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How to write a java program that computes the value of e^x

I'm trying to figure out how to answer this question for my Java class, using only while loops:
Write an application that computes the value of mathematical constant e^x by using the following formula. Allow the user to enter the number of terms to calculate. e^x = 1 + (x/1!) + (x^2/2!) + (x^3/3!) + ...
I can't figure out how I would do this without also asking the user for a value for x? Below is the code that I created for calculating x with the number of terms and just the number 1 for the exponent of each fraction. Any help is appreciated
import java.util.Scanner;
public class FactorialB {
public static void main(String[] args) {
Scanner scanner = new Scanner(System.in);
int counter = 0;
float answer = 0;
System.out.print("Enter number of terms: ");
int n = scanner.nextInt();
while (counter < n) {
double factorial = 1;
int factCounter = counter;
while (factCounter > 1) {
factorial = factCounter * factorial;
factCounter--;
}
answer += 1 / factorial;
counter++;
}
System.out.printf("e = %f%n", answer);
}
}

Firstly the question you seem to be asking:
There is no way to make a program that will give e for a specific number unless you ask the user for that number.
However it might be that they just want you to make a method that provides the solution (if it were called) independently of user input. (because the code to get user input isn't very interesting, what is interesting is how you reach the result).
An alternative way to provide x and n are for instance passing them as commandline arguments. (args[] in your main would be a way to provide them)
I would create a separate method that receives x and n that covers the main calculation:
e^x = 1 + (x/1!) + (x^2/2!) + (x^3/3!) + ...
And separate methods that cover 'calculating a single term (x^1/1!), (x^2/2!), etc' and 'factorialize(n)'
public void calculatePartialE_term(int x, int n) {
if (n == 0) {
return 1; // this will allow you to use a while loop, covers the n = 0 case
} else {
// removed the implementation, but basically do
// x^n/n! here for whatever value of n this term is calculating.
}
}
public int calcualteNFactorial(int n) {
// assert n >= 1
// use a while loop to calculate n factorial
}
the benefit of doing this in a separate methods is that you can prove / verify the working of calculatePartialE_term or calcualteNFactorial independently of one another.
now you can simply write a while loop based on x and n to do something like
public int calculateE_to_x(int x, int n) {
int current = 0;
int sum = 0;
while (current <= n) {
sum += calculatePartialE_term(x, current);
}
}
I wouldn't expect your teacher to expect you to show code that handles user input but even if that is the case it will be easier for them to verify your work if the actual work (of calculating) is done in a separate method.

