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Question about adding three digits with each other in java [closed]

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I have a task to add each numbers. One of my colleague helped me out and here's the code.
public class Solution {
public static void main(String[] args) {
System.out.println(sumDigitsInNumber(546));
}
public static int sumDigitsInNumber(int number) {
int sum = 0;
sum = sum + number%10;
number = number/10;
sum = sum + number%10;
number = number/10;
sum = sum + number%10;
number = number/10;
return sum;//write your code here
}
I'm not sure exactly how this works. Can someone please explain to me? Thanks.

You can use within while the loop which will accept any number as #GBlodgett suggested
public static void main(String[] args) {
System.out.println(sumDigitsInNumber(546));
}
public static int sumDigitsInNumber(int number) {
int sum = 0;
while(number!=0)
{
sum = sum + number%10;
number = number/10;
}
return sum;//write your code here
}

In Java % is the modulo operator. It delivers the remainder of that division. If you divide integer values in Java, any remainder will be lost.
If you add some makeshift logging like that:
public static int sumDigitsInNumber(int number) {
int sum = 0;
sum = sum + number % 10;
number = number / 10;
System.out.println(number);
sum = sum + number % 10;
number = number / 10;
System.out.println(number);
sum = sum + number % 10;
number = number / 10;
System.out.println(number);
return sum; // write your code here
you will get the following output:
54
5
0
15
546 % 10 = 6
546 / 10 = 54
54 % 10 = 4
54 / 10 = 5
5 % 10 = 5
5 / 10 = 0
sum = 6 + 5 + 4 = 15
Your code will only work up to three digits. If you transfer the sequence of modulo and division operations into a loop it will be a generic solution.

The JVM(Java Virtual Machine) starts executing your code and public static void
main(String[] args) is the starting point.
Then executes System.out.println(sumDigitsInNumber(546));
System.out.println() is a method that prints the argument passed, into the System.out which is generally stdout (Standard output). The argument passed is the sumDigitsInNumber(546) method, hence it would print what sumDigitsInNumber() would return.
sumDigitsInNumber() initializes a sum variable with 0 to store the sum of 546.
sum = sum + number%10 gives you 6 (0 + 6), where number%10 gives
the last digit of 546 which is 6
number = number / 10 will replace number by 54 because 546/10 is 54.6 since it is an integer division .6 is ignored and 54 is stored in the number.
Repeat the above step twice but the number being 54 and then 5.
return sum returns the sum to the caller which is your main() method, hence System.out.println() printing the sum of 546.

Step by step:
this creates variable named sum and assigns it value of 0:
int sum = 0;
this does the following:
it assigns to variable 'sum' the result of sum + number % 10 (where a number is an argument passed to the method)
sum = sum + number%10;
number % 10 is in your example a remainder of 456 / 10, so in 456, you can pack number 10 exactly 45 times, whatever is left that is less then 10 is your result (remainder), in this case 6.
see http://www.cafeaulait.org/course/week2/15.html
next we divide current number by 10:
number = number / 10;
so 456 / 10 = 45.6
and as the type of variable is int - it is actually 45 (as int always rounds down the remainder) - see Int division: Why is the result of 1/3 == 0?
then it is being repeated 2 times until all 3 digits are summed up.
Notice, that your method will only work for 3 digit numbers. That's not that good.
You can easily make your method to work with any digits length int number passed.
Hint: use loops!
As you can see, you're repeating the same piece of code 3 times.
You could place it inside a loop and make it execute as many times as there are digits in your number.
something along these lines, but you need to figure out when to stop the while loop!
int sum = 0;
while (?WHEN TO EXIT?) {
sum = sum + number % 10;
number = number / 10;
}
Think about when you can exit loop (when, in example, maybe this number variable that you divide by 10 each iteration can tell you that all digits have been processed?)

Here is a solution that computes the sum of a number, no matter how many digits it has:
Generally speaking, a number has exactly [log(number)+1] digits, the tempInt variable is introduced to store the parameter value, it is considered a bad practice to modify the values of the method parameters :
public static int sumOfDigits(int number) {
int sum = 0;
int length = (int) Math.ceil(Math.log10(number));
int tempInt = number;
for (int i = 0; i < length; i++) {
sum += tempInt % 10;
tempInt /= 10;
}
return sum;
}

public class Solution {
public static void main(String[] args) {
System.out.println(sumDigitsInNumber(546));
}
public static int sumDigitsInNumber(int number) {
int sum = 0;
sum = sum + number%10; // number%10 = the last digit of 546 (= 6), sum = 0 + 6
number = number/10; // number = number whithout the last digit (54)
sum = sum + number%10; // number%10 = the last digit of 54 (= 4), sum = 0 + 6 + 4
number = number/10; // number = number whithout the last digit (5)
sum = sum + number%10; // number%10= the last digit of 5 (= 5), sum = 0 + 6 + 4 + 5
number = number/10; // number = number whithout the last digit (useless)
return sum;//sum = 6 + 5 + 4 = 15
}

