Taken from Introduction to Algorithms
Describe a Θ(n lg n)-time algorithm that, given a set S of n integers and another integer x, determines whet
Here's is an alternate solution, by adding few more conditions into mergesort.
public static void divide(int array[], int start, int end, int sum) {
if (array.length < 2 || (start >= end)) {
return;
}
int mid = (start + end) >> 1; //[p+r/2]
//divide
if (start < end) {
divide(array, start, mid, sum);
divide(array, mid + 1, end, sum);
checkSum(array, start, mid, end, sum);
}
}
private static void checkSum(int[] array, int str, int mid, int end, int sum) {
int lsize = mid - str + 1;
int rsize = end - mid;
int[] l = new int[lsize]; //init
int[] r = new int[rsize]; //init
//copy L
for (int i = str; i <= mid; ++i) {
l[i-str] = array[i];
}
//copy R
for (int j = mid + 1; j <= end; ++j) {
r[j - mid - 1] = array[j];
}
//SORT MERGE
int i = 0, j = 0, k=str;
while ((i < l.length) && (j < r.length) && (k <= end)) {
//sum-x-in-Set modification
if(sum == l[i] + r[j]){
System.out.println("THE SUM CAN BE OBTAINED with the values" + l[i] + " " + r[j]);
}
if (l[i] < r[j]) {
array[k++] = l[i++];
} else {
array[k++] = r[j++];
}
}
//left over
while (i < l.length && k <= end) {
array[k++] = l[i++];
//sum-x-in-Set modification
for(int x=i+1; x < l.length; ++x){
if(sum == l[i] + l[x]){
System.out.println("THE SUM CAN BE OBTAINED with the values" + l[i] + " " + l[x]);
}
}
}
while (j < r.length && k <= end) {
array[k++] = r[j++];
//sum-x-in-Set modification
for(int x=j+1; x < r.length; ++x){
if(sum == r[j] + r[x]){
System.out.println("THE SUM CAN BE OBTAINED with the values" + r[j] + " " + r[x]);
}
}
}
}
But the complexity of this algorithm is still not equal to THETA(nlogn)