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Optimizing the largest palindrome from product of two three digit numbers?

I am working on an interview question which I was asked in which I was supposed to write a program to find the largest palindrome from product of two three digit numbers.
Here is the question
I came up with this brute force approach which starts from bottom.
public class LargestPalindromeQuestion {
public static void main(String[] args) {
int value = 0;
for (int i = 100; i <= 999; i++) {
for (int j = i; j <= 999; j++) {
int value1 = i * j;
if (isPalindrome(value1) && value < value1) {
value = value1;
}
}
}
System.out.println(value);
}
private static boolean isPalindrome(final int product) {
int p = product;
int reverse = 0;
while (p != 0) {
reverse *= 10;
reverse += p % 10;
p /= 10;
}
return reverse == product;
}
}
They asked me what are the optimizations I can do in this program? I mentioned that we can try pruning the search space and optimize checking step for each item in the search space but then I am confuse how would I make this work in my above solution?
What are the optimizations we can do in this program? Right now it is executing 810000 steps to find the largest palindrome.
What is the least number of steps we can execute to find the largest palindrome in two three digit numbers?

The program looks very good to me. I would make the i loop count from 999 down to 100, and I would only check j values that would actually give a larger product than the current maximum.
This program is able to finish surprisingly soon, at i == 952 to be precise. The mathematical reason for this is that once the solution 906609 (993 * 913) is found, it will no longer be possible to find a larger palindrome where the larger factor is less than the square-root of 906609, which is 952.160....
public static void main(String[] args) {
int value = 0;
for (int i = 999; i >= 100; i--) {
int r = value / i;
if (r >= i) {
System.out.println("We broke at i = " + i);
break;
}
for (int j = i; j > r; j--) {
int value1 = i * j;
if (isPalindrome(value1)) {
value = value1;
break;
}
}
}
System.out.println(value);
}

One pretty simple way of optimizing this would be to simply start with the highest 3-digit numbers instead of the smallest. Since the solution will most likely be closer to the pair (999 , 999) than to (100 , 100).

One useful mechanism to prune the search tree is to notice that the highest digit of the product a * b doesn't change often. E.g.
a = 111; b = 112 a*b = 12432
; b = 113 a*b = 12543
; b = 114 a*b = 12654
; ...
; b = 180 a*b = 19980
; b = 181 a*b = 20091 = (19980 + a)
Thus, for all the values in between (a = 111, a < b < 181), one already knows the MSB, which must equal to the LSB or (a % 10) * (b % 10) % 10 == MSB.
e.g.
LSB = 1 --> a % 10 == 1, b % 10 == 1
OR a % 10 == 3, b % 10 == 7
OR a % 10 == 7, b % 10 == 3
OR a % 10 == 9, b % 10 == 9
Most of the time there's either none, or just one candidate in set 'b' to be checked for any pair MSB, a % 10.

The least number of steps I could get to is 375. Consider multiplying the three-digit number, a1a2a3, by the three-digit number, b1b2b3:
JavaScript code:
var modHash = new Array(10);
var iterations = 0;
for (var i=1; i<10; i++){
modHash[i] = {0: [0]}
for (var j=1; j<10; j++){
iterations ++;
var r = i * j % 10;
if (modHash[i][r])
modHash[i][r].push(j);
else
modHash[i][r] = [j];
}
}
var highest = 0;
function multiples(x,y,carry,mod){
for (var i in modHash[x]){
var m = (10 + mod - i - carry) % 10;
if (modHash[y][m]){
for (var j in modHash[x][i]){
for (var k in modHash[y][m]){
iterations ++;
var palindrome = num(9,modHash[y][m][k],x,9,modHash[x][i][k],y);
if (x == 3 && mod == 0){
console.log(x + " * " + modHash[x][i][j] + " + "
+ y + " * " + modHash[y][m][k] + ": " + palindrome);
}
var str = String(palindrome);
if (str == str.split("").reverse().join("") && palindrome > highest){
highest = palindrome;
}
}
}
}
}
}
function num(a1,a2,a3,b1,b2,b3){
return (100*a1 + 10*a2 + a3)
* (100*b1 + 10*b2 + b3);
}
var a3b3s = [[7,7,4],[9,1,0],[3,3,0]];
for (var i in a3b3s){
for (var mod=0; mod<10; mod++){
var x = a3b3s[i][0],
y = a3b3s[i][1],
carry = a3b3s[i][2];
multiples(x,y,carry,mod);
}
}
console.log(highest);
console.log("iterations: " + iterations);
Output:
3 * 0 + 3 * 0: 815409
3 * 7 + 3 * 3: 907809
3 * 4 + 3 * 6: 908109
3 * 1 + 3 * 9: 906609
3 * 8 + 3 * 2: 907309
3 * 5 + 3 * 5: 908209
3 * 2 + 3 * 8: 907309
3 * 9 + 3 * 1: 906609
3 * 6 + 3 * 4: 908109
3 * 3 + 3 * 7: 907809
906609
iterations: 375

First optimize isPalindrome by seperating 6 digits as 3 digits. i.e. N = ABCDEF => a = ABC = N/1000, b = DEF = N%1000; Then reverse b and return a==reversed_b;
Secondly while producing palindromes loop through till max_palindrome_so_far/999 which is the minimum value that you would use. max_palindrome_so_far is initially equals N.
public class Solution {
public static boolean isPalindrome(int n){
int a = n/1000;
int b = n%1000;
int d, r = 0, i = 3;
while(i-- > 0){
d = b%10;
r = r*10 + d;
b = b/10;
}
if (a == r)
return true;
return false;
}
public static void main(String[] args) {
Scanner in = new Scanner(System.in);
int t = in.nextInt();
for(int a0 = 0; a0 < t; a0++){
int n = in.nextInt();
int r=0, m=n;
int i,j;
for(i = 999;i>=100;i--){
for(j = 999;j>=m/999;j--){
if (i*j < n && i*j > 100000 && isPalindrome(i*j)){
r = Math.max(i*j, r);
m = r;
}
}
}
// System.out.println(i + " * " + j + " = " + i*j);
System.out.println(r);
}
}
}

Coin Combinations Through Brute Force

I have some code that will brute force solve the following problem:
Given a set of x coins and a target sum to reach, what is the fewest number of coins required to reach that target?
The code so far:
import java.util.ArrayList;
import java.util.Arrays;
public class coinsSum {
public static int min = Integer.MAX_VALUE;
public static int[] combination;
public static final int TARGET = 59;
public static void main(String[] args) {
long start = System.nanoTime();
int[] validCoins = new int[] {1, 2, 5, 10, 20};
Arrays.sort(validCoins);
int len = validCoins.length;
ArrayList<Integer> maxList = new ArrayList<Integer>();
for(int c : validCoins) {
maxList.add(TARGET / c);
}
int[] max = new int[len];
for(int i = 0; i < len; i++) {
max[i] = maxList.get(i).intValue();
}
permutations(new int[len], max, validCoins, 0); // bread&butter
if(min != Integer.MAX_VALUE) {
System.out.println();
System.out.println("The combination " + Arrays.toString(combination) + " uses " + min + " coins to make the target of: " + TARGET);
} else {
System.out.println("The target was not reachable using these coins");
}
System.out.println("TOOK: " + (System.nanoTime() - start) / 1000000 + "ms");
}
public static void permutations(int[] workspace, int[] choices, int[] coins, int pos) {
if(pos == workspace.length) {
int sum = 0, coinCount = 0;
System.out.println("TRYING " + Arrays.toString(workspace));
for(int a = 0; a < coins.length; a++) {
sum += workspace[a] * coins[a];
coinCount += workspace[a];
}
if(sum == TARGET) {
// System.out.println(Arrays.toString(n)); //valid combinations
if(coinCount < min) {
min = coinCount;
combination = workspace;
System.out.println(Arrays.toString(combination)+" uses " + min + " coins");
}
}
return;
}
for(int i = 0; i <= choices[pos]; i++) {
workspace[pos] = i;
permutations(workspace, choices, coins, pos + 1);
}
}
}
This solution uses recursion, is there any way to do compute combinations in java using loops?
How else can all possible combinations be iterated through?

