We Keep Coding

Rearrange elements in an integer array in a fashion where-you first replace and then move the replaced integer to first part of the array

I came across a Hackerearth coding problem where you have to perform the following tasks over an integer array-
Search for a particular number in the array and replace it's occurrences with 1
Move all the 1s to the first part of the array, maintaining the original order of the array
For example- if we have an integer array {22,1,34,22,16,22,35,1}, here we search for the number "22" (let us assume it is present in the array), replace it with 1 and move all those 1s (including the 1s already present) to the first part of the array and the resultant array should look like {1,1,1,1,1,1,34,16,35} -maintaining the original order of the array, preferably in Java.
I actually have coded a solution and it works fine but is not optimal, can anyone help me find an optimal solution (w.r.t. time-space complexity)?
Below is my solution-
public static void main(String[] args) {
int[] n = rearr(new int[] {22,1,34,22,16,22,1,34,1}, 22);
for(int i=0; i<n.length; i++) {
System.out.print(n[i]+" ");
}
}
static int[] rearr(int[] a, int x) {
int[] temp = new int[a.length];
int j=0, c=0, k=0;
//search and replace
for(int i=0; i<a.length; i++) {
if(a[i] == x) {
a[i] = 1;
}
}
//shift all 1s to first part of array or shift all non-1s to last part of the array
for(int i=0; i<a.length; i++) {
if(a[i] != 1) {
temp[j] = a[i];
j++;
}
if(a[i] == 1) {
c++;
}
}
j=0;
for(int i=0; i<a.length && c>0; i++, c--) {
a[i] = 1;
j++;
}
for(int i=j ;i<a.length; i++) {
a[i] = temp[k];
k++;
}
return a;
}

This can be done in linear time and space complexity, by returning a completely new list instead of modifying the original list.
static int[] rearr(int[] a, int x) {
// allocate the array we'll return
int[] b = new int[a.length];
int fillvalue = 1;
// iterate backwards through the list, and transplant every value OTHER than
// (x or 1) to the last open index in b, which we track with b_idx
int b_idx = b.length - 1;
for (int i = a.length - 1; i >= 0; i--) {
if (a[i] != x && a[i] != fillvalue)) {
b[b_idx] = a[i];
b_idx--;
}
}
// once we've gone through and done that, fill what remains of b with ones
// which are either original or are replacements, we don't care
for (int i = b_idx; i >= 0; i--) {
b[i] = fillvalue;
}
return b;
}
This is linear space complexity because it requires additional space equal to the size of the given list. It's linear time complexity because, in the worst case, it iterates over the size of the list exactly twice.
As a bonus, if we decide we want to leave the original 1s where they were, we can do that without any trouble at all, by simply modifying the if condition. Same if we decide we want to change the fill value to something else.
Doing this with constant space complexity would require O(n^2) list complexity, as it would require swapping elements in a to their proper positions. The easiest way to do that would probably be to do replacements on a first run through the list, and then do something like bubblesort to move all the 1s to the front.

This can be done in a single iteration through the array. We can use 2 pointer approach here where we will use on pointer to iterate through the array and other one to point to the index of 1 in the array.
The code is below:
public static void main(String[] args) {
// input array
int[] arr = { 22, 1, 34, 22, 16, 22, 35, 1, 20, 33, 136 };
// element to be replaced
int x = 22;
int j = -1;
for (int i = arr.length - 1; i >= 0; i--) {
if (arr[i] == 1 || arr[i] == x) {
if (j == -1) {
j = i;
}
// incase arr[i]==x
arr[i] = 1;
} else {
if (j != -1) {
arr[j] = arr[i];
arr[i] = 1;
j--;
}
}
}
for (int i = 0; i < arr.length; i++) {
System.out.println(arr[i]);
}
}
Here we initialise j=-1 since we consider there are no 1's present in the array.
Then we start iterating the array from the end towards the starting of the array as we have to push all the 1's to the starting of the array. Now when we reach to 1 or x (particular number in your case), we check if this is first occurrence of the x or 1, if yes then we initialise the j with this index and change arr[i] = 1 because this could be equal to x then we need to make it 1. If the arr[i] is not 1 or x it means its a number which we need to push at back of the array. We check if we have position of 1 or j=-1. If j=-1 it means this number is already pushed back at end of array else we swap the number at i and j, and decrement j by 1.
At the end of the array we will have the array sorted in a fashion which is required.
Time Complexity: Since we are only iterating the array one, hence the time complexity is O(n).
Space Complexity: Since there are no extra space being used or constant space being used hence the space complexity is O(1)