Possible multiplications of k distinct factors with largest possible factor n

Let M(n,k) be the sum of all possible multiplications of k distinct factors with largest possible factor n, where order is irrelevant.
For example, M(5,3) = 225 , because:
1*2*3 = 6
1*2*4 = 8
1*2*5 = 10
1*3*4 = 12
1*3*5 = 15
1*4*5 = 20
2*3*4 = 24
2*3*5 = 30
2*4*5 = 40
3*4*5 = 60
6+8+10+12+15+20+24+30+40+60 = 225.
One can easily notice that there are C(n,k) such multiplications, corresponding to the number of ways one can pick k objects out of n possible objects. In the example above, C(5,3) = 10 and there really are 10 such multiplications, stated above.
The question can also be visualized as possible n-sized sets containing exactly k 0's, where each cell that does not contain 0 inside it, has the value of its index+1 inside it. For example, one possible such set is {0,2,3,0,5}. From here on, one needs to multiply the values in the set that are different than 0.
My approach is a recursive algorithm. Similiarly to the above definition of
M(n,k), I define M(n,j,k) to be the sum of all possible multiplications of exactly k distinct factors with largest possible factor n, AND SMALLEST possible factor j. Hence, my approach would yield the desired value if ran on
M(n,1,k). So I start my recursion on M(n,1,k), with the following code, written in Java:
public static long M (long n, long j, long k)
{
if (k==1)
return usefulFunctions.sum(j, n);
for (long i=j;i<=n-k+1+1;i++)
return i*M(n,i+1,k-1);
}
Explanation to the code:
Starting with, for example, n=5 , j=1, k=3, the algorithm will continue to run as long as we need more factors, (k>=1), and it is made sure to run only distinct factors thanks to the for loop, which increases the minimal possible value j as more factors are added. The loop runs and decreases the number of needed factors as they are 'added', which is achieved through applying
M(n,j+1,k-1). The j+1 assures that the factors will be distinct because the minimal value of the factor increases, and k-1 symbolizes that we need 1 less factor to add.
The function 'sum(j,n)' returns the value of the sum of all numbers starting from j untill n, so sum(1,10)=55. This is done with a proper, elegant and simple mathematical formula, with no loops: sum(j,n) = (n+1)*n/2 - (i-1)*i/2
public static long sum (long i, long n)
{
final long s1 = n * (n + 1) / 2;
final long s2 = i * (i - 1) / 2;
return s1 - s2 ;
}
The reason to apply this sum when k=1, I will explain with an example:
Say we have started with 1*2. Now we need a third factor, which can be either of 3,4,5. Because all multiplications: 1*2*3, 1*2*4, 1*2*5 are valid, we can return 1*2*(3+4+5) = 1*2*sum(3,5) = 24.
Similiar logic explains the coefficient "i" next to the M(n,j+1,k-1).
say we have now the sole factor 2. Hence we need 2 more factors, so we multiply 2 by the next itterations, which should result in:
2*(3*sum(4,5) + 4*sum(5,5))
However, for a reason I can't explain yet, the code doesn't work. It returns wrong values and also has "return" issues that cause the function not to return anything, don't know why.
This is the reason i'm posting this question here, in hope someone will aid me. Either by fixing this code or sharing a code of his own. Explaining where I'm going wrong will be most appreciable.
Thanks a lot in advance, and sorry for this very long question,
Matan.
-----------------------EDIT------------------------
Below is my fixed code, which solves this question. Posting it incase one should ever need it :) Have fun !
public static long M(long n, long j, long k)
{
if (k == 0)
return 0;
if (k == 1)
return sum(j,n);
else
{
long summation = 0;
for (long i=j; i<=n; i++)
summation += i*M(n, i+1, k-1);
return summation;
}
}

I see that u got ur answer and i really like ur algorithm but i cant control myself posting a better algorithm . here is the idea
M(n,k) = coefficient of x^k in (1+x)(1+2*x)(1+3*x)...(1+n*x)
u can solve above expression by divide and conquer algorithm Click Here to find how to multiply above expression and get polynomial function in the form of ax^n + bx^(n-1)....+c
overall algorithm time complexity is O(n * log^2 n)
and best part of above algorithm is
in the attempt of finding solution for M(n,k) , u will find solution for M(n,x) where 1<=x<=n
i hope it will be useful to know :)

I am not sure about your algorithm, but you certainly messed up with your sum function. The problem you have is connected to type casting and division of integer numbers. Try something like this:
public static long sum (long i, long n)
{
final long s1 = n * (n + 1) / 2;
final long s2 = (i * i - i) / 2;
return s1 - s2 ;
}

You have a problem with your sum function : here is the correct formula:
public static long sum (long i, long n)
{
double s1 = n*(n+1)/2;
double s2 = i*(i-1)/2;
return (long)(s1-s2);
}
Here the full solution :
static int n = 5;
static long k = 3;
// no need to add n and k them inside your M function cause they are fixed.
public static long M (long start) // start = 1
{
if(start > k) // if start is superior to k : like your example going from 1..3 , then you return 0
return 0;
int res = 0; // res of your function
for(long i=start+1;i<n;i++){
res+=start*i*sum(i+1,n); // here you take for example 1*2*sum(3,5) + 1*3*sum(4,5).... ect
}
return res+M(start+1); // return res and start again from start+1 wich would be 2.
}
public static long sum (long i, long n)
{
if(i>n)
return 0;
double s1 = n*(n+1)/2;
double s2 = i*(i-1)/2;
return (long)(s1-s2);
}
public static void main(String[] args) {
System.out.println(M(1));
}
Hope it helped

Checking whether a number is in Fibonacci Sequence?