You can sort the array of coins. Then go from right to left, keep subtracting from the target value, untill the coin is bigger from the remaining value of target. Move left in the array of coins and repeat the process.
Example:
{1, 2, 5, 10, 20}
num = 59
Try coins from right to left:
59 - 20 = 39
So far coins used [20]
39 - 20 = 19
So far coins used [20,20]
19 - 20 = -1, Can't use 20!
19 - 10 = 9
So far coins used [20,20,10]
9 - 10 = -1, Can't use 10!
9 - 5 = 4
So far coins used [20,20,10,5]
4 - 5 = -1, Can't use 5!
4 - 2 = 2
So far coins used [20,20,10,5,2]
2 - 2 = 0
So far coins used [20,20,10,5,2,2]
Total coin used 6

Here is a solution in python that uses dynamic programming to find the minimum number of coins to reach a target value.
The algorithm works as follow
dp[i][target] = minimum number of coins required required to acheive target using first i coin
dp[i][target] = min(dp[i-1][target],dp[i-1][target-coin[i]]+1)
dp[i-1][target] denotes not using the ith coin
dp[i-1][target-coin[i]] denotes making use of ith coin
Since for each coin your are checking wheather to include it or not the algorithm is enumerating through all possible combination.
Here is an space optimized version of the above algorithm
maxvalue = 10 ** 9
def minchange(coins, target):
no_of_coins = len(coins)
dp = [maxvalue for i in range(target + 1) ]
dp[0] = 0
for i in range(no_of_coins):
for j in range(coins[i], target + 1):
dp[j] = min(dp[j], dp[j - coins[i]] + 1)
return dp[target]

I found a dynamic programming approach which is definitely not optimised, but isn't too bad for target numbers up to 10000 if anyone is interested
import java.util.*;
public class coinSumMinimalistic {
public static final int TARGET = 12003;
public static int[] validCoins = {1, 3, 5, 6, 7, 10, 12};
public static void main(String[] args) {
Arrays.sort(validCoins);
sack();
}
public static void sack() {
Map<Integer, Integer> coins = new TreeMap<Integer, Integer>();
coins.put(0, 0);
int a = 0;
for(int i = 1; i <= TARGET; i++) {
if(a < validCoins.length && i == validCoins[a]) {
coins.put(i, 1);
a++;
} else coins.put(i, -1);
}
for(int x = 2; x <= TARGET; x++) {
if(x % 5000 == 0) System.out.println("AT: " + x);
ArrayList<Integer> list = new ArrayList<Integer>();
for(int i = 0; i <= x / 2; i++) {
int j = x - i;
list.add(i);
list.add(j);
}
coins.put(x, min(list, coins));
}
System.out.println("It takes " + coins.get(TARGET) + " coins to reach the target of " + TARGET);
}
public static int min(ArrayList<Integer> combos, Map<Integer, Integer> coins) {
int min = Integer.MAX_VALUE;
int total = 0;
for(int i = 0; i < combos.size() - 1; i += 2) {
int x = coins.get(combos.get(i));
int y = coins.get(combos.get(i + 1));
if(x < 0 || y < 0) continue;
else {
total = x + y;
if(total > 0 && total < min) {
min = total;
}
}
}
int t = (min == Integer.MAX_VALUE || min < 0) ? -1:min;
return t;
}
public static void print(Map<Integer, Integer> map) {
for(Map.Entry<Integer, Integer> entry : map.entrySet()) {
System.out.println("[" + entry.getKey() + ", " + entry.getValue() + "]");
}
System.out.println();
}
}

adding fractions using recursion e=1+1/1!+1/2!+1/3!+

I need to write a recursive method to compute the following series:
e = 1+1/1!+1/2!+1/3!+...
This is what I have so far.
public static void main(String[] args)
{ System.out.println("enter n :");
int n =scan.nextInt();
double h = fact(n);
System.out.println(" e = ");
}
public double fact(int n)
{
if (n == 1)
return 1;
else
return ???;
}
}

So, assuming the n input you're taking is the starting denominator for the smallest fraction you'd add...
(For example, given n = 10, you want to add 1 through 1/10)
Then you need to set up your method so that when you call fact(10), it's going to return the sum of 1/10 plus the result of fact(9), or more generically, 1/n + fact(1/n-1);
So, you're looking for something like this:
public double fact(int n) {
if (n < 0) {
return 0.0;
} else if (n == 0) {
return 1.0;
} else {
return (1.0/n + fact(n-1))
}
}
Also, please note the changes to the base cases. When n < 0, we just return 0.0, because if I recall correctly, the factorial of any negative number is always 0, right?
Meanwhile, the base case should be n==0, not n == 1. Your series starts with 1 + 1/1. Note that 1 is not 1/0 or 1/nothing, it's just 1/1. We can't return 1/n when n is 0. For the series to calculate correctly, we have to add the first return the first element of the series in the case of n = 0.
And keep in mind, as with all recursive functions, very large values of n will cause a stack overflow.

Here are a couple of resources:
Math is fun
"Yes you can! But you need to get into a subject called the "Gamma
Function", which is beyond this simple page.
Half Factorial
But I can tell you the factorial of half (½) is half of the square
root of pi = (½)√π, and so some "half-integer" factorials are:"
More specifically you want the Gamma Function
Apache commons has an implementation of this function.
Discussion on Math Exchange
And here is an implementation from Princeton
public class Gamma {
static double logGamma(double x) {
double tmp = (x - 0.5) * Math.log(x + 4.5) - (x + 4.5);
double ser = 1.0 + 76.18009173 / (x + 0) - 86.50532033 / (x + 1)
+ 24.01409822 / (x + 2) - 1.231739516 / (x + 3)
+ 0.00120858003 / (x + 4) - 0.00000536382 / (x + 5);
return tmp + Math.log(ser * Math.sqrt(2 * Math.PI));
}
static double gamma(double x) { return Math.exp(logGamma(x)); }
public static void main(String[] args) {
double x = Double.parseDouble(args[0]);
System.out.println("Gamma(" + x + ") = " + gamma(x));
System.out.println("log Gamma(" + x + ") = " + logGamma(x));
}
}