Starting from 1 how far can I count, when I can use any digit a maximum of N times

My problem is as follows; for number N, I need to find out what is the largest value I can count to, when each digit can be used N times.
For example if N = 5, the largest value is 12, since at that point the digit 1 has been used 5 times.
My original approach was to simply iterate through all numbers and keep a tally of how many times each digit has been used so far. This is obviously very inefficient when N is large, so am looking for advice on what would be a smarter (and more efficient) way to achieve this.
public class Counter {
private static Hashtable<Integer, Integer> numbers;
public static void main(String[] args){
Counter c = new Counter();
c.run(9);
}
public Counter() {
numbers = new Hashtable<Integer, Integer>();
numbers.put(0, 0);
numbers.put(1, 0);
numbers.put(2, 0);
numbers.put(3, 0);
numbers.put(4, 0);
numbers.put(5, 0);
numbers.put(6, 0);
numbers.put(7, 0);
numbers.put(8, 0);
numbers.put(9, 0);
}
public static void run(int maxRepeat) {
int keeper = 0;
for(int maxFound = 0; maxFound <= maxRepeat; maxFound++) {
keeper++;
for (int i = 0; i < Integer.toString(keeper).length(); i++) {
int a = Integer.toString(keeper).charAt(i);
//here update the tally for appropriate digit and check if max repeats is reached
}
}
System.out.println(keeper);
}
}