It was asked to find a way to check whether a number is in the Fibonacci Sequence or not.
The constraints are
1≤T≤10^5
1≤N≤10^10
where the T is the number of test cases,
and N is the given number, the Fibonacci candidate to be tested.
I wrote it the following using the fact a number is Fibonacci if and only if one or both of (5*n2 + 4) or (5*n2 – 4) is a perfect square :-
import java.io.*;
import java.util.*;
public class Solution {
public static void main(String[] args) {
Scanner sc = new Scanner(System.in);
int n = sc.nextInt();
for(int i = 0 ; i < n; i++){
int cand = sc.nextInt();
if(cand < 0){System.out.println("IsNotFibo"); return; }
int aTest =(5 * (cand *cand)) + 4;
int bTest = (5 * (cand *cand)) - 4;
int sqrt1 = (int)Math.sqrt(aTest);// Taking square root of aTest, taking into account only the integer part.
int sqrt2 = (int)Math.sqrt(bTest);// Taking square root of bTest, taking into account only the integer part.
if((sqrt1 * sqrt1 == aTest)||(sqrt2 * sqrt2 == bTest)){
System.out.println("IsFibo");
}else{
System.out.println("IsNotFibo");
}
}
}
}
But its not clearing all the test cases? What bug fixes I can do ?

A much simpler solution is based on the fact that there are only 49 Fibonacci numbers below 10^10.
Precompute them and store them in an array or hash table for existency checks.
The runtime complexity will be O(log N + T):
Set<Long> nums = new HashSet<>();
long a = 1, b = 2;
while (a <= 10000000000L) {
nums.add(a);
long c = a + b;
a = b;
b = c;
}
// then for each query, use nums.contains() to check for Fibonacci-ness
If you want to go down the perfect square route, you might want to use arbitrary-precision arithmetics:
// find ceil(sqrt(n)) in O(log n) steps
BigInteger ceilSqrt(BigInteger n) {
// use binary search to find smallest x with x^2 >= n
BigInteger lo = BigInteger.valueOf(1),
hi = BigInteger.valueOf(n);
while (lo.compareTo(hi) < 0) {
BigInteger mid = lo.add(hi).divide(2);
if (mid.multiply(mid).compareTo(x) >= 0)
hi = mid;
else
lo = mid.add(BigInteger.ONE);
}
return lo;
}
// checks if n is a perfect square
boolean isPerfectSquare(BigInteger n) {
BigInteger x = ceilSqrt(n);
return x.multiply(x).equals(n);
}

Your tests for perfect squares involve floating point calculations. That is liable to give you incorrect answers because floating point calculations typically give you inaccurate results. (Floating point is at best an approximate to Real numbers.)
In this case sqrt(n*n) might give you n - epsilon for some small epsilon and (int) sqrt(n*n) would then be n - 1 instead of the expected n.
Restructure your code so that the tests are performed using integer arithmetic. But note that N < 1010 means that N2 < 1020. That is bigger than a long ... so you will need to use ...
UPDATE
There is more to it than this. First, Math.sqrt(double) is guaranteed to give you a double result that is rounded to the closest double value to the true square root. So you might think we are in the clear (as it were).
But the problem is that N multiplied by N has up to 20 significant digits ... which is more than can be represented when you widen the number to a double in order to make the sqrt call. (A double has 15.95 decimal digits of precision, according to Wikipedia.)
On top of that, the code as written does this:
int cand = sc.nextInt();
int aTest = (5 * (cand * cand)) + 4;
For large values of cand, that is liable to overflow. And it will even overflow if you use long instead of int ... given that the cand values may be up to 10^10. (A long can represent numbers up to +9,223,372,036,854,775,807 ... which is less than 1020.) And then we have to multiply N2 by 5.
In summary, while the code should work for small candidates, for really large ones it could either break when you attempt to read the candidate (as an int) or it could give the wrong answer due to integer overflow (as a long).
Fixing this requires a significant rethink. (Or deeper analysis than I have done to show that the computational hazards don't result in an incorrect answer for any large N in the range of possible inputs.)