Calculating e^n recursively is very expensive. It is O(n^2) and it is hard to know when to stop. Instead I suggest you do it iteratively.
static final int runs = 20000;
static volatile int exp = 1;
static volatile int n = 18;
static volatile double dontOptimiseAway;
public static void main(String[] args) throws InterruptedException {
System.out.println("Math.exp(1)=" + Math.exp(1));
System.out.println("exp_iter(18)=" + exp_iter(18));
System.out.println("exp_recurse(18)=" + exp_recurse(18));
for (int t = 0; t < 3; t++) {
System.out.printf("exp(1), exp_iter(18), exp_recurse(18) took %,d / %,d / %,d ns on average%n",
timeMathExp(), timeExpIter(), timeExpRecurse());
}
}
public static long timeMathExp() {
long start = System.nanoTime();
for (int i = 0; i < runs; i++)
dontOptimiseAway = Math.exp(exp);
return (System.nanoTime() - start) / runs;
}
public static long timeExpIter() {
long start = System.nanoTime();
for (int i = 0; i < runs; i++)
dontOptimiseAway = exp_iter(n);
return (System.nanoTime() - start) / runs;
}
public static long timeExpRecurse() {
long start = System.nanoTime();
for (int i = 0; i < runs; i++)
dontOptimiseAway = exp_recurse(n);
return (System.nanoTime() - start) / runs;
}
public static double exp_iter(int n) {
double exp = 0, x = 1;
for (int i = 2; i <= n; i++)
exp += (x /= i);
return 2 + exp;
}
public static double exp_recurse(int n) {
return n <= 0 ? 1 : 1.0 / fact(n) + exp_recurse(n - 1);
}
public static double fact(int n) {
return n <= 1 ? 1 : n * fact(n - 1);
}
prints
Math.exp(1)=2.718281828459045
exp_iter(18)=2.718281828459045
exp_recurse(18)=2.7182818284590455
exp(1), exp_iter(18), exp_recurse(18) took 111 / 191 / 760 ns on average
exp(1), exp_iter(18), exp_recurse(18) took 75 / 78 / 558 ns on average
exp(1), exp_iter(18), exp_recurse(18) took 69 / 66 / 552 ns on average

write the code as below and call it from main class.
public static double recursiveFun(double value){
if (value==1)
return 1.0;
if (value==2){
return (1/(value-1) + 1/value);
}
else
return recursiveFun(value-1) + 1/value;
}

Homework: how to write own multiplication of big numbers?

In my project I have to deal with multiplication of big numbers ( greater then java.long ) stared in my own BigNumber class as int[]. Basically I need to implement something like this :
157 x
121 y
----
157 result1
314 + result2
157 + result3
------
18997 finalResult
But how do I implement it?
I thought about expanding result2,3 with zeros (3140, 15700) and adding them. But first I somehow need to navigate between each digit of y and multiply it by each digit of x.

Use the diagonal approach. Make an array, and multiply each digit by each other digit and fill in the numbers in each cell.
36 x 92
3 6
+-----+-----+
| 2 / | 5 / |
9 | / | / |
| / 7 | / 4 |
+-----+-----+
| 0 / | 1 / |
2 | / | / |
| / 6 | / 2 |
+-----+-----+
Add the numbers on each diagonal. Move from the least-significant digit (at the lower right) to the most (upper left).
2 2 (least-significant)
(6 + 1 + 4) = 11 (make this 1, and carry the 1 to the next digit) 1
(5 + 7 + 0 + 1(carried)) = 13 (make this 3, and carry the 1) 3
2 + 1(carried) = 3 3 (most-significant)
The answer's 3312.
Make a two-dimensional array of your digits. Fill the array with the multiplications of the single digits together.
Write some logic to scrape the diagonals as I did above.
This should work for arbitrarily large numbers (as long as you still have memory left).

Here's the code I had written. Basically same as manual multiplication. Pass the two big numbers as strings to this function, the result is returned as a string.
public String multiply(String num1, String num2){
int product, carry=0, sum=0;
String result = new String("");
String partial = new String("");
ArrayList<String> partialList = new ArrayList<String>();
/* computing partial products using this loop. */
for(int j=num2.length()-1 ; j>=0 ; j--) {
for(int i=num1.length()-1 ; i>=0 ; i--) {
product = Integer.parseInt((new Character(num1.charAt(i))).toString()) *
Integer.parseInt((new Character(num2.charAt(j))).toString()) + carry;
carry = product/10;
partial = Integer.toString(product%10) + partial;
}
if(carry != 0)
partial = Integer.toString(carry) + partial;
partialList.add(partial);
partial = "";
carry = 0;
}
/* appending zeroes incrementally */
for(int i=0 ; i<partialList.size() ; i++)
partialList.set(i, partialList.get(i) + (Long.toString( (long)java.lang.Math.pow(10.0,(double)i))).substring(1) );
/* getting the size of the largest partial product(last) */
int largestPartial = partialList.get(partialList.size()-1).length();
/* prefixing zeroes */
int zeroes;
for(int i=0 ; i<partialList.size() ; i++) {
zeroes = largestPartial - partialList.get(i).length();
if(zeroes >= 1)
partialList.set(i, (Long.toString( (long)java.lang.Math.pow(10.0,(double)zeroes))).substring(1) + partialList.get(i) );
}
/* to compute the result */
carry = 0;
for(int i=largestPartial-1 ; i>=0 ; i--) {
sum = 0;
for(int j=0 ; j<partialList.size() ; j++)
sum = sum + Integer.parseInt(new Character(partialList.get(j).charAt(i)).toString());
sum = sum + carry;
carry = sum/10;
result = Integer.toString(sum%10) + result;
}
if(carry != 0)
result = Integer.toString(carry) + result;
return result;
}

I would avoid the headaches of writing your own and just use the java.math.BigInteger class. It should have everything you need.

Separating out the carrying and the digit multiplication:
def carries(digitlist):
digitlist.reverse()
for idx,digit in enumerate(digitlist):
if digit>9:
newdigit = digit%10
carry = (digit-newdigit)/10
digitlist[idx] = newdigit
if idx+1 > len(digitlist)-1:
digitlist.append(carry)
else:
digitlist[idx+1] += carry
digitlist.reverse()
return True
def multiply(first,second):
digits = [0 for place in range(len(first)+len(second))]
for fid,fdig in enumerate(reversed(first)):
for sid,sdig in enumerate(reversed(second)):
offset = fid+sid
mult = fdig*sdig
digits[offset] += mult
digits.reverse()
carries(digits)
return digits
def prettify(digitlist):
return ''.join(list(`i` for i in digitlist))
Then we can call it:
a = [1,2,3,4,7,6,2]
b = [9,8,7,9]
mult = multiply(a,b)
print prettify(a)+"*"+prettify(b)
print "calc:",prettify(mult)
print "real:",int(prettify(a))*int(prettify(b))
Yields:
1234762*9879
calc: 12198213798
real: 12198213798
Of course the 10s in the carries function and the implicit decimal representation in prettify are the only thing requiring this to be base 10. Adding an argument could make this base n, so you could switch to base 1000 in order to reduce the numbers of blocks and speed up the calculation.