Trying to create a array with the intersection of two arrays but fails at creating array with the proper structure

So, I am trying to create 2 randomly generated arrays,(a, and b, each with 10 unique whole numbers from 0 to 20), and then creating 2 arrays with the info of the last two. One containing the numbers that appear in both a and b, and another with the numbers that are unique to a and to b. The arrays must be listed in a "a -> [1, 2, 3,...]" format. At the moment I only know how to generate the 2 arrays, and am currently at the Intersection part. The problem is, that I can create a array with the correct list of numbers, but it will have the same length of the other two, and the spaces where it shouldn't have anything, it will be filled with 0s when its supposed to create a smaller array with only the right numbers.
package tps.tp1.pack2Arrays;
public class P02ArraysExtractUniqsAndReps {
public static void main(String[] args) {
int nbr = 10;
int min = 0;
int max = 20;
generateArray(nbr, min, max);
System.out.println();
}
public static int[] generateArray(int nbr, int min, int max) {
int[] a = new int[nbr];
int[] b = new int[nbr];
int[] s = new int[nbr];
s[0] = 0;
for (int i = 0; i < a.length; i++) {
a[i] = (int) (Math.random() * (max - min));
b[i] = (int) (Math.random() * (max - min));
for (int j = 0; j < i; j++) {
if (a[i] == a[j]) {
i--;
}
if (b[i] == b[j]) {
i--;
}
}
}
System.out.println("a - > " + Arrays.toString(a));
System.out.println("b - > " + Arrays.toString(b));
for (int k = 0; k < a.length; k++) {
for (int l = 0; l < b.length; l++) {
if (a[k] == b[l]) {
s[l] = b[l];
}else {
}
}
}
System.out.println("(a ∪ (b/(a ∩ b)) - > " + Arrays.toString(s));
return null;
}
public static boolean hasValue(int[] array, int value) {
for (int i = 0; i < array.length; i++) {
if (array[i] == value) {
return true;
}
}
return false;
}
}
Is there any way to create the array without the incorrect 0s? (I say incorrect because it is possible to have 0 in both a and b).
Any help/clarification is appreciated.

First, allocate an array large enough to hold the intersection. It needs to be no bigger that the smaller of the source arrays.
When you add a value to the intersection array, always add it starting at the beginning of the array. Use a counter to update the next position. This also allows the value 0 to be a valid value.
Then when finished. use Array.copyOf() to copy only the first part of the array to itself, thus removing the empty (unfilled 0 value) spaces. This works as follow assuming count is the index you have been using to add to the array: Assume count = 3
int[] inter = {1,2,3,0,0,0,0};
inter = Arrays.copyOf(inter, count);
System.out.println(Arrays.toString(inter);
prints
[1,2,3]
Here is an approach using a List
int[] b = {4,3,1,2,5,0,2};
int [] a = {3,5,2,3,7,8,2,0,9,10};
Add one of the arrays to the list.
List<Integer> list = new ArrayList<>();
for(int i : a) {
list.add(i);
}
Allocate the intersection array with count used as the next location. It doesn't matter which array's length you use.
int count = 0;
int [] intersection = new int[a.length];
Now simply iterate thru the other array.
if the list contains the value, add it to the intersection array.
then remove it from the list and increment count. NOTE - The removed value must be converted to an Integer object, otherwise, if a simple int value, it would be interpreted as an index and the value at that index would be removed and not the actual value itself (or an Exception might be thrown).
once finished the intersection array will have the values and probably unseen zeroes at the end.
for(int i = 0; i < b.length; i++) {
int val = b[i];
if (list.contains(val)) {
intersection[count++] = val;
list.remove(Integer.valueOf(val));
}
}
To shorten the array, use the copy method mentioned above.
intersection = Arrays.copyOf(intersection, count);
System.out.println(Arrays.toString(intersection));
prints
[3, 2, 5, 0, 2]
Note that it does not matter which array is which. If you reverse the arrays for a and b above, the same intersection will result, albeit in a different order.