According to this link a number is Fibonacci if and only if one or both of (5*n2 + 4) or (5*n2 – 4) is a perfect square so you can basically do this check.
Hope this helps :)

Use binary search and the Fibonacci Q-matrix for a O((log n)^2) solution per test case if you use exponentiation by squaring.
Your solution does not work because it involves rounding floating point square roots of large numbers (potentially large enough not to even fit in a long), which sometimes will not be exact.
The binary search will work like this: find Q^m: if the m-th Fibonacci number is larger than yours, set right = m, if it is equal return true, else set left = m + 1.

As it was correctly said, sqrt could be rounded down. So:
Even if you use long instead of int, it has 18 digits.
even if you use Math.round(), not simply (int) or (long). Notice, your function wouldn't work correctly even on small numbers because of that.
double have 14 digits, long has 18, so you can't work with squares, you need 20 digits.
BigInteger and BigDecimal have no sqrt() function.
So, you have three ways:
write your own sqrt for BigInteger.
check all numbers around the found unprecise double sqrt() for being a real sqrt. That means also working with numbers and their errors simultaneously. (it's horror!)
count all Fibonacci numbers under 10^10 and compare against them.
The last variant is by far the simplest one.

Looks like to me the for-loop doesn't make any sense ?
When you remove the for-loop for me the program works as advertised:
import java.io.*;
import java.util.*;
public class Solution {
public static void main(String[] args) {
Scanner sc = new Scanner(System.in);
int cand = sc.nextInt();
if(cand < 0){System.out.println("IsNotFibo"); return; }
int aTest = 5 * cand *cand + 4;
int bTest = 5 * cand *cand - 4;
int sqrt1 = (int)Math.sqrt(aTest);
int sqrt2 = (int)Math.sqrt(bTest);
if((sqrt1 * sqrt1 == aTest)||(sqrt2 * sqrt2 == bTest)){
System.out.println("IsFibo");
}else{
System.out.println("IsNotFibo");
}
}
}

You only need to test for a given candidate, yes? What is the for loop accomplishing? Could the results of the loop be throwing your testing program off?
Also, there is a missing } in the code. It will not run as posted without adding another } at the end, after which it runs fine for the following input:
10 1 2 3 4 5 6 7 8 9 10
IsFibo
IsFibo
IsFibo
IsNotFibo
IsFibo
IsNotFibo
IsNotFibo
IsFibo
IsNotFibo
IsNotFibo

Taking into account all the above suggestions I wrote the following which passed all test cases
import java.io.*;
import java.util.*;
public class Solution {
public static void main(String[] args) {
Scanner sc = new Scanner(System.in);
long[] fib = new long[52];
Set<Long> fibSet = new HashSet<>(52);
fib[0] = 0L;
fib[1] = 1L;
for(int i = 2; i < 52; i++){
fib[i] = fib[i-1] + fib[i - 2];
fibSet.add(fib[i]);
}
int n = sc.nextInt();
long cand;
for(int i = 0; i < n; i++){
cand = sc.nextLong();
if(cand < 0){System.out.println("IsNotFibo");continue;}
if(fibSet.contains(cand)){
System.out.println("IsFibo");
}else{
System.out.println("IsNotFibo");
}
}
}
}
I wanted to be on the safer side hence I choose 52 as the number of elements in the Fibonacci sequence under consideration.

Complexity of coin algorithm

Can anyone tell me the complexity (Big O notation preferred) of this code? It finds the least number of "coins" needed to make a target sum.
To do this it calculates the least number of coins for each number up to the target starting from 1. Each number is worked out based on the possible pairs of numbers that could sum to it, and the pair with the smallest cost is used. An example hopefully makes this clearer
If the "coins" are {1, 3, 4} and the target is 13 then it iterates from 1 to 13, where the cost of 2 the minimum from (0+2, 1+1), the c(5) is the smallest cost of (c(0)+c(5), c(1)+c(4), c(2)+c(3)), etc up to c(13)
This is a version of the knapsack problem and I'm wondering how to define its complexity?
Code:
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;
}
}
EDIT: Upon research I think that the complexity is O(k*n^2) where n is the target, and k is the number of coins supplied, is this correct?