I have implemented this in C++. refer to this for logic...
#include <iostream>
#include <deque>
using namespace std;
void print_num(deque<int> &num) {
for(int i=0;i < num.size();i++) {
cout<<num[i];
}
cout<<endl;
}
deque<int> sum(deque<int> &oppA, deque<int> &oppB) {
if (oppA.size() == 0) return oppB;
if (oppB.size() == 0) return oppA;
deque<int> result;
unsigned int carry = 0;
deque<int>::reverse_iterator r_oppA = oppA.rbegin();
deque<int>::reverse_iterator r_oppB = oppB.rbegin();
while ((r_oppA != oppA.rend()) && (r_oppB != oppB.rend())) {
int tmp = *r_oppA + *r_oppB + carry;
result.push_front(tmp % 10);
carry = tmp / 10;
r_oppB++;
r_oppA++;
}
while (r_oppA != oppA.rend()) {
int tmp = *r_oppA + carry;
result.push_front(tmp % 10);
carry = tmp / 10;
r_oppA++;
}
while (r_oppB != oppB.rend()) {
int tmp = *r_oppB + carry;
result.push_front(tmp % 10);
carry = tmp / 10;
r_oppB++;
}
return result;
}
deque<int> multiply(deque<int>& multiplicand, deque<int>& multiplier) {
unsigned int carry = 0;
deque<int> result;
int deci_cnt = 0;
deque<int>::reverse_iterator r_multiplier = multiplier.rbegin();
deque<int> tmp_result;
while (r_multiplier != multiplier.rend()) {
for (int i=0; i<deci_cnt ;i++) {
tmp_result.push_front(0);
}
deque<int>::reverse_iterator r_multiplicand = multiplicand.rbegin();
while (r_multiplicand != multiplicand.rend()) {
int tmp = (*r_multiplicand) * (*r_multiplier) + carry;
tmp_result.push_front(tmp % 10);
carry = tmp / 10;
r_multiplicand++;
}
if (carry != 0) {
tmp_result.push_front(carry);
carry = 0;
}
result = sum(result, tmp_result);
deci_cnt++;
tmp_result.clear();
r_multiplier++;
}
return result;
}
deque<int> int_to_deque(unsigned long num) {
deque<int> result;
if (num == 0) {
result.push_front(0);
}
while (num > 0) {
result.push_front(num % 10);
num = num / 10;
}
return result;
}
int main() {
deque<int> num1 = int_to_deque(18446744073709551615ULL);
deque<int> num2 = int_to_deque(18446744073709551615ULL);
deque<int> result = multiply(num1, num2);
print_num(result);
return 0;
}
Output: 340282366920928463426481119284349108225

You're going to have to treat each int in the array as a single "digit". Instead of using base 10 where each digit goes from 0 to 9, you'll have to use base 2^32 = 4294967296, where every digit goes from 0 to 4294967295.
I would first implement addition, as your algorithm for multiplication might use addition as an auxiliary.

As this is for homework I'll give a few hints.
You could approach it the same way you show your example, using strings to hold numbers of any length and implementing:
add one number to another
multiply as your example by appending zeroes and calling the addition method per step (so for multiply with 20, append the "0" and addd that number twice
The addition method you can build by retrieving the char[] from the strings, allocate a result char[] that is 1 longer than the longest and add like you would do on paper from the end back to the start of both arrays.
The end result will not be the best performing solution, but it it easy to show it is correct and will handle any length numbers (as long they will fit a Java string.)
Update
Ok, if you solved adding two numbers, you could:
implement multiplication by 10
implement multiplication by repeated addition like in your example
or:
implement multiplication by 2 (left shift)
implement a binary multiplication via the same concept, only this time x 2 and add once
to illustrate the latter,
13
5 x
----
13 x 1
26 x 0
52 x 1
---- +
65
note that the 1 0 1 are the bits in the number (5) you multiply with and 26 = 13 x 2, 52 = 26 x 2. Your get the idea :-)

did it my own way :
int bigger = t1.length;
int smaller = t2.length;
int resultLength = bigger + smaller;
int []resultTemp = new int[resultLength];
int []result = new int[bigger + smaller];
int []temporary = new int[resultLength+1];
int z = resultLength-1;
int zet = z;
int step = 0;
int carry = 0;
int modulo = 0;
for(int i=smaller-1; i>=0; i--){
for(int k = bigger-1; k>= -1; k--){
if(k == -1 && carry != 0 ){
resultTemp[z] = carry;
carry = 0;
break;
}
else if(k == -1 && carry == 0){
resultTemp[z] = 0;
break;
}
resultTemp[z] = carry + t1[k]*t2[i];
carry = 0;
if( resultTemp[z] > 9 ){
modulo = resultTemp[z] % 10;
carry = resultTemp[z]/10;
resultTemp[z] = modulo;
}
else{
resultTemp[z] = resultTemp[z];
}
z--;
}
temporary = add(resultTemp, result);
result = copyArray(temporary);
resultTemp = clear(resultTemp);
z = zet;
step++;
z = z - step;
}
then I check the sign.

Since this is homework... Are you sure using an int array is your best shot?
I tried to implement something similar a year ago for performance in a research
project, and we ended up going with concatenated primitives..
Using this you can take advantage of what's already there, and "only" have to worry about overflows near the ends.. This might prove to be fairly simple when you implement your multiplication with <<'s (bit shift lefts) and additions..
Now if you want a real challenge try to implement a modulo... ;)

You can check the below solution which teaches us both multiplication and addition of bigger numbers. Please comment if it can be improved.
public static void main(String args[]) {
String s1 = "123666666666666666666666666666666666666666666666669999999999999999999999999666666666666666666666666666666666666666666666666666666666666666666";
String s2 = "45688888888888888888888888888888888888888888888888888888888888888888888888888888888888888888888888888888888888888888";
System.out.println(multiply(s1, s2));
}
private static String multiply(String s1, String s2) {
int[] firstArray = convert(s1);
int[] secondArray = convert(s2);
//System.out.println(Arrays.toString(firstArray));
//System.out.println(Arrays.toString(secondArray));
// pass the arrays and get the array which is holding the individual
// rows while we multiply using pen and paper
String[] result = doMultiply(firstArray, secondArray);
//System.out.println(Arrays.toString(result));
// Now we are almost done lets format them as we like
result = format(result);
//System.out.println(Arrays.toString(result));
//Add elements now and we are done
String sum="0";
for(String s:result){
sum=add(sum,s);
}
return sum;
}
private static String[] doMultiply(int[] firstArray, int[] secondArray) {
String[] temp = new String[secondArray.length];
for (int i = secondArray.length - 1; i >= 0; i--) {
int result = 0;
int carry = 0;
int rem = 0;
temp[secondArray.length - 1 - i] = "";
for (int j = firstArray.length - 1; j >= 0; j--) {
result = (secondArray[i] * firstArray[j]) + carry;
carry = result / 10;
rem = result % 10;
temp[secondArray.length - 1 - i] = rem
+ temp[secondArray.length - 1 - i];
}
// if the last carry remains in the last digit
if (carry > 0)
temp[secondArray.length - 1 - i] = carry
+ temp[secondArray.length - 1 - i];
}
return temp;
}
public static int[] convert(String str) {
int[] arr = new int[str.length()];
for (int i = 0; i < str.length(); i++) {
arr[i] = Character.digit(str.charAt(i), 10);
}
return arr;
}
private static String[] format(String[] result) {
for (int i = 0; i < result.length; i++) {
int j = 0;
while (j < i) {
result[i] += "0";
j++;
}
}
return result;
}
public static String add(String num1, String num2) {
//System.out.println("First Number :" + num1);
//System.out.println("Second Number :" + num2);
int max = num1.length() > num2.length() ? num1.length() : num2.length();
int[] numArr1 = new int[max];
int[] numArr2 = new int[max];
for (int i = 0; i < num1.length(); i++) {
numArr1[i] = Integer.parseInt(""
+ num1.charAt(num1.length() - 1 - i));
}
for (int i = 0; i < num2.length(); i++) {
numArr2[i] = Integer.parseInt(""
+ num2.charAt(num2.length() - 1 - i));
}
int carry = 0;
int[] sumArr = new int[max + 1];
for (int k = 0; k < max; k++) {
int tempsum = numArr1[k] + numArr2[k] + carry;
sumArr[k] = tempsum % 10;
carry = 0;
if (tempsum >= 10) {
carry = 1;
}
}
sumArr[max] = carry;
/* System.out.println("Sum :"
+ new StringBuffer(Arrays.toString(sumArr)).reverse()
.toString().replaceAll(",", "").replace("[", "")
.replace("]", "").replace(" ", ""));*/
return new StringBuffer(Arrays.toString(sumArr)).reverse().toString()
.replaceAll(",", "").replace("[", "").replace("]", "")
.replace(" ", "");
}