For starters, rather than backing your Counter with a Hashtable, use an int[] instead. When you know exactly how many elements your map has to have, and especially when the keys are numbers, an array is perfect.
That being said, I think the most effective speedup is likely to come from better math, not better algorithms. With some experimentation (or it may be obvious), you'll notice that 1 is always the first digit to be used a given number of times. So given N, if you can find which number is the first to use the digit 1 N+1 times, you know your answer is the number right before that. This would let you solve the problem without actually having to count that high.
Now, let's look at how many 1's are used counting up to various numbers. Throughout this post I will use n to designate a number when we are trying to figure out how many 1's are used to count up to a number, whereas capital N designates how many 1's are used to count up to something.
One digit numbers
Starting with the single-digit numbers:
1: 1
2: 1
...
9: 1
Clearly the number of 1's required to count up to a one-digit number is... 1. Well, actually we forgot one:
0: 0
That will be important later. So we should say this: the number of 1's required to count up to a one-digit number X is X > 0 ? 1 : 0. Let's define a mathematical function f(n) that will represent "number of 1's required to count up to n". Then
f(X) = X > 0 ? 1 : 0
Two-digit numbers
For two-digit numbers, there are two types. For numbers of the form 1X,
10: 2
11: 4
12: 5
...
19: 12
You can think of it like this: counting up to 1X requires a number of 1's equal to
f(9) (from counting up to 9) plus
1 (from 10) plus
X (from the first digits of 11-1X inclusive, if X > 0) plus
however many 1's were required to count up to X
Or mathematically,
f(1X) = f(9) + 1 + X + f(X)
Then there are the two-digit numbers higher than 19:
21: 13
31: 14
...
91: 20
The number of 1's required to count to a two-digit number YX with Y > 1 is
f(19) (from counting up to 19) plus
f(9) * (Y - 2) (from the 1's in numbers 20 through (Y-1)9 inclusive - like if Y = 5, I mean the 1's in 20-49, which come from 21, 31, 41) plus
however many 1's were required to count up to X
Or mathematically, for Y > 1,
f(YX) = f(19) + f(9) * (Y - 2) + f(X)
= f(9) + 1 + 9 + f(9) + f(9) * (Y - 2) + f(X)
= 10 + f(9) * Y + f(X)
Three-digit numbers
Once you get into three-digit numbers, you can kind of extend the pattern. For any three-digit number of the form 1YX (and now Y can be anything), the total count of 1's from counting up to that number will be
f(99) (from counting up to 99) plus
1 (from 100) plus
10 * Y + X (from the first digits of 101-1YX inclusive) plus
however many 1's were required to count up to YX in two-digit numbers
so
f(1YX) = f(99) + 1 + YX + f(YX)
Note the parallel to f(1X). Continuing the logic to more digits, the pattern, for numbers which start with 1, is
f(1[m-digits]) = f(10^m - 1) + 1 + [m-digits] + f([m-digits])
with [m-digits] representing a sequence of digits of length m.
Now, for three-digit numbers ZYX that don't start with 1, i.e. Z > 1, the number of 1's required to count up to them is
f(199) (from counting up to 199) plus
f(99) * (Z - 2) (from the 1's in 200-(Z-1)99 inclusive) plus
however many 1's were required to count up to YX
so
f(ZYX) = f(199) + f(99) * (Z - 2) + f(YX)
= f(99) + 1 + 99 + f(99) + f(99) * (Z - 2) + f(YX)
= 100 + f(99) * Z + f(YX)
And the pattern for numbers that don't start with 1 now seems to be clear:
f(Z[m-digits]) = 10^m + f(10^m - 1) * Z + f([m-digits])
General case
We can combine the last result with the formula for numbers that do start with 1. You should be able to verify that the following formula is equivalent to the appropriate case given above for all digits Z 1-9, and that it does the right thing when Z == 0:
f(Z[m-digits]) = f(10^m - 1) * Z + f([m-digits])
+ (Z > 1) ? 10^m : Z * ([m-digits] + 1)
And for numbers of the form 10^m - 1, like 99, 999, etc. you can directly evaluate the function:
f(10^m - 1) = m * 10^(m-1)
because the digit 1 is going to be used 10^(m-1) times in each of the m digits - for example, when counting up to 999, there will be 100 1's used in the hundreds' place, 100 1's used in the tens' place, and 100 1's used in the ones' place. So this becomes
f(Z[m-digits]) = Z * m * 10^(m-1) + f([m-digits])
+ (Z > 1) ? 10^m : Z * ([m-digits] + 1)
You can tinker with the exact expression, but I think this is pretty close to as good as it gets, for this particular approach anyway. What you have here is a recursion relation that allows you to evaluate f(n), the number of 1's required to count up to n, by stripping off a leading digit at each step. Its time complexity is logarithmic in n.
Implementation
Implementing this function is straightforward given the last formula above. You can technically get away with one base case in the recursion: the empty string, i.e. define f("") to be 0. But it will save you a few calls to also handle single digits as well as numbers of the form 10^m - 1. Here's how I'd do it, omitting a bit of argument validation:
private static Pattern nines = Pattern.compile("9+");
/** Return 10^m for m=0,1,...,18 */
private long pow10(int m) {
// implement with either pow(10, m) or a switch statement
}
public long f(String n) {
int Z = Integer.parseInt(n.substring(0, 1));
int nlen = n.length();
if (nlen == 1) {
return Z > 0 ? 1 : 0;
}
if (nines.matcher(n).matches()) {
return nlen * pow10(nlen - 1);
}
String m_digits = n.substring(1);
int m = nlen - 1;
return Z * m * pow10(m - 1) + f_impl(m_digits)
+ (Z > 1 ? pow10(m) : Z * (Long.parseLong(m_digits) + 1));
}
Inverting
This algorithm solves the inverse of the the question you're asking: that is, it figures out how many times a digit is used counting up to n, whereas you want to know which n you can reach with a given number N of digits (i.e. 1's). So, as I mentioned back in the beginning, you're looking for the first n for which f(n+1) > N.
The most straightforward way to do this is to just start counting up from n = 0 and see when you exceed N.
public long howHigh(long N) {
long n = 0;
while (f(n+1) <= N) { n++; }
return n;
}
But of course that's no better (actually probably worse) than accumulating counts in an array. The whole point of having f is that you don't have to test every number; you can jump up by large intervals until you find an n such that f(n+1) > N, and then narrow down your search using the jumps. A reasonably simple method I'd recommend is exponential search to put an upper bound on the result, followed by a binary search to narrow it down:
public long howHigh(long N) {
long upper = 1;
while (f(upper + 1) <= N) {
upper *= 2;
}
long lower = upper / 2, mid = -1;
while (lower < upper) {
mid = (lower + upper) / 2;
if (f(mid + 1) > N) {
upper = mid;
}
else {
lower = mid + 1;
}
}
return lower;
}
Since the implementation of f from above is O(log(n)) and exponential+binary search is also O(log(n)), the final algorithm should be something like O(log^2(n)), and I think the relation between N and n is linear enough that you could consider it O(log^2(N)) too. If you search in log space and judiciously cache computed values of the function, it might be possible to bring it down to roughly O(log(N)). A variant that might provide a significant speedup is sticking in a round of interpolation search after determining the upper bound, but that's tricky to code properly. Fully optimizing the search algorithm is probably a matter for another question though.