The first thing I notice is that you are declaring your intersection array at the top of the method.
int[] s = new int[nbr];
You are declaring the same amount of space for the array regardless of the amount you actually use.
Method Arrays.toString(int []) will print any uninitialized slots in the array as "0"
There are several different approaches you can take here:
You can delay initializing the array until you have determined the size of the set you are dealing with.
You can transfer your content into another well sized array after figuring out your result set.
You could forego using Array.toString, and build the string up yourself.

CodeFights - issues with time limit when writing FirstDuplicate method

I'm trying to solve the problem below from CodeFights. I left my answer in Java after the question. The code works for all the problems, except the last one. Time limit exception is reported. What could I do to make it run below 3000ms (CodeFights requirement)?
Note: Write a solution with O(n) time complexity and O(1) additional space complexity, since this is what you would be asked to do during a real interview.
Given an array a that contains only numbers in the range from 1 to a.length, find the first duplicate number for which the second occurrence has the minimal index. In other words, if there are more than 1 duplicated numbers, return the number for which the second occurrence has a smaller index than the second occurrence of the other number does. If there are no such elements, return -1.
Example
For a = [2, 3, 3, 1, 5, 2], the output should be
firstDuplicate(a) = 3.
There are 2 duplicates: numbers 2 and 3. The second occurrence of 3 has a smaller index than than second occurrence of 2 does, so the answer is 3.
For a = [2, 4, 3, 5, 1], the output should be
firstDuplicate(a) = -1.
Input/Output
[time limit] 3000ms (java)
[input] array.integer a
Guaranteed constraints:
1 ≤ a.length ≤ 105,
1 ≤ a[i] ≤ a.length.
[output] integer
The element in a that occurs in the array more than once and has the minimal index for its second occurrence. If there are no such elements, return -1.
int storedLeastValue = -1;
int indexDistances = Integer.MAX_VALUE;
int indexPosition = Integer.MAX_VALUE;
for (int i = 0; i < a.length; i++)
{
int tempValue = a[i];
for (int j = i+1; j < a.length; j++) {
if(tempValue == a[j])
{
if(Math.abs(i-j) < indexDistances &&
j < indexPosition)
{
storedLeastValue = tempValue;
indexDistances = Math.abs(i-j);
indexPosition = j;
break;
}
}
}
}
return storedLeastValue;

Your solution has two nested for loops which implies O(n^2) while the question explicitly asks for O(n). Since you also have a space restriction you can't use an additional Set (which can provide a simple solution as well).
This question is good for people that have strong algorithms/graph theory background. The solution is sophisticated and includes finding an entry point for a cycle in a directed graph. If you're not familiar with these terms I'd recommend that you'll leave it and move to other questions.

Check this one, it's also O(n) , but without additional array.
int firstDuplicate(int[] a) {
if (a.length <= 1) return -1;
for (int i = 0; i < a.length; i++) {
int pos = Math.abs(a[i]) - 1;
if (a[pos] < 0) return pos + 1;
else a[pos] = -a[pos];
}
return -1;
}

The accepted answer does not work with the task.
It would work if the input array would indeed contain no bigger value than its length.
But it does, eg.: [5,5].
So, we have to define which number is the biggest.
int firstDuplicate(int[] a) {
int size = 0;
for(int i = 0; i < a.length; i++) {
if(a[i] > size) {
size = a[i];
}
}
int[] t = new int[size+1];
for(int i = 0; i < a.length; i++) {
if(t[a[i]] == 0) {
t[a[i]]++;
} else {
return a[i];
}
}
return -1;
}

What about this:
public static void main(String args[]) {
int [] a = new int[] {2, 3, 3, 1, 5, 2};
// Each element of cntarray will hold the number of occurrences of each potential number in the input (cntarray[n] = occurrences of n)
// Default initialization to zero's
int [] cntarray = new int[a.length + 1]; // need +1 in order to prevent index out of bounds errors, cntarray[0] is just an empty element
int min = -1;
for (int i=0;i < a.length ;i++) {
if (cntarray[a[i]] == 0) {
cntarray[a[i]]++;
} else {
min = a[i];
// no need to go further
break;
}
}
System.out.println(min);
}

You can store array values in hashSet. Check if value is already present in hashSet if not present then add it in hashSet else that will be your answer. Below is code which passes all test cases:-
int firstDuplicate(int[] a) {
HashSet<Integer> hashSet = new HashSet<>();
for(int i=0; i<a.length;i++){
if (! hashSet.contains(a[i])) {
hashSet.add(a[i]);
} else {
return a[i];
}
}
return -1;
}

