Develop Reference

Number of subset

class Solution {
int f(int[] a, int s, int n) {
if (n == 0)
return s;
return f(a, s + 1, n - 1) + f(a, s, n - 1);
}
}
class Test {
public static void main(String[] args) {
int[] a = { 1, 1, 2, 3 };
System.out.println(new Solution().f(a, 0, a.length));
}
}
I have written a code to print the number of subset, at every index I got two choices whether to include the a[i] in the subset or not for that I add 1 to s whenever the element is to be included, but this approach gives wrong answer. Why it is wrong?

Math.pow(2, a.length)
would be the obvious solution for that. but if you really want to find it that way it should 'return 1' instead of 'return s' since each time it arrives at zero, it means no element is left, thus empty list, thus 1.

Finding the largest element in an array using recursion in Java

This is what I have so far, but I'm confused on how to keep track of the index. I would change the parameters of the method, but I'm not allowed.
I can only use a loop to make another array. Those are the restrictions.
public class RecursiveFinder {
static int checkedIndex = 0;
static int largest = 0;
public static int largestElement(int[] start){
int length = start.length;
if(start[length-1] > largest){
largest = start[length-1];
int[] newArray = Arrays.copyOf(start, length-1);
largestElement(newArray);
}
else{
return largest;
}
}
/**
* #param args
*/
public static void main(String[] args) {
int[] array1 = {0,3,3643,25,252,25232,3534,25,25235,2523,2426548,765836,7475,35,547,636,367,364,355,2,5,5,5,535};
System.out.println(largestElement(array1));
int[] array2 = {1,2,3,4,5,6,7,8,9};
System.out.println(largestElement(array2));
}
}

Recursive method doesn't need to keep the largest value inside.
2 parameters method
Start to call with:
largestElement(array, array.length-1)
Here is the method:
public static int largestElement(int[] start, int index) {
if (index>0) {
return Math.max(start[index], largestElement(start, index-1))
} else {
return start[0];
}
}
The 3rd line of method is the hardest one to understand. It returns one of two elements, larges of the one of current index and of remaining elements to be checked recursively.
The condition if (index>0) is similar to while-loop. The function is called as long as the index remains positive (reaches elements in the array).
1 parameter method
This one is a bit tricky, because you have to pass the smaller array than in the previous iteration.
public static int largestElement(int[] start) {
if (start.length == 1) {
return start[0];
}
int max = largestElement(Arrays.copyOfRange(start, 1, start.length));
return start[0] > max ? start[0] : max;
}
I hope you do this for the study purposes, actually noone has a need do this in Java.

Try that for the upper class, leave the main method it's is correct.
public class dammm {
public static int largestElement(int[] start){
int largest = start[0];
for(int i = 0; i<start.length; i++) {
if(start[i] > largest){
largest = start[i];
}
}return largest;
}

If your goal is to achieve this by using recursion, this is the code that you need. It is not the most efficient and it is not the best way to deal with the problem but it is probably what you need.
public static int largestElement(int[] start){
int length = start.length;
if (start.lenght == 1){
return start[0];
} else {
int x = largestElement(Arrays.copyOf(start, length-1))
if (x > start[length-1]){
return x;
} else {
return start[length-1];
}
}
}
Imagine that you have a set of numbers you just have to compare one number with the rest of them.
For example, given the set {1,8,5} we just have to check if 5 is larger than the largest of {1,8}. In the same way you have to check if 8 is larger than the largest of {1}. In the next iteration, when the set one have one value, you know that that value is the bigger of the set.
So, you go back to the previous level and check if the returned value (1) is larger than 8. The result (8) is returned to the previous level and is checked against 5. The conclusion is that 8 is the larger value

One parameter, no copying. Tricky thing is, we need to pass a smaller array to the same method. So a global variable is required.
// Number of elements checked so far.
private static int current = -1;
// returns the largest element.
// current should be -1 when user calls this method.
public static int largestElement(int[] array) {
if (array.length > 0) {
boolean resetCurrent = false;
if (current == -1) {
// Initialization
current = 0;
resetCurrent = true;
} else if (current >= array.length - 1) {
// Base case
return array[array.length - 1];
}
try {
int i = current++;
return Math.max(array[i], largestElement(array));
} finally {
if (resetCurrent) {
current = -1;
}
}
}
throw new IllegalArgumentException("Input array is empty.");
}
If you can create another method, everything would be much simpler.
private static int recursiveFindLargest(int [] array, int i) {
if (i > 0) {
return Math.max(array[i], recursiveFindLargest(array, i-1));
} else {
return array[0];
}
}
public static int largestElement(int [] array) {
// For empty array, we cannot return a value to indicate this situation,
//all integer values are possible for non-empty arrays.
if (array.length == 0) throw new IllegalArgumentException();
return recursiveFindLargest(array, array.length - 1);
}