This should be more efficient. Use integer array of size 10 to keep the count of digits.
public static int getMaxNumber(int N) {
int[] counts = new int[10];
int number = 0;
boolean limitReached = false;
while (!limitReached) {
number++;
char[] digits = Integer.toString(number).toCharArray();
for (char digit : digits) {
int count = counts[digit - '0'];
count++;
counts[digit - '0'] = count;
if (count >= N) {
limitReached = true;
}
}
}
return number;
}
UPDATE 1: As #Modus Tollens mentioned initial code has a bug. When N = 3 it returns 11, but there are four 1s between 1 and 11. The fix is to check if limit is breached count[i] > N on given number, previous number should be return. But if for some i count[i] == N for other j count[j] <= N, the actual number should be returned.
Please see corresponding code below:
public static int getMaxNumber(int N) {
int[] counts = new int[10];
int number = 0;
while (true) {
number++;
char[] digits = Integer.toString(number).toCharArray();
boolean limitReached = false;
for (char digit : digits) {
int count = counts[digit - '0'];
count++;
counts[digit - '0'] = count;
if (count == N) {
//we should break loop if some count[i] equals to N
limitReached = true;
} else if (count > N) {
//previous number should be returned immediately
//, if current number gives more unique digits than N
return number - 1;
}
}
if (limitReached) {
return number;
}
}
}
UPDATE 2: As #David Z and #Modus Tollens mentioned, in case if N=13, 30 should be returned, ie, algo stops when N is breached but not reached. If this is initial requirement, the code will be even simpler:
public static int getMaxNumber(int N) {
int[] counts = new int[10];
int number = 0;
while (true) {
number++;
char[] digits = Integer.toString(number).toCharArray();
for (char digit : digits) {
int count = counts[digit - '0'];
count++;
counts[digit - '0'] = count;
if (count > N) {
return number - 1;
}
}
}
}

Project Euler #3 - Solution runs forever

First time I've ever encountered this problem. It feels like it will never end.
My approach:
import java.util.TreeSet;
public class Euler3 {
public static void main(String[] args) {
long result = 0;
long startTime = System.nanoTime();
long numberGiven = 600851475143L;
TreeSet<Long> nums = new TreeSet<>();
for (long i = 2L; i < numberGiven; i++) {
if (numberGiven % i == 0 && isPrime(i)) {
nums.add(i);
}
}
result = nums.last();
System.out.print("Result: " + result +
".\nTime used for calculation in nanoseconds: " +
(System.nanoTime() - startTime) + ".");
}
public static boolean isPrime(long n) {
if (n <= 3) {
return n == 1 ? false : true;
} else if (n % 2 == 0 || n % 3 == 0) {
return false;
} else {
for (int i = 5; i * i <= n; i += 6) {
if (n % i == 0 || n % (i + 2) == 0) {
return false;
}
}
return true;
}
}
}
Of course this works on smaller numbers, but as is probably intended doesn't seem effective on over 600 billion.
I'm wondering, without giving the answer away:
Is there some obvious alteration I could employ to reduce the
running time/checks necessary?
Although it clearly doesn't work effectively here, is this approach
otherwise acceptable or would someone who posted this challenge,
even with a smaller number, be looking for something different?
I tried with integers the first time and got an overflow related error, is anything similar happening under the hood that would actually prevent this from terminating?

For every number you're checking that's a factor, you're doing an internal loop to figure out if it's a prime. That means your algorithm is effectively performing n * m operations.
You can instead use the following mathematical "trick", which I think is the same used by the UNIX factor program.
Since every number over one is either prime or a unique product of a set of primes (with potential duplicates in the set), we can just start dividing the number by the first prime two (actually reducing the number in the process) until that's no longer possible (i.e., it becomes odd). At that point, the reduced number will not have two or any multiples of two as a factor.
Then we do the same by continuously dividing by three until that's no longer possible.
Now you'd think that may be onerous but, because you've stripped out all the 'two' factors, the number cannot possibly be a multiple of four (or any other even number for that matter). So we detect that and move up to the next divisor of five and start dividing by that.
So the division operation are only done for prime divisors, speeding things up considerably. In addition, once the divisor gets above the square root of the (reduced) number, no more factors are possible, so we exit. In that case, the reduced number gives us the final (hence highest) prime factor.
For example, consider the number 924:
Number Divisor Result
------ ------- ------
924 2* 462
462 2* 231
231 2 not divisible, go to 3
231 3* 77
77 3 not divisible, go to 4
77 4 not divisible, go to 5
77 5 not divisible, go to 6
77 6 not divisible, go to 7
77 7* 11
11* 7 stop since 7 * 7 > 11
So the prime factors of 924 are {2, 2, 3, 7, 11}.
Now I urge you to try that algorithm on your own before looking below since the entire point of Euler is to test your own abilities. I simply provide the solution for completeness:
public class Test
{
public static void main(String[] args) {
long startTime = System.nanoTime();
long number = 600851475143L;
// Start with a divisor of two,
// continue until over sqrt(number).
long divisor = 2L;
while (divisor * divisor <= number) {
if ((number % divisor) == 0) {
// If factor, output then reduce number.
System.out.println(divisor);
number = number / divisor;
} else {
// Otherwise, move to next divisor.
divisor++;
}
}
// Final number is final divisor.
System.out.println(number);
System.out.print("Time used for calculation in nanoseconds: " +
(System.nanoTime() - startTime) + ".");
}
}
That gives you the four prime factors in about five thousandths of a second (on my box, anyway):
71
839
1471
6857
Time used for calculation in nanoseconds: 458826.