My simple solution with a HashMap
int solution(int[] a) {
HashMap<Integer, Integer> countMap = new HashMap<Integer, Integer>();
int min = -1;
for (int i=0; i < a.length; i++) {
if (!(countMap.containsKey(a[i]))) {
countMap.put(a[i],1);
}
else {
return a[i];
}
}
return min;
}

Solution is very simple:
Create a hashset
keep iterating over the array
if element is already not in the set, add it.
else element will be in the set, then it mean this is minimal index of first/second the duplicate
int solution(int[] a) {
HashSet<Integer> set = new HashSet<>();
for(int i=0; i<a.length; i++){
if(set.contains(a[i])){
// as soon as minimal index duplicate found where first one was already in the set, return it
return a[i];
}
set.add(a[i]);
}
return -1;
}

A good answer for this exercise can be found here - https://forum.thecoders.org/t/an-interesting-coding-problem-in-codefights/163 - Everything is done in-place, and it has O(1) solution.

An algorithm where I find the min and max element value and then do it again after removing those elements

I have the methods to find the smallest and largest value, and also to place them where they need to be. I also have a method to call those methods, and shrink to a subarray. The problem is, even though it is sorting, I can't print the array once I've moved into the subarray. Please help, there has to be a better way and I've banged my head against the wall for a while now.
package mySort;
import java.util.Arrays;
public class MyAlg {
public static int findSmall(int[] input){
int sm = input[0];
for(int i = 0; i <= input.length - 1; i++){
if(sm < input[i])
sm = input[i];
}
input[0] = sm;
return sm;
}
public static int findLarge(int[] input){
int lg = input[input.length -1];
for(int i = 0; i <= input.length - 1; i++){
if(input[i] > lg)
lg = input[i];
}
input[input.length -1] = lg;
return lg;
}
public static int[] sort(int[] input){
findSmall(input);
findLarge(input);
for(int i = 0; i<= (input.length - 1) / 2; i++){
int[] tmp = Arrays.copyOfRange(input, i + 1, input.length - 2 );
findSmall(tmp);
findLarge(tmp);
}
}
}

I am not sure if you are required to use an array or not, but if you are free to use whatever data structure you like I would recommend a TreeSet. This data structure implements SortedSet which means as the objects are added they are sorted already for you. Then you can use methods such as
first() - to return the lowest value
last() - to return the highest value
Then you could remove those highest and lowest elements or use these methods after that
ceiling(int) - highest number lower than given int
floor(int) - smallest number higher than given int
Lmk if you need more help or just need an implementation for an array.