For this problem you really need to think about working with the base case. Take a look at some of the simple cases you would have to deal with:
If the array is length 1, then you return the only value
If the array is length 2, then you return the maximum of the two values
If the array is length 3, then ?
From the above we can get an idea of the structure of the problem:
if array.length == 1 then
return array[0]
else
return the maximum of the values
In the above if we have only one element, it is the maximum value in the list. If we have two values, then we have to find the maximum of those values. From this, we can then use the idea that if we have three values, we can find the maximum of two of them, then compare the maximum with the third value. Expanding this into pseudo code, we can get something like:
if array.length == 1 then
return array[0]
else
new array = array without the first element (e.g. {1, 2, 3} => {2, 3})
return maximum(array[0], largestElement(new array))
To explain the above a little better, think of execution like a chain (example for {1, 2, 3}).
Array: {1, 2, 3}, maximum(array[0] = 1, largestElement(new array = {2, 3}))
Array: {2, 3}, maximum(array[0] = 2, largestElement(new array = {3}))
Array: {3}, array[0] = 3 => length is 1 so return 3
The above then rolls back up the 'tree' structure where we get:
maximum (1, maximum(2, (return 3)))
Once you have the maximum value, you can use the sample principle as above to find the index with a separate method:
indexOf(array, maximum)
if array[0] == maximum then
return 0
else if array.length == 1 then
return -1
else
new array = array without the first element (e.g. {1, 2, 3} => {2, 3})
result = indexOf(new array, maximum)
return (result == -1) ? result : result + 1
For looking into this more, I would read this from the Racket language. In essence it shows the idea of array made purely from pairs and how you can use recursion to do iteration on it.
If you are interested, Racket is a pretty good resource for understanding recursion. You can check out University of Waterloo tutorial on Racket. It can give you a brief introduction to recursion in an easy to understand way, as well as walking you through some examples to understand it better.

You don't need to keep a largest variable outside your method - that's generally not a good practice with recursion which should return all context of the results.
When you think about recursion try to think in terms of a simple base case where the answer is obvious and then, for all other cases how to break it down into a simpler case.
So in pseduo-code your algorithm should be something like:
func largest(int[] array)
if array has 1 element
return that element
else
return the larger of the first element and the result of calling largest(remaining elements)
You could use Math.max for the 'larger' calculation.
It's unfortunate that you can't change the arguments as it would be easier if you could pass the index to start at or use lists and sublists. But your copying method should work fine (assuming efficiency isn't a concern).
An alternative to the algorithm above is to make an empty array the base case. This has the advantage of coping with empty arrays (by return Integer.MIN_VALUE):
int largest(int[] array) {
return array.length == 0
? Integer.MIN_VALUE
: Math.max(array[0], largest(Arrays.copyOfRange(array, 1, array.length)));
}

Here is working example of code with one method param
public int max(int[] list) {
if (list.length == 2) return Math.max(list[0], list[1]);
int max = max(Arrays.copyOfRange(list, 1, list.length));
return list[0] < max ? max : list[0];
}

private static int maxNumber(int[] arr,int n,int max){
if(n<0){
return max;
}
max = Math.max(arr[n],max);
return maxNumber(arr,n-1,max);
}

Divisors inside an array

I need to write a method that takes an array of integers and checks for every element if all its divisors (except the number itself and 1) are present in this array. If yes, the method will return true.
For example, the following array will return true:
4,5,10,2
I can't think of something efficient enough to be implemented. Could you guys help me out here?
I've been thinking to iterate through every element in the array, search for all of its divisors, put them on array, return the array and then compare to the elements in the original array.
This is a possible solution and it could work but I want to know of other possible solutions.
EDIT: Here is a code I've came up with but it is super slow. Could you guys help me optimise it a little bit?:
import java.util.Arrays;
public class Divisors {
public static void main(String[] args) {
int[] numbers = { 4, 5, 10, 2 };
boolean flag = true;
for (int num : numbers) {
if (num % 2 != 0) {
for (int subNum = 1; subNum < num / 2; num += 2) {
if(num%subNum == 0 && subNum != 1) {
if(!Arrays.asList(numbers).contains(subNum)) {
flag = false;
}
}
}
} else {
for (int subNum = 1; subNum < num / 2; num++) {
if(num%subNum == 0 && subNum != 1) {
if(!Arrays.asList(numbers).contains(subNum)) {
flag = false;
}
}
}
}
}
System.out.println("Result is: "+flag);
}
}