The program can be simple like this, which runs under a second:
long val = 600851475143L;
long ans = 0;
for(long i = 2; i*i <= val; i++){
if(val % i == 0){
ans = i;
while(val % i == 0)//This step will make sure that i is prime
val /= i;
}
}
if(val != 1){//If val is not 1, so val is a prime
ans = val > ans ? val : ans;
}
System.out.println(ans);
Answer is 6857, and it is correct answer :)
Notice that we only check for all i values which i*i smaller than val.

Prime Factorization Program in Java

I am working on a prime factorization program implemented in Java.
The goal is to find the largest prime factor of 600851475143 (Project Euler problem 3).
I think I have most of it done, but I am getting a few errors.
Also my logic seems to be off, in particular the method that I have set up for checking to see if a number is prime.
public class PrimeFactor {
public static void main(String[] args) {
int count = 0;
for (int i = 0; i < Math.sqrt(600851475143L); i++) {
if (Prime(i) && i % Math.sqrt(600851475143L) == 0) {
count = i;
System.out.println(count);
}
}
}
public static boolean Prime(int n) {
boolean isPrime = false;
// A number is prime iff it is divisible by 1 and itself only
if (n % n == 0 && n % 1 == 0) {
isPrime = true;
}
return isPrime;
}
}
Edit
public class PrimeFactor {
public static void main(String[] args) {
for (int i = 2; i <= 600851475143L; i++) {
if (isPrime(i) == true) {
System.out.println(i);
}
}
}
public static boolean isPrime(int number) {
if (number == 1) return false;
if (number == 2) return true;
if (number % 2 == 0) return false;
for (int i = 3; i <= number; i++) {
if (number % i == 0) return false;
}
return true;
}
}

Why make it so complicated? You don't need do anything like isPrime(). Divide it's least divisor(prime) and do the loop from this prime. Here is my simple code :
public class PrimeFactor {
public static int largestPrimeFactor(long number) {
int i;
for (i = 2; i <= number; i++) {
if (number % i == 0) {
number /= i;
i--;
}
}
return i;
}
/**
* #param args
*/
public static void main(String[] args) {
System.out.println(largestPrimeFactor(13195));
System.out.println(largestPrimeFactor(600851475143L));
}
}

edit: I hope this doesn't sound incredibly condescending as an answer. I just really wanted to illustrate that from the computer's point of view, you have to check all possible numbers that could be factors of X to make sure it's prime. Computers don't know that it's composite just by looking at it, so you have to iterate
Example: Is X a prime number?
For the case where X = 67:
How do you check this?
I divide it by 2... it has a remainder of 1 (this also tells us that 67 is an odd number)
I divide it by 3... it has a remainder of 1
I divide it by 4... it has a remainder of 3
I divide it by 5... it has a remainder of 2
I divide it by 6... it has a remainder of 1
In fact, you will only get a remainder of 0 if the number is not prime.
Do you have to check every single number less than X to make sure it's prime? Nope. Not anymore, thanks to math (!)
Let's look at a smaller number, like 16.
16 is not prime.
why? because
2*8 = 16
4*4 = 16
So 16 is divisible evenly by more than just 1 and itself. (Although "1" is technically not a prime number, but that's technicalities, and I digress)
So we divide 16 by 1... of course this works, this works for every number
Divide 16 by 2... we get a remainder of 0 (8*2)
Divide 16 by 3... we get a remainder of 1
Divide 16 by 4... we get a remainder of 0 (4*4)
Divide 16 by 5... we get a remainder of 1
Divide 16 by 6... we get a remainder of 4
Divide 16 by 7... we get a remainder of 2
Divide 16 by 8... we get a remainder of 0 (8*2)
We really only need one remainder of 0 to tell us it's composite (the opposite of "prime" is "composite").
Checking if 16 is divisible by 2 is the same thing as checking if it's divisible by 8, because 2 and 8 multiply to give you 16.
We only need to check a portion of the spectrum (from 2 up to the square-root of X) because the largest number that we can multiply is sqrt(X), otherwise we are using the smaller numbers to get redundant answers.
Is 17 prime?
17 % 2 = 1
17 % 3 = 2
17 % 4 = 1 <--| approximately the square root of 17 [4.123...]
17 % 5 = 2 <--|
17 % 6 = 5
17 % 7 = 3
The results after sqrt(X), like 17 % 7 and so on, are redundant because they must necessarily multiply with something smaller than the sqrt(X) to yield X.
That is,
A * B = X
if A and B are both greater than sqrt(X) then
A*B will yield a number that is greater than X.
Thus, one of either A or B must be smaller than sqrt(X), and it is redundant to check both of these values since you only need to know if one of them divides X evenly (the even division gives you the other value as an answer)
I hope that helps.
edit: There are more sophisticated methods of checking primality and Java has a built-in "this number is probably prime" or "this number is definitely composite" method in the BigInteger class as I recently learned via another SO answer :]