Unfortunately your code is quite flawed, so I just rewrote everything. The below code will sort any int[] by placing the smallest int in the input array in the left most unfilled position of a new array and placing the biggest in the right most unfilled position of a new array, until the new array is a sorted version of the input array. Enjoy
private static int[] sort(int[] input) {
//create an empty array the same size as input
int[] sorted = new int[input.length];
//create another empty array the same size as input
int[] temp = new int[input.length];
// copy input into temp
for (int i = 0; i <= (input.length - 1); i++) {
temp[i] = input[i];
}
//create variables to tell where to put big and small
//in the sorted array
int leftIndex = 0;
int rightIndex = sorted.length - 1;
//create variables to hold the biggest and smallest values in
//input. For now we'll give them the values of the first element
//in input, they'll change
int big = input[0];
int small = input[0];
// sort
//sort the array as you described
while (temp.length != 0) {
//find the biggest and smallest value in temp
big = findBig(temp);
small = findSmall(temp);
//place the biggest at the end of the sorted array
//and place the smallest at the beginning of the sorted array
sorted[leftIndex] = small;
sorted[rightIndex] = big;
//move the left index of the sorted array up, so we don't over write
//the element we put in on the next iteration, same for the right index to,
//but down
leftIndex++;
rightIndex--;
if(temp.length != 1){
//remove the biggest and smallest values from the temp array
temp = removeElement(temp, big);
temp = removeElement(temp, small);
}else{
//only remove one element in the event the array size is odd
//also not at this point leftIndex == rightIndex as it will be the last
//element
temp = removeElement(temp, big);
}
//repeat, until the temp array is empty
}
// print out the content of the sorted array
for (int i = 0; i <= (sorted.length - 1); i++) {
System.out.println("Index " + i + ": " + sorted[i]);
}
//return the sorted array
return sorted;
}
//find the smallest number in an int array and return it's value
private static int findSmall(int[] input) {
int smallest = input[0];
for (int i = 0; i <= (input.length - 1); i++) {
if (smallest > input[i]) {
smallest = input[i];
}
}
return smallest;
}
//find the biggest value in an int array and return it's value
private static int findBig(int[] input) {
int biggest = input[0];
for (int i = 0; i <= (input.length - 1); i++) {
if (biggest < input[i]) {
biggest = input[i];
}
}
return biggest;
}
//remove an element from an int array, based on it's value
private static int[] removeElement(int[] input, int elementValue) {
//create a temp array of size input - 1, because there will be one less element
int[] temp = new int[input.length - 1];
//create variable to tell which index to remove, set to 0 to start
//will change unless it is right
int indexToRemove = 0;
//find out what the index of the element you want to remove is
for (int i = 0; i <= (input.length - 1); i++) {
if (input[i] == elementValue) {
//assign the value to
indexToRemove = i;
break;
}
}
//variable that says if we've hit the index we want to remove
boolean removeFound = false;
for (int i = 0; i <= (input.length - 1); i++) {
//check if we are at the index we want to remove
if (indexToRemove == i) {
//if we are say so
removeFound = true;
}
//done if we aren't at the index we want to remove
if (i != indexToRemove && removeFound == false) {
//copy input to temp as normal
temp[i] = input[i];
}
//done if we've hit the index we want to remove
if (i != indexToRemove && removeFound == true) {
//note the -1, as we've skipped one and need the to decrement
//note input isn't decremented, as we need the value as normal
//note we skipped the element we wanted to delete
temp[i - 1] = input[i];
}
}
//return the modified array that doesn't contain the element we removed
//and it is 1 index smaller than the input array
return temp;
}
}
Also, I'd place all of these methods into a class Sort, but I wrote it in this way to mimic the way you wrote your code to a certain extent. This would require you to create a getSorted method, and I'd also change the sort method to a constructor if it was placed in a class Sort.

I have written an algorithm to solve your this problem. Using divide and conquer we can solve this problem effectively. Comparing each value to every one the smallest and the largest value can be found. After cutting off 2 values the first one(smallest) and the last one (largest) the new unsorted array will be processed with the same algorithm to find the smallest and largest value.
You can see my algorithm in [GitHub] (https://github.com/jabedhossain/SortingProblem/)
Although its written in C++, the comments should be enough to lead you through.

Find the largest sum including at most two consecutive elements from an array

I've been playing around a bit with the algorithms for getting the largest sum with no two adjacent elements in an array but I was thinking:
If we have an array with n elements and we want to find the largest sum so that 3 elements never touch. That's to say if we have the array a = [2, 5, 3, 7, 8, 1] we can pick 2 and 5 but not 2, 5 and 3 because then we have 3 in a row. The larget sum with these rules for this array would be: 22 (2 and 5, 7 and 8. 2+5+7+8=22)
I'm not sure how I would implement this, any ideas?
Edit:
I've only come so far as to think about what might be good to do:
Let's just stick to the same array:
int[] a = {2, 5, 3, 7, 8, 1};
int{} b = new int[n}; //an array to store results in
int n = a.length;
// base case
b[1] = a[1];
// go through each element:
for(int i = 1; i < n; i++)
{
/* find each possible way of going to the next element
use Math.max to take the "better" option to store in the array b*/
}
return b[n]; // return the last (biggest) element.
This is just a thought I got in my head, hasn't reached longer than this.