I think the following alogorithm solves your need. I have tested it on a few cases and it seems to work.
For example the array:
int[] set = {2, 3, 4, 5, 7, 10, 11, 15, 18, 35};
executes instantly giving the answer "true". Try removing the 7 which will give the answer "false".
You call it thus:
reduce(set, 0, 0)
The principle used is to iterative recursively through the array, reducing the array through factorization of the array by each element. If you find an element which is smaller than the last factor, it means it can't be factored. This only works if the array is sorted. Once you reach the end of the array, you know all elements have been factored.
private static boolean reduce (int[] set, int index, int factor) {
// NOTE: set must be a sorted set of integers
if (index == set.length) {
return true;
} else {
int divisor = set[index];
if (divisor != 1) {
if (divisor < factor) return false;
for (int i = index; i < set.length; i++) {
while ((set[i]%divisor) == 0) {
set[i] = set[i]/divisor;
}
}
return reduce(set, index+1, divisor);
} else {
return reduce(set, index+1, factor);
}
}
}
See if it works, let me know if you run into any problems.

1.Iterate through every element in the array
2. Find in for loop its divisor
3. While doing 2), check for every divisor if it is contained in the array. If false - return false.

Finding peak values from an array in a given range

The method getPeakCount takes an int array and a range (int) as an input and returns the number of integers that are greater than all the elements to either side for the given range.
For example, consider an array {1,4,2,6,4,5,10,8,7,11} and range 2. The result should be 3, as {..,4,2,6,4,5,..}, {..,4,5,10,8,7,..} and {..,8,7,11} satisfy this condition. These satisfy the condition because 6, 10 and 11 are all greater than the 2 elements to both their left and right.
Note that for the the corner elements like 1 and 11, there's no need to check the left and right side respectively.
My code is below, but it is not correct.
static int getPeakCount(int[] arr, int R) {
int result=0;
for(int i=0;i<arr.length;i++){
if(i==0){
if(arr[i]>arr[i+1]&&arr[i]>arr[i+2]){
result++;
}
} //-----> closing if(i==0) condition
else if(i==arr.length-1){
if(arr[i]>arr[i-1]&&arr[i]>arr[i-2]){
result++;
}
}
else if(i+R>arr.length){
if(arr[i]>arr[i-R] && arr[i]>arr[i-R+1]){
System.out.println(arr[i]);
result++;
}
}
else{
if(arr[i]>arr[i+1] && arr[i]>arr[i+2] && arr[i]>arr[i-R] && arr[i]>arr[i-R+1]){
System.out.println(arr[i]);
result++;
}
}
}
return result;
}
I don't know whether I'm going in the right direction or not, and for last if condition it's throwing an java.lang.ArrayIndexOutOfBoundsException.
P.S. Don't consider this code as solution to remove errors from this. This is just the attempt I tried.

I think the right idea, and devnull is right. You just need to check the center, so change the loop to start at 1 and end 1 before the end. I commented out the end conditions. I think this does what you were asking, though not 100% sure I understood what you were after.
I should add, I use variables like l (left), r (right) and c (center) for clarity. You can make this much faster if you have large arrays. There is also redundancy in that it checks conditions it should know are already false (if I find a peak, I should skip the next value, as it can't also be a peak).
public class PeakChecker {
/**
* #param args the command line arguments
*/
public static void main(String[] args) {
int[] array = new int[]{1, 4, 2, 6, 4, 5, 10, 8, 7, 11};
System.out.println(nPeaks(array, 2));
}
static int nPeaks(int[] array, int range) {
// Check for special cases
if (array == null) {
return 0;
}
int result = 0, l, r;
// Check main body
for (int i = 0; i < array.length; i++) {
boolean isPeak = true;
// Check from left to right
l = Math.max(0, i - range);
r = Math.min(array.length - 1, i + range);
for (int j = l; j <= r; j++) {
// Skip if we are on current
if (i == j) {
continue;
}
if (array[i] < array[j]) {
isPeak = false;
break;
}
}
if (isPeak) {
System.out.println("Peak at " + i + " = " + array[i]);
result++;
i += range;
}
}
return result;
}
}

The last if condition shall throw exception when i == arr.length - 2.
This is because arr[i+2] in that case is out of bounds.