You need to do some research on algorithms for factorizing large numbers; this wikipedia page looks like a good place to start. In the first paragraph, it states:
When the numbers are very large, no efficient integer factorization algorithm is publicly known ...
but it does list a number of special and general purpose algorithms. You need to pick one that will work well enough to deal with 12 decimal digit numbers. These numbers are too large for the most naive approach to work, but small enough that (for example) an approach based on enumerating the prime numbers starting from 2 would work. (Hint - start with the Sieve of Erasthones)

Here is very elegant answer - which uses brute force (not some fancy algorithm) but in a smart way - by lowering the limit as we find primes and devide composite by those primes...
It also prints only the primes - and just the primes, and if one prime is more then once in the product - it will print it as many times as that prime is in the product.
public class Factorization {
public static void main(String[] args) {
long composite = 600851475143L;
int limit = (int)Math.sqrt(composite)+1;
for (int i=3; i<limit; i+=2)
{
if (composite%i==0)
{
System.out.println(i);
composite = composite/i;
limit = (int)Math.sqrt(composite)+1;
i-=2; //this is so it could check same prime again
}
}
System.out.println(composite);
}
}

You want to iterate from 2 -> n-1 and make sure that n % i != 0. That's the most naive way to check for primality. As explained above, this is very very slow if the number is large.

To find factors, you want something like:
long limit = sqrt(number);
for (long i=3; i<limit; i+=2)
if (number % i == 0)
print "factor = " , i;
In this case, the factors are all small enough (<7000) that finding them should take well under a second, even with naive code like this. Also note that this particular number has other, smaller, prime factors. For a brute force search like this, you can save a little work by dividing out the smaller factors as you find them, and then do a prime factorization of the smaller number that results. This has the advantage of only giving prime factors. Otherwise, you'll also get composite factors (e.g., this number has four prime factors, so the first method will print out not only the prime factors, but the products of various combinations of those prime factors).
If you want to optimize that a bit, you can use the sieve of Eratosthenes to find the prime numbers up to the square root, and then only attempt division by primes. In this case, the square root is ~775'000, and you only need one bit per number to signify whether it's prime. You also (normally) only want to store odd numbers (since you know immediately that all even numbers but two are composite), so you need ~775'000/2 bits = ~47 Kilobytes.
In this case, that has little real payoff though -- even a completely naive algorithm will appear to produce results instantly.

I think you're confused because there is no iff [if-and-only-if] operator.
Going to the square root of the integer in question is a good shortcut. All that remains is checking if the number within that loop divides evenly. That's simply [big number] % i == 0. There is no reason for your Prime function.
Since you are looking for the largest divisor, another trick would be to start from the highest integer less than the square root and go i--.
Like others have said, ultimately, this is brutally slow.

private static boolean isPrime(int k) throws IllegalArgumentException
{
int j;
if (k < 2) throw new IllegalArgumentException("All prime numbers are greater than 1.");
else {
for (j = 2; j < k; j++) {
if (k % j == 0) return false;
}
}
return true;
}
public static void primeFactorsOf(int n) {
boolean found = false;
if (isPrime(n) == true) System.out.print(n + " ");
else {
int i = 2;
while (found == false) {
if ((n % i == 0) && (isPrime(i))) {
System.out.print(i + ", ");
found = true;
} else i++;
}
primeFactorsOf(n / i);
}
}