I think this will help you
import java.util.ArrayList;
import java.util.List;
public class Multiply {
static int len;
public static void main(String[] args) {
System.out.println(multiply("123456789012345678901","123456789012345678901");
}
private static ArrayList<Integer> addTheList(List<ArrayList<Integer>> myList) {
ArrayList<Integer> result=new ArrayList<>();
for(int i=0;i<len;i++)
{
result.add(0);
}
int index=0;
for(int i=0;i<myList.size();i++)
{
ArrayList<Integer> a=new ArrayList<>(myList.get(index));
ArrayList<Integer> b=new ArrayList<>(myList.get(index+1));
for (int j = 0; j < a.size()||j < b.size(); i++) {
result.add(a.get(i) + b.get(i));
}
}
return result;
}
private static ArrayList<Integer> multiply(ArrayList<Integer> list1, Integer integer) {
ArrayList<Integer> result=new ArrayList<>();
int prvs=0;
for(int i=0;i<list1.size();i++)
{
int sum=(list1.get(i)*integer)+prvs;
System.out.println(sum);
int r=sum/10;
int m=sum%10;
if(!(r>0))
{
result.add(sum);
}
else
{
result.add(m);
prvs=r;
}
if(!(i==(list1.size()-1)))
{
prvs=0;
}
}
if(!(prvs==0))
{
result.add(prvs);
}
return result;
}
private static ArrayList<Integer> changeToNumber(String str1) {
ArrayList<Integer> list1=new ArrayList<>();
for(int i=0;i<str1.length();i++)
{
list1.add(Character.getNumericValue(str1.charAt(i)));
}
return list1;
}
public static String multiply(String num1, String num2) {
String n1 = new StringBuilder(num1).reverse().toString();
String n2 = new StringBuilder(num2).reverse().toString();
int[] d = new int[num1.length()+num2.length()];
//multiply each digit and sum at the corresponding positions
for(int i=0; i<n1.length(); i++){
for(int j=0; j<n2.length(); j++){
d[i+j] += (n1.charAt(i)-'0') * (n2.charAt(j)-'0');
}
}
StringBuilder sb = new StringBuilder();
//calculate each digit
for(int i=0; i<d.length; i++){
int mod = d[i]%10;
int carry = d[i]/10;
if(i+1<d.length){
d[i+1] += carry;
}
sb.insert(0, mod);
}
//remove front 0's
while(sb.charAt(0) == '0' && sb.length()> 1){
sb.deleteCharAt(0);
}
return sb.toString();
}
}

Way to get number of digits in an int?

Is there a neater way for getting the number of digits in an int than this method?
int numDigits = String.valueOf(1000).length();

Your String-based solution is perfectly OK, there is nothing "un-neat" about it. You have to realize that mathematically, numbers don't have a length, nor do they have digits. Length and digits are both properties of a physical representation of a number in a specific base, i.e. a String.
A logarithm-based solution does (some of) the same things the String-based one does internally, and probably does so (insignificantly) faster because it only produces the length and ignores the digits. But I wouldn't actually consider it clearer in intent - and that's the most important factor.

The logarithm is your friend:
int n = 1000;
int length = (int)(Math.log10(n)+1);
NB: only valid for n > 0.