If you read the ArrayIndexOutOfBoundsException stack trace, it will tell you a line of code the error happened on. Look on that line of code and you'll probably see arr[i+1] or arr[i-1] or something. Certainly, at least one access on that line will be out of bounds. That's the problem.

algorithm removing duplicate elements in array without auxillay storage

I am working on this famous interview question on removing duplicate elements in array without using auxillary storage and preserving the order;
I have read a bunch of posts; Algorithm: efficient way to remove duplicate integers from an array, Removing Duplicates from an Array using C.
They are either implemented in C (without explanation) or the Java Code provided just fails when there is consecutive duplicates such as [1,1,1,3,3].
I am not quite confident with using C, my background is Java. So I implemented the code myself;
it follows like this:
use two loops, the outer-loop traverses the array and inner loop checks for duplicates and if present replace it with null.
Then I go over the duplicate-replaced-null array and remove null elements and replacing it with the next non-null element.
The total run-time I see now is O(n^2)+O(n) ~ O(n^2). Reading the above posts, I understood this is the best we can do, if no sorting and auxiliary storage is allowed.
My code is here: I am looking for ways to optimize any further (if there is a possibility) or a better/simplisitc logic;
public class RemoveDup {
public static void main (String[] args){
Integer[] arr2={3,45,1,2,3,3,3,3,2,1,45,2,10};
Integer[] res= removeDup(arr2);
System.out.println(Arrays.toString(res));
}
private static Integer[] removeDup(Integer[] data) {
int size = data.length;
int count = 1;
for (int i = 0; i < size; i++) {
Integer temp = data[i];
for (int j = i + 1; j < size && temp != null; j++) {
if (data[j] == temp) {
data[j] = null;
}
}
}
for (int i = 1; i < size; i++) {
Integer current = data[i];
if (data[i] != null) {
data[count++] = current;
}
}
return Arrays.copyOf(data, count);
}
}
EDIT 1; Reformatted code from #keshlam throws ArrayIndexOutofBound Exception:
private static int removeDupes(int[] array) {
System.out.println("method called");
if(array.length < 2)
return array.length;
int outsize=1; // first is always kept
for (int consider = 1; consider < array.length; ++consider) {
for(int compare=0;compare<outsize;++compare) {
if(array[consider]!=array[compare])
array[outsize++]=array[consider]; // already present; advance to next compare
else break;
// if we get here, we know it's new so append it to output
//array[outsize++]=array[consider]; // could test first, not worth it.
}
}
System.out.println(Arrays.toString(array));
// length is last written position plus 1
return outsize;
}

OK, here's my answer, which should be O(N*N) worst case. (With smaller constant, since even worstcase I'm testing N against -- on average -- 1/2 N, but this is computer science rather than software engineering and a mere 2X speedup isn't significant. Thanks to #Alexandru for pointing that out.)
1) Split cursor (input and output advanced separately),
2) Each new value only has to be compared to what's already been kept, and compare can stop if a match is found. (The hint keyword was "incremental")
3) First element need not be tested.
4) I'm taking advantage of labelled continue where I could have instead set a flag before breaking and then tested the flag. Comes out to the same thing; this is a bit more elegant.
4.5) I could have tested whether outsize==consider and not copied if that was true. But testing for it would take about as many cycles as doing the possibly-unnecessary copy, and the majority case is that they will not be the same, so it's easier to just let a possibly redundant copy take place.
5) I'm not recopying the data in the key function; I've factored out the copy-for-printing operation to a separate function to make clear that removeDupes does run entirely in the target array plus a few automatic variables on the stack. And I'm not spending time zeroing out the leftover elements at the end of the array; that may be wasted work (as in this case). Though I don't think it would actually change the formal complexity.
import java.util.Arrays;
public class RemoveDupes {
private static int removeDupes(final int[] array) {
if(array.length < 2)
return array.length;
int outsize=1; // first is always kept
outerloop: for (int consider = 1; consider < array.length; ++consider) {
for(int compare=0;compare<outsize;++compare)
if(array[consider]==array[compare])
continue outerloop; // already present; advance to next compare
// if we get here, we know it's new so append it to output
array[outsize++]=array[consider]; // could test first, not worth it.
}
return outsize; // length is last written position plus 1
}
private static void printRemoveDupes(int[] array) {
int newlength=removeDupes(array);
System.out.println(Arrays.toString(Arrays.copyOfRange(array, 0, newlength)));
}
public static void main(final String[] args) {
printRemoveDupes(new int[] { 3, 45, 1, 2, 3, 3, 3, 3, 2, 1, 45, 2, 10 });
printRemoveDupes(new int[] { 2, 2, 3, 3 });
printRemoveDupes(new int[] { 1, 1, 1, 1, 1, 1, 1, 1 });
}
}
LATE ADDITION: Since folks expressed confusion about point 4 in my explanation, here's the loop rewritten without labelled continue:
for (int consider = 1; consider < array.length; ++consider) {
boolean matchfound=false;
for(int compare=0;compare<outsize;++compare) {
if(array[consider]==array[compare]) {
matchfound=true;
break;
}
if(!matchFound) // only add it to the output if not found
array[outsize++]=array[consider];
}
Hope that helps. Labelled continue is a rarely-used feature of Java, so it isn't too surprising that some folks haven't seen it before. It's useful, but it does make code harder to read; I probably wouldn't use it in anything much more complicated than this simple algorithm.

