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The first approach involves using an iterative method to solve the problem. This generally involves using loops to traverse and manage the input data while making use of auxiliary data structures to optimize the solution.
Time Complexity: O(n), where n is the number of elements in the array.
Space Complexity: O(1), as it uses constant space.
1def iterative_solution(arr):
2 for i in arr:
3 print(i, end=' ')The Python implementation uses a simple loop to iterate over the list and print each element. Modify the loop body to adjust the functionality as needed.
The second approach uses recursion to solve the given problem, which can simplify problems with a clear recursive structure. This involves a base case and a recursive call that processes a subset of the data.
Time Complexity: O(n), due to n recursive calls.
Space Complexity: O(n), for the recursion call stack.
1void recursiveSolution(std::vector<int>& arr, int index) {
if (index < arr.size()) {
std::cout << arr[index] << " ";
recursiveSolution(arr, index + 1);
}
}This C++ recursive function processes each element of a vector and prints it. It terminates once the index equals the vector size.