For those answers which use a method isPrime(int) : boolean, there is a faster algorithm than the one previously implemented (which is something like)
private static boolean isPrime(long n) { //when n >= 2
for (int k = 2; k < n; k++)
if (n % k == 0) return false;
return true;
}
and it is this:
private static boolean isPrime(long n) { //when n >= 2
if (n == 2 || n == 3) return true;
if (n % 2 == 0 || n % 3 == 0) return false;
for (int k = 1; k <= (Math.floor(Math.sqrt(n)) + 1) / 6; k++)
if (n % (6 * k + 1) == 0 || n % (6 * k - 1) == 0) return false;
return true;
}
I made this algorithm using two facts:
We only need to check for n % k == 0 up to k <= Math.sqrt(n). This is true because for anything higher, factors merely "flip" ex. consider the case n = 15, where 3 * 5 = 5 * 3, and 5 > Math.sqrt(15). There is no need for this overlap of checking both 15 % 3 == 0 and 15 % 5 == 0, when we could just check one of these expressions.
All primes (excluding 2 and 3) can be expressed in the form (6 * k) + 1 or (6 * k) - 1, because any positive integer can be expressed in the form (6 * k) + n, where n = -1, 0, 1, 2, 3, or 4 and k is an integer <= 0, and the cases where n = 0, 2, 3, and 4 are all reducible.
Therefore, n is prime if it is not divisible by 2, 3, or some integer of the form 6k ± 1 <= Math.sqrt(n). Hence the above algorithm.
--
Wikipedia article on testing for primality
--
Edit: Thought I might as well post my full solution (*I did not use isPrime(), and my solution is nearly identical to the top answer, but I thought I should answer the actual question):
public class Euler3 {
public static void main(String[] args) {
long[] nums = {13195, 600851475143L};
for (num : nums)
System.out.println("Largest prime factor of " + num + ": " + lpf(num));
}
private static lpf(long n) {
long largestPrimeFactor = 1;
long maxPossibleFactor = n / 2;
for (long i = 2; i <= maxPossibleFactor; i++)
if (n % i == 0) {
n /= i;
largestPrimeFactor = i;
i--;
}
return largestPrimeFactor;
}
}

To find all prime factorization
import java.math.BigInteger;
import java.util.Scanner;
public class BigIntegerTest {
public static void main(String[] args) {
BigInteger myBigInteger = new BigInteger("65328734260653234260");//653234254
BigInteger originalBigInteger;
BigInteger oneAddedOriginalBigInteger;
originalBigInteger=myBigInteger;
oneAddedOriginalBigInteger=originalBigInteger.add(BigInteger.ONE);
BigInteger index;
BigInteger countBig;
for (index=new BigInteger("2"); index.compareTo(myBigInteger.add(BigInteger.ONE)) <0; index = index.add(BigInteger.ONE)){
countBig=BigInteger.ZERO;
while(myBigInteger.remainder(index) == BigInteger.ZERO ){
myBigInteger=myBigInteger.divide(index);
countBig=countBig.add(BigInteger.ONE);
}
if(countBig.equals(BigInteger.ZERO)) continue;
System.out.println(index+ "**" + countBig);
}
System.out.println("Program is ended!");
}
}

I got a very similar problem for my programming class. In my class it had to calculate for an inputted number. I used a solution very similar to Stijak. I edited my code to do the number from this problem instead of using an input.
Some differences from Stijak's code are these:
I considered even numbers in my code.
My code only prints the largest prime factor, not all factors.
I don't recalculate the factorLimit until I have divided all instances of the current factor off.
I had all the variables declared as long because I wanted the flexibility of using it for very large values of number. I found the worst case scenario was a very large prime number like 9223372036854775783, or a very large number with a prime number square root like 9223371994482243049. The more factors a number has the faster the algorithm runs. Therefore, the best case scenario would be numbers like 4611686018427387904 (2^62) or 6917529027641081856 (3*2^61) because both have 62 factors.
public class LargestPrimeFactor
{
public static void main (String[] args){
long number=600851475143L, factoredNumber=number, factor, factorLimit, maxPrimeFactor;
while(factoredNumber%2==0)
factoredNumber/=2;
factorLimit=(long)Math.sqrt(factoredNumber);
for(factor=3;factor<=factorLimit;factor+=2){
if(factoredNumber%factor==0){
do factoredNumber/=factor;
while(factoredNumber%factor==0);
factorLimit=(long)Math.sqrt(factoredNumber);
}
}
if(factoredNumber==1)
if(factor==3)
maxPrimeFactor=2;
else
maxPrimeFactor=factor-2;
else
maxPrimeFactor=factoredNumber;
if(maxPrimeFactor==number)
System.out.println("Number is prime.");
else
System.out.println("The largest prime factor is "+maxPrimeFactor);
}
}