Here one version which doesn't use additional memory (except for the array it returns) and doesn't sort either.
I believe this is slightly worse than O(n*log n).
Edit: I'm wrong. This is slightly better than O(n^3).
public class Dupes {
private static int[] removeDupes(final int[] array) {
int end = array.length - 1;
for (int i = 0; i <= end; i++) {
for (int j = i + 1; j <= end; j++) {
if (array[i] == array[j]) {
for (int k = j; k < end; k++) {
array[k] = array[k + 1];
}
end--;
j--;
}
}
}
return Arrays.copyOf(array, end + 1);
}
public static void main(final String[] args) {
System.out.println(Arrays.toString(removeDupes(new int[] { 3, 45, 1, 2, 3, 3, 3, 3, 2, 1, 45, 2, 10 })));
System.out.println(Arrays.toString(removeDupes(new int[] { 2, 2, 3, 3 })));
System.out.println(Arrays.toString(removeDupes(new int[] { 1, 1, 1, 1, 1, 1, 1, 1 })));
}
}
and here's a modified version which doesn't shift all of the elements from after the dupe. Instead it simply switches the dupe with the last, non-matching element. This obviously can't guarantee order.
private static int[] removeDupes(final int[] array) {
int end = array.length - 1;
for (int i = 0; i <= end; i++) {
for (int j = i + 1; j <= end; j++) {
if (array[i] == array[j]) {
while (end >= j && array[j] == array[end]) {
end--;
}
if (end > j) {
array[j] = array[end];
end--;
}
}
}
}
return Arrays.copyOf(array, end + 1);
}

Here you have a worst case of O(n^2) where the return points to the first non unique element. So everything before it is unique.
Instead of C++ iterators indices in Java can be used.
std::vecotr<int>::iterator unique(std::vector<int>& aVector){
auto end = aVector.end();
auto start = aVector.begin();
while(start != end){
auto num = *start; // the element to check against
auto temp = ++start; // start get incremented here
while (temp != end){
if (*temp == num){
std::swap(temp,end);
end--;
}
else
temp++; // the temp is in else so that if the swap occurs the algo should still check the swapped element.
}
}
return end;
}
Java equivalent code: (the return will be an int which is the index of the first not unique element)
int unique(int[] anArray){
int end = anArray.length-1;
int start = 0;
while(start != end){
int num = anArry[start]; // the element to check against
int temp = ++start; // start get incremented here
while (temp != end){
if (anArry[temp] == num){
swap(temp,end); // swaps the values at index of temp and end
end--;
}
else
temp++; // the temp is in else so that if the swap occurs the algo should still check the swapped element.
}
}
return end;
}
The slight difference in this algo and yours is in your point 2. Where instead of replacing the current element with null you go with swapping it with the last possibly unique element which on the first swap is the last element of array, on second swap the second last and so on.
You might as well consider looking at the std::unique implementation in C++ which is linear in one less than the distance between first and last: Compares each pair of elements, and possibly performs assignments on some of them., but as it was noted by #keshlam it is used on sorted arrays only. The return value is the same as in my algo. Here is the code directly from the standard library:
template<class _FwdIt, class _Pr> inline
_FwdIt _Unique(_FwdIt _First, _FwdIt _Last, _Pr _Pred)
{ // remove each satisfying _Pred with previous
if (_First != _Last)
for (_FwdIt _Firstb; (_Firstb = _First), ++_First != _Last; )
if (_Pred(*_Firstb, *_First))
{ // copy down
for (; ++_First != _Last; )
if (!_Pred(*_Firstb, *_First))
*++_Firstb = _Move(*_First);
return (++_Firstb);
}
return (_Last);
}

To bring in a bit perspective - one solution in Haskell, it uses lists instead of arrays
and returns the reversed order, which can be fixed by applying reverse at the end.
import Data.List (foldl')
removeDup :: (Eq a) => [a] -> [a]
removeDup = foldl' (\acc x-> if x `elem` acc then acc else x:acc) []