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This approach involves solving the problem using an iterative method, where we use loops to perform the necessary calculations. This can be more efficient in terms of space complexity, especially if recursion would lead to excessive function call overhead.
Time Complexity: O(n), where n is the number of elements.
Space Complexity: O(1) since we are not using any extra space proportional to the input size.
1function solveProblem(n) {
2 for (let i = 0; i < n; i++) {
3 // Solution logic here
4 process.stdout.write(i + ' ');
5 }
6}
7
8const n = 10;
9solveProblem(n);JavaScript uses a simple for loop with process.stdout.write to print the result without newline, iterating through the required number of elements.
This approach explores solving the problem through recursion, which can offer simplicity and expressiveness. However, care must be taken with recursion depth to avoid stack overflow.
Time Complexity: O(n)
Space Complexity: O(n) due to the call stack.
1#include <iostream>
2using namespace std;
void solveProblem(int n, int i) {
if (i >= n) return;
// Solution logic here
cout << i << " ";
solveProblem(n, i + 1);
}
int main() {
int n = 10;
solveProblem(n, 0);
return 0;
}The recursive approach in C++ is similar to C, using a function that calls itself with incremented parameters, with results printed via std::cout.