I thinky the code you provided is kind of chaotic. So this post is more about the conceptual algorithm instead of the real algorithm. This can differ a bit since for instance insertion in an ArrayList<T> is not O(1), but I'm confident that you can use good datastructures (for instance LinkedList<T>s) for this to let all operations run in constant time.
What your algorithm basically does is the following:
It starts with a map that maps all the given coins to one: it requires one coin to achieve the value on the coin.
For each iteration, it mixes all already achieved values with all already achieved values. The result is thus the sum of the coins and it takes at the sum of the number of coins unless it was already present in the collection.
This step you forgot: kick out values strictly larger than the requested value: since all coins are strictly positive, you will never be able to construct a value with such composition less than the requested value.
You keep doing this until you have constructed the requested coin value.
If at iteration i all new values added to the set are strictly larger than the requested value, you can stop: the requested value can't be constructed.
The parameters are:
n: the number of coins.
r: the requested value.
A first observation is that each step of (2.) requires O(s^2) time with s the number of elements in the set at the start of the iteration: this is because you match every value with every value.
A second observation is that you can never have more elements in the set than the requested value. This means that s is bounded by O(r) (we assume all coins are integers, thus the set can contain at most all integer values from 0 to r-1). Step (2.) has thus a maximum time complexity of O(r^2).
And furthermore the set evolves progressively: at each iteration, you will always construct a new value that is at least one larger than the maximum thus far. As a consequence, the algorithm will perform maximum O(r) iterations.
This implies that the algorithm has a time-complexity of O(r^3): r times O(r^2).
Why is the behavior exponential and thus at least NP-hard?
A first argument is that it comes down on how you represent input: in many cases, numbers are represented using a system with a radix greater than or equal to 2. This means that with k characters, you can represent a value that scales with O(g^k) with g the radix. Thus exponential. In other words, if you use a 32-bit number, worst case, r=O(2^32). So if you take this as input, there is an exponential part. If you would encode the target using unary notation, the algorithm is in P. But of course that's a bit like the padding-argument: given you provide enough useless input data (exponential or even super-exponential), all algorithms are in P, but you don't buy much with this.
A second argument is that if you leave the the requested value out of the input, you can only state that you start with n coins. You know that the number of iterations is fixed: you see the target value as an unknown constant. Each iteration, the total number of values in the Map<Integer,Integer> potentially squares. This thus means that the computational effort is:
n+n^2+n^4+n^6+...n^(log r)
^ ^ ^
| \-- first iteration \-- end of algorithm
\-- insertion
It is clear that this behavior is exponential in n.

how to code a factorial

my question is not so much about code as it is the logic behind writing a factorial program. I am currently taking a MOOC at the University of Helsinki and I have become stuck on this exercise. As the course moves on to new exercises the instructions have become more and more vague. I realize this probably isn't the place to ask this question and if you must tag it or remove it, I do understand. I am trying to learn this on my own as I do not have the time or money to actually attend a university. This course has no time constraint and I wont be receiving a certificate of achievement for it, I simply want the knowledge.
these are the instructions given for the exercise
Create a program that calculates the factorial of the number n. The factorial n! is calculated using the formula 1*2*3*...*n. For example 4! = 1*2*3*4 = 24. Additionally, it is defined that 0! = 1.
// i don't understand the example that 4!= 1*2*3*4 = 24
// or how 0! = 1 pertains to multiplying numbers in succession to find the
// factorial of the user input number.
// i understand that 0! = 1 simply delclares that 0 is not equal to 1
// and 4 is not equal to 24, however if the 4! = portion of this statement
// is in reference to the user input number 4 that statement would not be
// true as 1*2*3*4 does equal 24 and 4 would be the number of executions
// of the block execution of the loop required to write the factorial
// program.
// EDIT: okay so according to this http://en.wikipedia.org/wiki/Factorial
// i am wrong about what is being done here as they are not declaring
// that 4 not equals 24 but yet that 4! is a way of correlating the non
// negative numbers up to 4, but given that math is not my strong suit
// it is even more confusing to me as to what i should be doing.
Example outputs:
Type a number: 3
Factorial is 6
Type a number: 10
Factorial is 3628800
my current code attempt is as follows
public static void main(String[] args) {
Scanner reader = new Scanner(System.in);
System.out.println("Type a number:");
int userIn = Integer.parseInt(reader.nextLine());
int factorial = 1;
int extra = 1;
int sum = 0;
while (factorial <= userIn) {
factorial++;
sum = factorial + userIn + extra;
}
System.out.println("The factorial is:"+sum);
}
}
I do not understand what it is that i am missing, i know from research that in the real world you would not code this as there are libraries you can download to perform the factorial function that are much more efficient than what i could code, but i don't want to simply skip this exercise with the knowledge that someone else has already coded and created a library to make our lives easier, i want to learn everything that this course has to offer. if i have made a simple error i don't mind an offered code correction, however i want to understand what makes the factorial operation tick so to speak, not just be given the answer so i can move on.

