: the verification algorithmns on this page do NOT all work.
// Javascript
String.prototype.luhnGet = function()
{
var luhnArr = [[0,1,2,3,4,5,6,7,8,9],[0,2,4,6,8,1,3,5,7,9]], sum = 0;
this.replace(/\D+/g,"").replace(/[\d]/g, function(c, p, o){
sum += luhnArr[ (o.length-p)&1 ][ parseInt(c,10) ]
});
return this + ((10 - sum%10)%10);
};
alert("54511187504546384725".luhnGet());​
Here's my findings for C#

function luhnCheck(value) {
return 0 === (value.replace(/\D/g, '').split('').reverse().map(function(d, i) {
return +['0123456789','0246813579'][i % 2][+d];
}).reduce(function(p, n) {
return p + n;
}) % 10);
}
Update: Here's a smaller version w/o string constants:
function luhnCheck(value) {
return !(value.replace(/\D/g, '').split('').reverse().reduce(function(a, d, i) {
return a + d * (i % 2 ? 2.2 : 1) | 0;
}, 0) % 10);
}
note the use of 2.2 here is to make doubling d roll over with an extra 1 when doubling 5 to 9.

Code is the following:
var LuhnCheck = (function()
{
var luhnArr = [0, 2, 4, 6, 8, 1, 3, 5, 7, 9];
return function(str)
{
var counter = 0;
var incNum;
var odd = false;
var temp = String(str).replace(/[^\d]/g, "");
if ( temp.length == 0)
return false;
for (var i = temp.length-1; i >= 0; --i)
{
incNum = parseInt(temp.charAt(i), 10);
counter += (odd = !odd)? incNum : luhnArr[incNum];
}
return (counter%10 == 0);
}
})();
The variable counter is the sum of all the digit in odd positions, plus the double of the digits in even positions, when the double exceeds 10 we add the two numbers that make it (ex: 6 * 2 -> 12 -> 1 + 2 = 3)
The Array you are asking about is the result of all the possible doubles
var luhnArr = [0, 2, 4, 6, 8, 1, 3, 5, 7, 9];
0 * 2 = 0 --> 0
1 * 2 = 2 --> 2
2 * 2 = 4 --> 4
3 * 2 = 6 --> 6
4 * 2 = 8 --> 8
5 * 2 = 10 --> 1+0 --> 1
6 * 2 = 12 --> 1+2 --> 3
7 * 2 = 14 --> 1+4 --> 5
8 * 2 = 16 --> 1+6 --> 7
9 * 2 = 18 --> 1+8 --> 9
So for example
luhnArr[3] --> 6 (6 is in 3rd position of the array, and also 3 * 2 = 6)
luhnArr[7] --> 5 (5 is in 7th position of the array, and also 7 * 2 = 14 -> 5 )

Another alternative:
function luhn(digits) {
return /^\d+$/.test(digits) && !(digits.split("").reverse().map(function(checkDigit, i) {
checkDigit = parseInt(checkDigit, 10);
return i % 2 == 0
? checkDigit
: (checkDigit *= 2) > 9 ? checkDigit - 9 : checkDigit;
}).reduce(function(previousValue, currentValue) {
return previousValue + currentValue;
}) % 10);
}

Alternative ;) Simple and Best
<script>
// takes the form field value and returns true on valid number
function valid_credit_card(value) {
// accept only digits, dashes or spaces
if (/[^0-9-\s]+/.test(value)) return false;
// The Luhn Algorithm. It's so pretty.
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;
}
console.log(valid_credit_card("5610591081018250"),"valid_credit_card Validation");
</script>
Best Solution here
http://plnkr.co/edit/34aR8NUpaKRCYpgnfUbK?p=preview
with all test cases passed according to
http://www.paypalobjects.com/en_US/vhelp/paypalmanager_help/credit_card_numbers.htm
and the credit goes to
https://gist.github.com/DiegoSalazar/4075533

const LuhnCheckCard = (number) => {
if (/[^0-9-\s]+/.test(number) || number.length === 0)
return false;
return ((number.split("").map(Number).reduce((prev, digit, i) => {
(!(( i & 1 ) ^ number.length)) && (digit *= 2);
(digit > 9) && (digit -= 9);
return prev + digit;
}, 0) % 10) === 0);
}
console.log(LuhnCheckCard("4532015112830366")); // true
console.log(LuhnCheckCard("gdsgdsgdsg")); // false

I worked out the following solution after I submitted a much worse one for a test..
function valid(number){
var splitNumber = parseInt(number.toString().split(""));
var totalEvenValue = 0;
var totalOddValue = 0;
for(var i = 0; i < splitNumber.length; i++){
if(i % 2 === 0){
if(splitNumber[i] * 2 >= 10){
totalEvenValue += splitNumber[i] * 2 - 9;
} else {
totalEvenValue += splitNumber[i] * 2;
}
}else {
totalOddValue += splitNumber[i];
}
}
return ((totalEvenValue + totalOddValue) %10 === 0)
}
console.log(valid(41111111111111111));

I recently wrote a solution using Javascript, I leave the code here for anyone who can help:
// checksum with Luhn Algorithm
const luhn_checksum = function(strIn) {
const len = strIn.length;
let sum = 0
for (let i = 0; i<10; i += 1) {
let factor = (i % 2 === 1) ? 2: 1
const v = parseInt(strIn.charAt(i), 10) * factor
sum += (v>9) ? (1 + v % 10) : v
}
return (sum * 9) % 10
}
// teste exampple on wikipedia:
// https://en.wikipedia.org/wiki/Luhn_algorithm
const strIn = "7992739871"
// The checksum of "7992739871" is 3
console.log(luhn_checksum(strIn))
If you understand this code above, you will have no problem converting it to any other language.
For example in python:
def nss_checksum(nss):
suma = 0
for i in range(10):
factor = 2 if (i % 2 == 1) else 1
v = int(nss[i]) * factor
suma += (1 + v % 10) if (v >9) else v
return (suma * 9) % 10
For more info, check this:
https://en.wikipedia.org/wiki/Luhn_algorithm
My Code(En español):
https://gist.github.com/fitorec/82a3e27fae3bab709a07c19c71c3a8d4

def validate_credit_card_number(card_number):
if(len(str(card_number))==16):
group1 = []
group1_double = []
after_group_double = []
group1_sum = 0
group2_sum = 0
group2 = []
total_final_sum = 0
s = str(card_number)
list1 = [int(i) for i in list(s)]
for i in range(14, -1, -2):
group1.append(list1[i])
for x in group1:
b = 0
b = x * 2
group1_double.append(b)
for j in group1_double:
if(j > 9):
sum_of_digits = 0
alias = str(j)
temp1 = alias[0]
temp2 = alias[1]
sum_of_digits = int(temp1) + int(temp2)
after_group_double.append(sum_of_digits)
else:
after_group_double.append(j)
for i in after_group_double:
group1_sum += i
for i in range(15, -1, -2):
group2.append(list1[i])
for i in group2:
group2_sum += i
total_final_sum = group1_sum + group2_sum
if(total_final_sum%10==0):
return True
else:
return False
card_number= 1456734512345698 #4539869650133101 #1456734512345698 # #5239512608615007
result=validate_credit_card_number(card_number)
if(result):
print("credit card number is valid")
else:
print("credit card number is invalid")