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This approach involves checking all possible combinations or permutations to find the solution. Although it's straightforward and easy to implement, it may not be the most efficient way due to its high time complexity.
Time Complexity: O(n^2) - where n is the size of the input.
Space Complexity: O(1) - constant space usage as no additional data structures are used.
1#include <stdio.h>
2
3void solve() {
4 // Your brute-force logic here
5 printf("Solution not implemented yet\n");
6}
7
8int main() {
9 solve();
10 return 0;
11}This C program sets up a framework for a brute-force solution. Currently, the logic is not implemented, but the structure is in place to solve the problem by iterating over possible solutions.
This approach uses a hash map to store intermediate results or counts, allowing for quicker lookup and more efficient processing, reducing the time complexity compared to the brute-force method.
Time Complexity: O(n) - linear time if hash lookups are constant time.
Space Complexity: O(n) - due to storage in the hash map.
1using System.Collections.Generic;
class Program {
static void Main() {
solve();
}
static void solve() {
// Implement optimized logic with hash map technique
Console.WriteLine("Solution not implemented yet");
}
}The C# code structure here encourages using Dictionary for optimizing solution efficiency beyond brute-force.