The factorial of a non-negative integer n, denoted by n!, is the product of all positive integers less than or equal to n. Eg:- 4!=1*2*3*4 . 0!=1 states that factorial of 0 is 1 and not that 0 is not equal to 1. The value of 0! is 1, according to the convention for an empty product. An empty product, or nullary product, is the result of multiplying no factors. It is by convention equal to the multiplicative identity 1 , just as the empty sum—the result of adding no numbers—is by convention zero (Like the sum of first 0 natural numbers would we 0), the additive identity.
For more on empty products read here http://en.wikipedia.org/wiki/Empty_product
For the programming part, there are basically two approaches to a factorial program:-
Using a for loop (No recursion)
int factorial ( int input )
{
int x, fact = 1;
for ( x = input; x > 1; x--) // iterating from n -> n-1 -> n-2 ... 1
{
fact *= x; // multiplying each number into the fact variable to get the factorial
}
return fact;
}
Recursive approach -The function calls itself ( Note- avoid using this approach in actual programming as it may be highly resource consuming and bug prone, As pointed out by "Edwin Buck" in the comments)
public int Factorial(int n)
{
if (n == 0)
{
return 1; //Base condition - If factorial reaches 0 return 1 and end recursion
}
else
{
return n * Factorial(n-1); // For factorial of n, function returns n * Factorial(n-1) i.e recursively calling the factorial function with one less value in the parameter untill 0 is reached (upon which base condtiion will be evaluated)
}
}

Try this one if you don't want to use an external function
public static void main(String[] args) {
Scanner reader = new Scanner(System.in);
System.out.println("Type a number:");
int userIn = Integer.parseInt(reader.nextLine());
int factorial = 1;
int i= userin;
while (userin >= 1) {
factorial *= userIn;
userin--;
}
System.out.println("The factorial is:"+factorial);
}
}

The problem is here
sum = factorial + userIn + extra;
where you "calculate" your factorial from the latest factorial++ value in the loop.
You can't calculate factorials from sums in this manner. Factorials are products of all the integers between 1 and the "factorial" number, so
1! = 1
2! = 1 * 2
3! = 1 * 2 * 3
4! = 1 * 2 * 3 * 4
If you start off calculating your factorial wrong, then the other parts of the problem don't matter much, they will be wrong by extension.

// Factorial example (ie 5 * 4 * 3 * 2 * 1)
function factorial($n) {
if ($n == 1) return 1;
return $n * factorial($n-1);
}
echo factorial(5); // Outputs 120
// Nested Array Summing Example
$example = array(1, 2, array(10,20,30), 4);
function sum_array($array) {
$total = 0;
foreach ($array as $element) {
if(is_array($element)) {
$total += sum_array($element);
} else {
$total += $element;
}
}
return $total;
}
echo sum_array($example); // Outputs 67

Your question is similar to mine, and it was actually a school assignment.
Though question is answered, i will contribute my solution.
public static void main(String[] args) {
Scanner reader = new Scanner(System.in);
int i = 1;
int factorial = 1;
System.out.println("Give number: ");
int number = Integer.parseInt(reader.nextLine());
while (i <= number) {
factorial = factorial * i;
i++;
}
System.out.println("Answer is " + factorial);
}