The fastest approach: divide and conquer.
Assuming your range is 0 to MAX_INT, then you have 1 to 10 digits. You can approach this interval using divide and conquer, with up to 4 comparisons per each input. First, you divide [1..10] into [1..5] and [6..10] with one comparison, and then each length 5 interval you divide using one comparison into one length 3 and one length 2 interval. The length 2 interval requires one more comparison (total 3 comparisons), the length 3 interval can be divided into length 1 interval (solution) and a length 2 interval. So, you need 3 or 4 comparisons.
No divisions, no floating point operations, no expensive logarithms, only integer comparisons.
Code (long but fast):
if (n < 100000) {
// 5 or less
if (n < 100){
// 1 or 2
if (n < 10)
return 1;
else
return 2;
} else {
// 3 or 4 or 5
if (n < 1000)
return 3;
else {
// 4 or 5
if (n < 10000)
return 4;
else
return 5;
}
}
} else {
// 6 or more
if (n < 10000000) {
// 6 or 7
if (n < 1000000)
return 6;
else
return 7;
} else {
// 8 to 10
if (n < 100000000)
return 8;
else {
// 9 or 10
if (n < 1000000000)
return 9;
else
return 10;
}
}
}
Benchmark (after JVM warm-up) - see code below to see how the benchmark was run:
baseline method (with String.length):
2145ms
log10 method: 711ms = 3.02 times
as fast as baseline
repeated divide: 2797ms = 0.77 times
as fast as baseline
divide-and-conquer: 74ms = 28.99
times as fast as baseline
Full code:
public static void main(String[] args) throws Exception {
// validate methods:
for (int i = 0; i < 1000; i++)
if (method1(i) != method2(i))
System.out.println(i);
for (int i = 0; i < 1000; i++)
if (method1(i) != method3(i))
System.out.println(i + " " + method1(i) + " " + method3(i));
for (int i = 333; i < 2000000000; i += 1000)
if (method1(i) != method3(i))
System.out.println(i + " " + method1(i) + " " + method3(i));
for (int i = 0; i < 1000; i++)
if (method1(i) != method4(i))
System.out.println(i + " " + method1(i) + " " + method4(i));
for (int i = 333; i < 2000000000; i += 1000)
if (method1(i) != method4(i))
System.out.println(i + " " + method1(i) + " " + method4(i));
// work-up the JVM - make sure everything will be run in hot-spot mode
allMethod1();
allMethod2();
allMethod3();
allMethod4();
// run benchmark
Chronometer c;
c = new Chronometer(true);
allMethod1();
c.stop();
long baseline = c.getValue();
System.out.println(c);
c = new Chronometer(true);
allMethod2();
c.stop();
System.out.println(c + " = " + StringTools.formatDouble((double)baseline / c.getValue() , "0.00") + " times as fast as baseline");
c = new Chronometer(true);
allMethod3();
c.stop();
System.out.println(c + " = " + StringTools.formatDouble((double)baseline / c.getValue() , "0.00") + " times as fast as baseline");
c = new Chronometer(true);
allMethod4();
c.stop();
System.out.println(c + " = " + StringTools.formatDouble((double)baseline / c.getValue() , "0.00") + " times as fast as baseline");
}
private static int method1(int n) {
return Integer.toString(n).length();
}
private static int method2(int n) {
if (n == 0)
return 1;
return (int)(Math.log10(n) + 1);
}
private static int method3(int n) {
if (n == 0)
return 1;
int l;
for (l = 0 ; n > 0 ;++l)
n /= 10;
return l;
}
private static int method4(int n) {
if (n < 100000) {
// 5 or less
if (n < 100) {
// 1 or 2
if (n < 10)
return 1;
else
return 2;
} else {
// 3 or 4 or 5
if (n < 1000)
return 3;
else {
// 4 or 5
if (n < 10000)
return 4;
else
return 5;
}
}
} else {
// 6 or more
if (n < 10000000) {
// 6 or 7
if (n < 1000000)
return 6;
else
return 7;
} else {
// 8 to 10
if (n < 100000000)
return 8;
else {
// 9 or 10
if (n < 1000000000)
return 9;
else
return 10;
}
}
}
}
private static int allMethod1() {
int x = 0;
for (int i = 0; i < 1000; i++)
x = method1(i);
for (int i = 1000; i < 100000; i += 10)
x = method1(i);
for (int i = 100000; i < 1000000; i += 100)
x = method1(i);
for (int i = 1000000; i < 2000000000; i += 200)
x = method1(i);
return x;
}
private static int allMethod2() {
int x = 0;
for (int i = 0; i < 1000; i++)
x = method2(i);
for (int i = 1000; i < 100000; i += 10)
x = method2(i);
for (int i = 100000; i < 1000000; i += 100)
x = method2(i);
for (int i = 1000000; i < 2000000000; i += 200)
x = method2(i);
return x;
}
private static int allMethod3() {
int x = 0;
for (int i = 0; i < 1000; i++)
x = method3(i);
for (int i = 1000; i < 100000; i += 10)
x = method3(i);
for (int i = 100000; i < 1000000; i += 100)
x = method3(i);
for (int i = 1000000; i < 2000000000; i += 200)
x = method3(i);
return x;
}
private static int allMethod4() {
int x = 0;
for (int i = 0; i < 1000; i++)
x = method4(i);
for (int i = 1000; i < 100000; i += 10)
x = method4(i);
for (int i = 100000; i < 1000000; i += 100)
x = method4(i);
for (int i = 1000000; i < 2000000000; i += 200)
x = method4(i);
return x;
}
Again, benchmark:
baseline method (with String.length): 2145ms
log10 method: 711ms = 3.02 times as fast as baseline
repeated divide: 2797ms = 0.77 times as fast as baseline
divide-and-conquer: 74ms = 28.99 times as fast as baseline
Edit
After I wrote the benchmark, I took a sneak peak into Integer.toString from Java 6, and I found that it uses:
final static int [] sizeTable = { 9, 99, 999, 9999, 99999, 999999, 9999999,
99999999, 999999999, Integer.MAX_VALUE };
// Requires positive x
static int stringSize(int x) {
for (int i=0; ; i++)
if (x <= sizeTable[i])
return i+1;
}
I benchmarked it against my divide-and-conquer solution:
divide-and-conquer: 104ms
Java 6 solution - iterate and compare: 406ms
Mine is about 4x as fast as the Java 6 solution.

Two comments on your benchmark: Java is a complex environment, what with just-in-time compiling and garbage collection and so forth, so to get a fair comparison, whenever I run a benchmark, I always: (a) enclose the two tests in a loop that runs them in sequence 5 or 10 times. Quite often the runtime on the second pass through the loop is quite different from the first. And (b) After each "approach", I do a System.gc() to try to trigger a garbage collection. Otherwise, the first approach might generate a bunch of objects, but not quite enough to force a garbage collection, then the second approach creates a few objects, the heap is exhausted, and garbage collection runs. Then the second approach is "charged" for picking up the garbage left by the first approach. Very unfair!
That said, neither of the above made a significant difference in this example.
With or without those modifications, I got very different results than you did. When I ran this, yes, the toString approach gave run times of 6400 to 6600 millis, while the log approach topok 20,000 to 20,400 millis. Instead of being slightly faster, the log approach was 3 times slower for me.
Note that the two approaches involve very different costs, so this isn't totally shocking: The toString approach will create a lot of temporary objects that have to be cleaned up, while the log approach takes more intense computation. So maybe the difference is that on a machine with less memory, toString requires more garbage collection rounds, while on a machine with a slower processor, the extra computation of log would be more painful.
I also tried a third approach. I wrote this little function:
static int numlength(int n)
{
if (n == 0) return 1;
int l;
n=Math.abs(n);
for (l=0;n>0;++l)
n/=10;
return l;
}
That ran in 1600 to 1900 millis -- less than 1/3 of the toString approach, and 1/10 the log approach on my machine.
If you had a broad range of numbers, you could speed it up further by starting out dividing by 1,000 or 1,000,000 to reduce the number of times through the loop. I haven't played with that.

Can't leave a comment yet, so I'll post as a separate answer.
The logarithm-based solution doesn't calculate the correct number of digits for very big long integers, for example:
long n = 99999999999999999L;
// correct answer: 17
int numberOfDigits = String.valueOf(n).length();
// incorrect answer: 18
int wrongNumberOfDigits = (int) (Math.log10(n) + 1);
Logarithm-based solution calculates incorrect number of digits in large integers

Using Java
int nDigits = Math.floor(Math.log10(Math.abs(the_integer))) + 1;
use import java.lang.Math.*; in the beginning
Using C
int nDigits = floor(log10(abs(the_integer))) + 1;
use inclue math.h in the beginning

Since the number of digits in base 10 of an integer is just 1 + truncate(log10(number)), you can do:
public class Test {
public static void main(String[] args) {
final int number = 1234;
final int digits = 1 + (int)Math.floor(Math.log10(number));
System.out.println(digits);
}
}
Edited because my last edit fixed the code example, but not the description.

Another string approach. Short and sweet - for any integer n.
int length = ("" + n).length();

Marian's solution adapted for long type numbers (up to 9,223,372,036,854,775,807), in case someone want's to Copy&Paste it.
In the program I wrote this for numbers up to 10000 were much more probable, so I made a specific branch for them. Anyway it won't make a significative difference.
public static int numberOfDigits (long n) {
// Guessing 4 digit numbers will be more probable.
// They are set in the first branch.
if (n < 10000L) { // from 1 to 4
if (n < 100L) { // 1 or 2
if (n < 10L) {
return 1;
} else {
return 2;
}
} else { // 3 or 4
if (n < 1000L) {
return 3;
} else {
return 4;
}
}
} else { // from 5 a 20 (albeit longs can't have more than 18 or 19)
if (n < 1000000000000L) { // from 5 to 12
if (n < 100000000L) { // from 5 to 8
if (n < 1000000L) { // 5 or 6
if (n < 100000L) {
return 5;
} else {
return 6;
}
} else { // 7 u 8
if (n < 10000000L) {
return 7;
} else {
return 8;
}
}
} else { // from 9 to 12
if (n < 10000000000L) { // 9 or 10
if (n < 1000000000L) {
return 9;
} else {
return 10;
}
} else { // 11 or 12
if (n < 100000000000L) {
return 11;
} else {
return 12;
}
}
}
} else { // from 13 to ... (18 or 20)
if (n < 10000000000000000L) { // from 13 to 16
if (n < 100000000000000L) { // 13 or 14
if (n < 10000000000000L) {
return 13;
} else {
return 14;
}
} else { // 15 or 16
if (n < 1000000000000000L) {
return 15;
} else {
return 16;
}
}
} else { // from 17 to ...¿20?
if (n < 1000000000000000000L) { // 17 or 18
if (n < 100000000000000000L) {
return 17;
} else {
return 18;
}
} else { // 19? Can it be?
// 10000000000000000000L is'nt a valid long.
return 19;
}
}
}
}
}