Algorithm for Maximum sum such that no two elements are adjacent:
Loop for all elements in arr[] and maintain two sums incl and excl where incl = Max sum including the previous element and excl = Max sum excluding the previous element.
Max sum excluding the current element will be max(incl, excl) and max sum including the current element will be excl + current element (Note that only excl is considered because elements cannot be adjacent).
At the end of the loop return max of incl and excl.
Implementation:
#include<stdio.h>
/*Function to return max sum such that no two elements
are adjacent */
int FindMaxSum(int arr[], int n)
{
int incl = arr[0];
int excl = 0;
int excl_new;
int i;
for (i = 1; i < n; i++)
{
/* current max excluding i */
excl_new = (incl > excl)? incl: excl;
/* current max including i */
incl = excl + arr[i];
excl = excl_new;
}
/* return max of incl and excl */
return ((incl > excl)? incl : excl);
}
/* Driver program to test above function */
int main()
{
int arr[] = {5, 5, 10, 100, 10, 5};
printf("%d \n", FindMaxSum(arr, 6));
getchar();
return 0;
}
Time Complexity: O(n)
Space Complexity: O(1)
Edit 1:
If you understand the above code, we can easily do this problem by maintaining the count of already adjacent numbers for previous position.
Here is a working implementation to the required question
//We could assume we store optimal result upto i in array sum
//but we need only sum[i-3] to sum[i-1] to calculate sum[i]
//so in this code, I have instead maintained 3 ints
//So that space complexity to O(1) remains
#include<stdio.h>
int max(int a,int b)
{
if(a>b)
return 1;
else
return 0;
}
/*Function to return max sum such that no three elements
are adjacent */
int FindMaxSum(int arr[], int n)
{
int a1 = arr[0]+arr[1];//equivalent to sum[i-1]
int a2 =arr[0];//equivalent to sum[i-2]
int a3 = 0;//equivalent to sum [i-3]
int count=2;
int crr = 0;//current maximum, equivalent to sum[i]
int i;
int temp;
for (i = 2; i < n; i++)
{
if(count==2)//two elements were consecutive for sum[i-1]
{
temp=max(a2+arr[i],a1);
if(temp==1)
{
crr= a2+arr[i];
count = 1;
}
else
{
crr=a1;
count = 0;
}
//below is the case if we sould have rejected arr[i-2]
// to include arr[i-1],arr[i]
if(crr<(a3+arr[i-1]+arr[i]))
{
count=2;
crr=a3+arr[i-1]+arr[i];
}
}
else//case when we have count<2, obviously add the number
{
crr=a1+arr[i];
count++;
}
a3=a2;
a2=a1;
a1=crr;
}
return crr;
}
/* Driver program to test above function */
int main()
{
int arr[] = {2, 5, 3, 7, 8, 1};
printf("%d \n", FindMaxSum(arr, 6));
return 0;
}
Time Complexity: O(n)
Space Complexity: O(1)

adi's solution can be easily generalized to allow up to n adjacent elements to be included in the sum. The trick is to maintain an array of n + 1 elements, where the k-th element in the array (0 ≤ k ≤ n) gives the maximum sum assuming that the k previous inputs are included in the sum and the k+1-th isn't:
/**
* Find maximum sum of elements in the input array, with at most n adjacent
* elements included in the sum.
*/
public static int maxSum (int input[], int n) {
int sums[] = new int[n+1]; // new int[] fills the array with zeros
int max = 0;
for (int x: input) {
int newMax = max;
// update sums[k] for k > 0 by adding x to the old sums[k-1]
// (loop from top down to avoid overwriting sums[k-1] too soon)
for (int k = n; k > 0; k--) {
sums[k] = sums[k-1] + x;
if (sums[k] > newMax) newMax = sums[k];
}
sums[0] = max; // update sums[0] to best sum possible if x is excluded
max = newMax; // update maximum sum possible so far
}
return max;
}
Like adi's solution, this one also runs in linear time (to be exact, O(mn), where m is the length of the input and n is the maximum number of adjacent elements allowed in the sum) and uses a constant amount of memory independent of the input length (O(n)). In fact, it could even be easily modified to process input streams whose length is not known in advance.

I would imagine putting the array into a binary tree in that order. That way you can keep track of which element is next to each other. Then just simply do an if (node is not directly linked to each other) to sum the nodes which are not next to each other. You can potentially do it with recursion and return the maximum number, makes things easier to code. Hope it helps.

For a set with n entries, there are 2^n ways to partition it. So to generate all possible sets, just loop from 0:2^n-1 and pick the elements from the array with those entries set to 1 (bear with me; I'm getting to your question):
max = 0;
for (i = 0; i < 1<<n; ++i) {
sum = 0;
for (j = 0; j < n; ++j) {
if (i & (1<<j)) { sum += array[j]; }
}
if (sum > max) { /* store max and store i */ }
}
This will find the maximum way to sum the entries of an array. Now, the issue you want is that you don't want to allow all values of i - specifically those that contain 3 consecutive 1's. This can be done by testing if the number 7 (b111) is available at any bit-shift:
for (i = 0; i < 1<<n; ++i) {
for (j = 0; j < n-2; ++j) {
if ((i & (7 << j)) == (7 << j)) { /* skip this i */ }
}
...