C++ Coding Test Course, What Algorithm Should Be Used to Solve It?

Introduction

Coding tests play an important role in modern software engineering. Many companies conduct coding tests to assess job candidates’ algorithmic problem-solving skills, and in this process, the C++ language has gained popularity due to its efficiency and various features. This post provides a guide on what algorithms to use through algorithm problems using C++.

Problem Description

Here is the algorithm problem we will solve. Let’s take the Two Sum problem as an example.

Problem: Two Sum

Given an integer array nums and an integer target, return the indices of the two numbers such that they add up to target. You may not use the same element twice, and you can assume that each input would have exactly one solution. 

Example:
    Input: nums = [2, 7, 11, 15], target = 9
    Output: [0, 1]
    Explanation: nums[0] + nums[1] = 2 + 7 = 9, so return [0, 1].

Problem Solving Strategy

To solve this problem, we can use several approaches:

1. Brute Force

The simplest way is to try all possible combinations. This method uses a double loop to check all possible pairs of numbers. The time complexity is O(n^2).

2. Using a Hash Map

By using a hash map to store each number as a key and its index as a value, we can execute it more efficiently. We traverse the array only once, calculating target - nums[i] for each element and check whether this value exists in the hash map. The time complexity is O(n).

3. Sorting and Binary Search

After sorting the numbers, we can use binary search, but the sorting process takes additional time, increasing the time complexity to O(n log n). Since this method is not the most efficient, we will choose the hash map approach.

Implementation

Now, let’s implement the optimal solution using a hash map in C++.


#include <iostream>
#include <vector>
#include <unordered_map>

using namespace std;

vector twoSum(vector& nums, int target) {
    unordered_map num_map; // Hash map to store numbers and their indices.
    vector result; // Vector to store results.

    for (int i = 0; i < nums.size(); i++) {
        int complement = target - nums[i]; // Calculate the required complement.
        if (num_map.find(complement) != num_map.end()) {
            result.push_back(num_map[complement]); // Add the index.
            result.push_back(i); // Add the current index.
            return result; // Return the result.
        }
        num_map[nums[i]] = i; // Add the number to the hash map.
    }
    return result; // Return an empty vector if no answer is found.
}

int main() {
    vector nums = {2, 7, 11, 15};
    int target = 9;
    vector result = twoSum(nums, target);
    
    cout << "[";
    for (int i = 0; i < result.size(); i++) {
        cout << result[i];
        if (i < result.size() - 1) cout << ", ";
    }
    cout << "]" << endl;
    return 0;
}

Code Explanation

The provided code has the following structure:

  1. Including Header Files: Necessary header files are included. iostream is for input-output streams, vector is for dynamic arrays, and unordered_map is needed for using the hash map.
  2. Function Definition: The twoSum function takes an integer array and a target value as arguments. It defines a hash map and traverses all elements of the array.
  3. Checking using Hash Map: In each iteration, it calculates the required value and updates the result if it exists in the hash map.
  4. Main Function: The main function defines the input values, calls the twoSum function, and outputs the result.

Time Complexity Analysis

The worst-case time complexity of this solution is O(n), where n is the size of the array. This is because adding and searching each element in the hash map takes an average of O(1) time. The additional space used is O(n) for the hash map.

Conclusion

Choosing the appropriate algorithm is very important when solving coding test problems in C++. In particular, analyzing the characteristics of the problem and the size of the data is crucial. In this post, we learned the optimal solution using a hash map through the Two Sum problem. This approach helps to solve many coding test problems that are straightforward yet efficient.

Additional Learning Resources

If you want to learn more advanced topics for solving algorithm problems, here are some resources to recommend:

  • GeeksforGeeks – Covers various algorithms and problem-solving techniques.
  • LeetCode – Offers a variety of coding test problems and topics.
  • HackerRank – A platform to learn by solving various types of algorithms and problems.

Final Thoughts

Learning to solve algorithm problems requires continuous effort and practice. Trying to solve various problems and finding optimal solutions will greatly help improve your skills. Based on a deep understanding of C++ and algorithms, I wish you success in your coding tests!