How about plain old Mathematics? Divide by 10 until you reach 0.
public static int getSize(long number) {
int count = 0;
while (number > 0) {
count += 1;
number = (number / 10);
}
return count;
}

I see people using String libraries or even using the Integer class. Nothing wrong with that but the algorithm for getting the number of digits is not that complicated. I am using a long in this example but it works just as fine with an int.
private static int getLength(long num) {
int count = 1;
while (num >= 10) {
num = num / 10;
count++;
}
return count;
}

Can I try? ;)
based on Dirk's solution
final int digits = number==0?1:(1 + (int)Math.floor(Math.log10(Math.abs(number))));

Marian's Solution, now with Ternary:
public int len(int n){
return (n<100000)?((n<100)?((n<10)?1:2):(n<1000)?3:((n<10000)?4:5)):((n<10000000)?((n<1000000)?6:7):((n<100000000)?8:((n<1000000000)?9:10)));
}
Because we can.

no String API, no utils, no type conversion, just pure java iteration ->
public static int getNumberOfDigits(int input) {
int numOfDigits = 1;
int base = 1;
while (input >= base * 10) {
base = base * 10;
numOfDigits++;
}
return numOfDigits;
}
You can go long for bigger values if you please.

Curious, I tried to benchmark it ...
import org.junit.Test;
import static org.junit.Assert.*;
public class TestStack1306727 {
#Test
public void bench(){
int number=1000;
int a= String.valueOf(number).length();
int b= 1 + (int)Math.floor(Math.log10(number));
assertEquals(a,b);
int i=0;
int s=0;
long startTime = System.currentTimeMillis();
for(i=0, s=0; i< 100000000; i++){
a= String.valueOf(number).length();
s+=a;
}
long stopTime = System.currentTimeMillis();
long runTime = stopTime - startTime;
System.out.println("Run time 1: " + runTime);
System.out.println("s: "+s);
startTime = System.currentTimeMillis();
for(i=0,s=0; i< 100000000; i++){
b= number==0?1:(1 + (int)Math.floor(Math.log10(Math.abs(number))));
s+=b;
}
stopTime = System.currentTimeMillis();
runTime = stopTime - startTime;
System.out.println("Run time 2: " + runTime);
System.out.println("s: "+s);
assertEquals(a,b);
}
}
the results are :
Run time 1: 6765
s: 400000000
Run time 2: 6000
s: 400000000
Now I am left to wonder if my benchmark actually means something but I do get consistent results (variations within a ms) over multiple runs of the benchmark itself ... :) It looks like it's useless to try and optimize this...
edit: following ptomli's comment, I replaced 'number' by 'i' in the code above and got the following results over 5 runs of the bench :
Run time 1: 11500
s: 788888890
Run time 2: 8547
s: 788888890
Run time 1: 11485
s: 788888890
Run time 2: 8547
s: 788888890
Run time 1: 11469
s: 788888890
Run time 2: 8547
s: 788888890
Run time 1: 11500
s: 788888890
Run time 2: 8547
s: 788888890
Run time 1: 11484
s: 788888890
Run time 2: 8547
s: 788888890

With design (based on problem). This is an alternate of divide-and-conquer. We'll first define an enum (considering it's only for an unsigned int).
public enum IntegerLength {
One((byte)1,10),
Two((byte)2,100),
Three((byte)3,1000),
Four((byte)4,10000),
Five((byte)5,100000),
Six((byte)6,1000000),
Seven((byte)7,10000000),
Eight((byte)8,100000000),
Nine((byte)9,1000000000);
byte length;
int value;
IntegerLength(byte len,int value) {
this.length = len;
this.value = value;
}
public byte getLenght() {
return length;
}
public int getValue() {
return value;
}
}
Now we'll define a class that goes through the values of the enum and compare and return the appropriate length.
public class IntegerLenght {
public static byte calculateIntLenght(int num) {
for(IntegerLength v : IntegerLength.values()) {
if(num < v.getValue()){
return v.getLenght();
}
}
return 0;
}
}
The run time of this solution is the same as the divide-and-conquer approach.

What about this recursive method?
private static int length = 0;
public static int length(int n) {
length++;
if((n / 10) < 10) {
length++;
} else {
length(n / 10);
}
return length;
}

simple solution:
public class long_length {
long x,l=1,n;
for (n=10;n<x;n*=10){
if (x/n!=0){
l++;
}
}
System.out.print(l);
}

A really simple solution:
public int numLength(int n) {
for (int length = 1; n % Math.pow(10, length) != n; length++) {}
return length;
}

Or instead the length you can check if the number is larger or smaller then the desired number.
public void createCard(int cardNumber, int cardStatus, int customerId) throws SQLException {
if(cardDao.checkIfCardExists(cardNumber) == false) {
if(cardDao.createCard(cardNumber, cardStatus, customerId) == true) {
System.out.println("Card created successfully");
} else {
}
} else {
System.out.println("Card already exists, try with another Card Number");
do {
System.out.println("Enter your new Card Number: ");
scan = new Scanner(System.in);
int inputCardNumber = scan.nextInt();
cardNumber = inputCardNumber;
} while(cardNumber < 95000000);
cardDao.createCard(cardNumber, cardStatus, customerId);
}
}
}

I haven't seen a multiplication-based solution yet. Logarithm, divison, and string-based solutions will become rather unwieldy against millions of test cases, so here's one for ints:
/**
* Returns the number of digits needed to represents an {#code int} value in
* the given radix, disregarding any sign.
*/
public static int len(int n, int radix) {
radixCheck(radix);
// if you want to establish some limitation other than radix > 2
n = Math.abs(n);
int len = 1;
long min = radix - 1;
while (n > min) {
n -= min;
min *= radix;
len++;
}
return len;
}
In base 10, this works because n is essentially being compared to 9, 99, 999... as min is 9, 90, 900... and n is being subtracted by 9, 90, 900...
Unfortunately, this is not portable to long just by replacing every instance of int due to overflow. On the other hand, it just so happens it will work for bases 2 and 10 (but badly fails for most of the other bases). You'll need a lookup table for the overflow points (or a division test... ew)
/**
* For radices 2 &le r &le Character.MAX_VALUE (36)
*/
private static long[] overflowpt = {-1, -1, 4611686018427387904L,
8105110306037952534L, 3458764513820540928L, 5960464477539062500L,
3948651115268014080L, 3351275184499704042L, 8070450532247928832L,
1200757082375992968L, 9000000000000000000L, 5054470284992937710L,
2033726847845400576L, 7984999310198158092L, 2022385242251558912L,
6130514465332031250L, 1080863910568919040L, 2694045224950414864L,
6371827248895377408L, 756953702320627062L, 1556480000000000000L,
3089447554782389220L, 5939011215544737792L, 482121737504447062L,
839967991029301248L, 1430511474609375000L, 2385723916542054400L,
3902460517721977146L, 6269893157408735232L, 341614273439763212L,
513726300000000000L, 762254306892144930L, 1116892707587883008L,
1617347408439258144L, 2316231840055068672L, 3282671350683593750L,
4606759634479349760L};
public static int len(long n, int radix) {
radixCheck(radix);
n = abs(n);
int len = 1;
long min = radix - 1;
while (n > min) {
len++;
if (min == overflowpt[radix]) break;
n -= min;
min *= radix;
}
return len;
}

One wants to do this mostly because he/she wants to "present" it, which mostly mean it finally needs to be "toString-ed" (or transformed in another way) explicitly or implicitly anyway; before it can be presented (printed for example). If that is the case then just try to make the necessary "toString" explicit and count the bits.