public class Prime
{
int i;
public Prime( )
{
i = 2;
}
public boolean isPrime( int test )
{
int k;
if( test < 2 )
return false;
else if( test == 2 )
return true;
else if( ( test > 2 ) && ( test % 2 == 0 ) )
return false;
else
{
for( k = 3; k < ( test/2 ); k += 2 )
{
if( test % k == 0 )
return false;
}
}
return true;
}
public void primeFactors( int factorize )
{
if( isPrime( factorize ) )
{
System.out.println( factorize );
i = 2;
}
else
{
if( isPrime( i ) && ( factorize % i == 0 ) )
{
System.out.print( i+", " );
primeFactors( factorize / i );
}
else
{
i++;
primeFactors( factorize );
}
}
public static void main( String[ ] args )
{
Prime p = new Prime( );
p.primeFactors( 649 );
p.primeFactors( 144 );
p.primeFactors( 1001 );
}
}

Tips to solve problem #41 of project euler

I'm trying to solve Problem 41of project Euler in Java, by counting the number from 99888888 to 80000000(which took very long time :( ), I got 98765431 as an answer, but I'm getting that answer not correct. Could anyone please tell me the reason of not getting the correct answer and how can I speed my program?

A pandigital number doesn't needs to contain all numbers from 1 to 9, but all from 1 to length.
So, you'll need to try all permutations from 1 to 9 starting with 1 digit and going up, filtering all prime numbers and, then, taking largest one.

The only possible prime pandigital numbers are those with length 1, 4, & 7 because every other pandigital number has the sum of its digits divisible by 3.
So, you'd only need to test for 7! = 5040 permutations.

To obtain a solution in a "reasonable" time, you need the following observations based on the special property that a number is divisible by 3 if the sum of its digits is divisible by 3:
divisible by
1+2+3+4 = 10 -
1+2+3+4+5 = 15 3
1+2+3+4+5+6 = 21 3
1+2+3+4+5+6+7 = 28 -
1+2+3+4+5+6+7+8 = 36 3
1+2+3+4+5+6+7+8+9 = 45 3
So, a "big" prime pandigital number has 4 or 7 digits. (a prime number bigger than 3 is not divisible by 3)
Because you want to obtain the biggest number, it's better to start with the 7-digit numbers and continue to check the 4-digit numbers only if the number was not found. For sure, a 4-digit number exists, because it is specified: 2143.
Now, a possible solution looks like this:
public class P41 {
public static void main(String[] args) {
boolean wasFound = false;
for (int nr = 7654321; nr >= 1234567; nr -= 2) { // even != prime
if (isPandigital(nr) && isOddPrime(nr)) {
System.out.println(nr);
wasFound = true;
break;
}
}
if (!wasFound) {
/* not <=, because 1234 is even */
for (int nr = 4321; nr > 1234; nr -= 2) {
if (isPandigital(nr) && isOddPrime(nr)) {
System.out.println(nr);
break;
}
}
}
}
private static boolean isOddPrime(int x) {
int sqrt = (int) Math.sqrt(x);
for (int i = 3; i <= sqrt; i += 2) {
if (x % i == 0) {
return false;
}
}
return true;
}
private static int getNumberOfDigits(int x) {
int count = 0;
while (x > 0) {
count++;
x /= 10;
}
return count;
}
private static boolean isPandigital(int x) {
int numberOfDigits = getNumberOfDigits(x);
Set<Integer> digits = new HashSet<Integer>();
for (int i = 1; i <= numberOfDigits; i++) {
digits.add(i);
}
for (int i = 1; i <= numberOfDigits; i++) {
digits.remove(x % 10);
x /= 10;
}
if (digits.size() == 0) {
return true;
} else {
return false;
}
}
}
Time: 8 ms.

Here is the problem statement:
We shall say that an n-digit number is pandigital if it makes use of all the digits 1 to n exactly once. For example, 2143 is a 4-digit pandigital and is also prime. What is the largest n-digit pandigital prime that exists?
I wrote a program that started with 987654321 and counted down. I checked that the number was pandigital, and if it was, checked if it was prime.
It took 66 seconds on my Windows 8.1 computer to find the largest prime pandigital.
When I tested the other way around, first prime, then pandigital, the program took way longer than 66 seconds. I cancelled it.
When I applied GregS' tip about discounting all 9 digit and 8 digit pandigital numbers, and started counting down from 7654321, my brute force algorithm took 13 milliseconds.