"#include
// Naive method to find a pair in an array with a given sum
void findPair(int nums[], int n, int target)
{
// consider each element except the last
for (int i = 0; i < n - 1; i++)
{
// start from the i'th element until the last element
for (int j = i + 1; j < n; j++)
{
// if the desired sum is found, print it
if (nums[i] + nums[j] == target)
{
printf("Pair found (%d, %d)\n", nums[i], nums[j]);
return;
}
}
}
// we reach here if the pair is not found
printf("Pair not found");
}
"
Gundala tarun,cse2020 V. - "#include
// Naive method to find a pair in an array with a given sum
void findPair(int nums[], int n, int target)
{
// consider each element except the last
for (int i = 0; i < n - 1; i++)
{
// start from the i'th element until the last element
for (int j = i + 1; j < n; j++)
{
// if the desired sum is found, print it
if (nums[i] + nums[j] == target)
{
printf("Pair found (%d, %d)\n", nums[i], nums[j]);
return;
}
}
}
// we reach here if the pair is not found
printf("Pair not found");
}
"See full answer
"Construct a min-heap either inplace, or by making a copy of the array and then applying heapify on that copy. This is done in O(n) time.
Maintain two zero-initialised variables - sum and count.
Keep popping off the heap while sum < k, and update count.
In the worst case you will have to do n pops, and each pop is O(log n), so the algorithm would take O(n log n) in total. Space complexity depends on whether you're allowed to modify inplace or not, so either O(1) or O(n) respectively."
Anonymous Wolf - "Construct a min-heap either inplace, or by making a copy of the array and then applying heapify on that copy. This is done in O(n) time.
Maintain two zero-initialised variables - sum and count.
Keep popping off the heap while sum < k, and update count.
In the worst case you will have to do n pops, and each pop is O(log n), so the algorithm would take O(n log n) in total. Space complexity depends on whether you're allowed to modify inplace or not, so either O(1) or O(n) respectively."See full answer
"function isPalindrome(s, start, end) {
while (s[start] === s[end] && end >= start) {
start++;
end--;
}
return end <= start;
}
function longestPalindromicSubstring(s) {
let longestPalindrome = '';
for (let i=0; i < s.length; i++) {
let j = s.length-1;
while (s[i] !== s[j] && i <= j) {
j--;
}
if (s[i] === s[j]) {
if (isPalindrome(s, i, j)) {
const validPalindrome = s.substring(i, j+1"
Tiago R. - "function isPalindrome(s, start, end) {
while (s[start] === s[end] && end >= start) {
start++;
end--;
}
return end <= start;
}
function longestPalindromicSubstring(s) {
let longestPalindrome = '';
for (let i=0; i < s.length; i++) {
let j = s.length-1;
while (s[i] !== s[j] && i <= j) {
j--;
}
if (s[i] === s[j]) {
if (isPalindrome(s, i, j)) {
const validPalindrome = s.substring(i, j+1"See full answer