We can achieve this using a recursive loop
public static int digitCount(int numberInput, int i) {
while (numberInput > 0) {
i++;
numberInput = numberInput / 10;
digitCount(numberInput, i);
}
return i;
}
public static void printString() {
int numberInput = 1234567;
int digitCount = digitCount(numberInput, 0);
System.out.println("Count of digit in ["+numberInput+"] is ["+digitCount+"]");
}

I wrote this function after looking Integer.java source code.
private static int stringSize(int x) {
final int[] sizeTable = {9, 99, 999, 9_999, 99_999, 999_999, 9_999_999,
99_999_999, 999_999_999, Integer.MAX_VALUE};
for (int i = 0; ; ++i) {
if (x <= sizeTable[i]) {
return i + 1;
}
}
}

One of the efficient ways to count the number of digits in an int variable would be to define a method digitsCounter with a required number of conditional statements.
The approach is simple, we will be checking for each range in which a n digit number can lie:
0 : 9 are Single digit numbers
10 : 99 are Double digit numbers
100 : 999 are Triple digit numbers and so on...
static int digitsCounter(int N)
{ // N = Math.abs(N); // if `N` is -ve
if (0 <= N && N <= 9) return 1;
if (10 <= N && N <= 99) return 2;
if (100 <= N && N <= 999) return 3;
if (1000 <= N && N <= 9999) return 4;
if (10000 <= N && N <= 99999) return 5;
if (100000 <= N && N <= 999999) return 6;
if (1000000 <= N && N <= 9999999) return 7;
if (10000000 <= N && N <= 99999999) return 8;
if (100000000 <= N && N <= 999999999) return 9;
return 10;
}
A cleaner way to do this is to remove the check for the lower limits as it won't be required if we proceed in a sequential manner.
static int digitsCounter(int N)
{
N = N < 0 ? -N : N;
if (N <= 9) return 1;
if (N <= 99) return 2;
if (N <= 999) return 3;
if (N <= 9999) return 4;
if (N <= 99999) return 5;
if (N <= 999999) return 6;
if (N <= 9999999) return 7;
if (N <= 99999999) return 8;
if (N <= 999999999) return 9;
return 10; // Max possible digits in an 'int'
}

Ideally, an integer divided by 10 multiple times will return the number of digits as long as the integer is not zero. As such a simple method to do so can be created as below.
public static int getNumberOfDigits(int number) {
int numberOfDigits = 0;
while(number != 0) {
number /= 10;
numberOfDigits++;
}
return numberOfDigits;
}

It depends on what you mean by "neat". I think the following code is fairly neat, and it runs fast.
It is based on Marian's answer, extended to work with all long values and rendered using the ? : operator.
private static long[] DIGITS = { 1l,
10l,
100l,
1000l,
10000l,
100000l,
1000000l,
10000000l,
100000000l,
1000000000l,
10000000000l,
100000000000l,
1000000000000l,
10000000000000l,
100000000000000l,
1000000000000000l,
10000000000000000l,
100000000000000000l,
1000000000000000000l };
public static int numberOfDigits(final long n)
{
return n == Long.MIN_VALUE ? 19 : n < 0l ? numberOfDigits(-n) :
n < DIGITS[8] ? // 1-8
n < DIGITS[4] ? // 1-4
n < DIGITS[2] ? // 1-2
n < DIGITS[1] ? 1 : 2 : // 1-2
n < DIGITS[3] ? 3 : 4 : // 3-4
n < DIGITS[6] ? // 5-8
n < DIGITS[5] ? 5 : 6 : // 5-6
n < DIGITS[7] ? 7 : 8 : // 7-8
n < DIGITS[16] ? // 9-16
n < DIGITS[12] ? // 9-12
n < DIGITS[10] ? // 9-10
n < DIGITS[9] ? 9 : 10 : // 9-10
n < DIGITS[11] ? 11 : 12 : // 11-12
n < DIGITS[14] ? // 13-16
n < DIGITS[13] ? 13 : 14 : // 13-14
n < DIGITS[15] ? 15 : 16 : // 15-16
n < DIGITS[17] ? 17 : // 17-19
n < DIGITS[18] ? 18 :
19;
}

Here is what such solution looks from the JDK developers. This is JDK 17 (class Long):
/**
* Returns the string representation size for a given long value.
*
* #param x long value
* #return string size
*
* #implNote There are other ways to compute this: e.g. binary search,
* but values are biased heavily towards zero, and therefore linear search
* wins. The iteration results are also routinely inlined in the generated
* code after loop unrolling.
*/
static int stringSize(long x) {
int d = 1;
if (x >= 0) {
d = 0;
x = -x;
}
long p = -10;
for (int i = 1; i < 19; i++) {
if (x > p)
return i + d;
p = 10 * p;
}
return 19 + d;
}
Note that the method takes into account a minus sign, if necessary.
Unfortunately the method is not exposed.
In terms of performance you can see from the comments that the JDK developer has at least given this some thought compared to alternatives. I would guess that
a divide-and-conquer method skewed toward lower numbers would perform slightly
better, because the CPU can do integer comparisons a bit faster than integer
multiplications. But the difference may so small that it is not measurable.
In any case, I wish this method had been exposed in the JDK so that people would not start rolling their own method.

Here's a really simple method I made that works for any number:
public static int numberLength(int userNumber) {
int numberCounter = 10;
boolean condition = true;
int digitLength = 1;
while (condition) {
int numberRatio = userNumber / numberCounter;
if (numberRatio < 1) {
condition = false;
} else {
digitLength++;
numberCounter *= 10;
}
}
return digitLength;
}
The way it works is with the number counter variable is that 10 = 1 digit space. For example .1 = 1 tenth => 1 digit space. Therefore if you have int number = 103342; you'll get 6, because that's the equivalent of .000001 spaces back. Also, does anyone have a better variable name for numberCounter? I can't think of anything better.
Edit: Just thought of a better explanation. Essentially what this while loop is doing is making it so you divide your number by 10, until it's less than one. Essentially, when you divide something by 10 you're moving it back one number space, so you simply divide it by 10 until you reach <1 for the amount of digits in your number.
Here's another version that can count the amount of numbers in a decimal:
public static int repeatingLength(double decimalNumber) {
int numberCounter = 1;
boolean condition = true;
int digitLength = 1;
while (condition) {
double numberRatio = decimalNumber * numberCounter;
if ((numberRatio - Math.round(numberRatio)) < 0.0000001) {
condition = false;
} else {
digitLength++;
numberCounter *= 10;
}
}
return digitLength - 1;
}