Author: root

Hello! In this article, we will solve coding test problems using C# and explore the importance and application of debugging. We will examine how debugging skills can be helpful through specific cases while solving actual problems.

Problem Description

"babad"

"bab" or "aba"

Problem Solving Process

Now, we will look at the approach to solve this problem step by step.

Step 1: Understanding the Problem

The key point of the problem is to check for palindromes in the given string. A palindrome is a string that reads the same forwards and backwards. For example, “racecar” is such an example. We need to generate all possible substrings from the given string and check each substring to see if it is a palindrome.

Step 2: Algorithm Design

To find the longest palindromic substring, we designed the following algorithm:

1. Generate all substrings of the given string.
2. Check if each substring is a palindrome.
3. If it is a palindrome, compare the length of that substring and keep the longest one.

Step 3: C# Code Implementation

Now, let’s implement the C# code according to each step.

using System;

public class LongestPalindromicSubstring
{
    public string GetLongestPalindrome(string s)
    {
        if (string.IsNullOrEmpty(s)) return "";

        string longestPalindrome = "";

        for (int i = 0; i < s.Length; i++)
        {
            // Check for odd-length palindromes
            string oddPalindrome = ExpandFromCenter(s, i, i);
            if (oddPalindrome.Length > longestPalindrome.Length)
            {
                longestPalindrome = oddPalindrome;
            }

            // Check for even-length palindromes
            string evenPalindrome = ExpandFromCenter(s, i, i + 1);
            if (evenPalindrome.Length > longestPalindrome.Length)
            {
                longestPalindrome = evenPalindrome;
            }
        }

        return longestPalindrome;
    }

    private string ExpandFromCenter(string s, int left, int right)
    {
        while (left >= 0 && right < s.Length && s[left] == s[right])
        {
            left--;
            right++;
        }
        return s.Substring(left + 1, right - left - 1);
    }
}

Step 4: Debugging and Testing

Now it’s time to test the implemented code and debug for any errors.

1. After running the code, input various cases to check if the results match the expectations.
2. In particular, test complex strings that include whitespace characters, numbers, and special characters to ensure palindromic checking works well.

Example Test Cases

LongestPalindromicSubstring lps = new LongestPalindromicSubstring();
Console.WriteLine(lps.GetLongestPalindrome("babad")); // bab or aba
Console.WriteLine(lps.GetLongestPalindrome("cbbd")); // bb
Console.WriteLine(lps.GetLongestPalindrome("a")); // a
Console.WriteLine(lps.GetLongestPalindrome("ac")); // a
Console.WriteLine(lps.GetLongestPalindrome("racecar")); // racecar

Debugging Tips

When debugging, keep the following points in mind:

• Carefully check variable values and use breakpoints to run the code if necessary.
• Compare expected values and actual values at each step to identify where errors occur.
• Break the code into small pieces and independently test each function to ensure they work properly.

Conclusion

In this article, we explored algorithm design and debugging processes through a palindromic problem utilizing C#. Debugging is a crucial step in solving problems, and it is a process that must be repeated to ensure that the program operates as expected. Take your time reviewing each step and do not hesitate to seek help when necessary.

Additional Learning Resources

Finally, you can refer to the following resources for deeper learning:

• Official C# Documentation
• LeetCode – Algorithm Problems
• GeeksforGeeks – Various Algorithm Resources

Coding tests are a mandatory procedure in modern IT companies. Many applicants are preparing to be evaluated on their understanding of algorithms and data structures, and their ability to solve problems based on this knowledge. In this article, we will take a closer look at how to solve algorithm problems using C#.

Problem: Valid Parentheses String

This is a problem of determining whether a given string is a valid parentheses string. The string is composed only of the characters ‘(‘, ‘)’, ‘{‘, ‘}’, ‘[‘ and ‘]’. A valid parentheses string must satisfy the following conditions:

• All opened parentheses must be closed by closed parentheses.
• A closed parenthesis must always correspond to the most recent opened parenthesis.
• The closing of parentheses should not occur before their opening.

For example, the string “{[()]}” is a valid parentheses string, while “{[(])}” is not valid.

Problem Solving Process

1. Problem Analysis

To solve this problem, we can use a stack data structure. Since the stack operates in a Last In First Out (LIFO) manner, we can add opened parentheses to the stack and, upon encountering a closed parenthesis, remove the most recently opened parenthesis from the stack. If the stack is empty after checking all parentheses, then it is a valid parentheses string.

2. Algorithm Design

The algorithm to solve this problem is as follows:

1. Define the pairs of parentheses: { '(': ')', '{': '}', '[': ']' }
2. Traverse the string and add opened parentheses to the stack.
3. Upon encountering a closed parenthesis, check if it matches with the most recent opened parenthesis from the stack.
4. If the stack is not empty or the pairs do not match, consider it an invalid string.
5. After exploring the entire string, if the stack is empty, then it is a valid string.

3. C# Code Implementation

using System;
using System.Collections.Generic;

public class ValidParentheses
{
    public static bool IsValid(string s)
    {
        Stack stack = new Stack();
        Dictionary parentheses = new Dictionary()
        {
            {'(', ')'},
            {'{', '}'},
            {'[', ']'}
        };

        foreach (char c in s)
        {
            // If it's an opened parenthesis, add it to the stack
            if (parentheses.ContainsKey(c))
            {
                stack.Push(c);
            }
            else
            {
                // If it's a closed parenthesis and the stack is empty, validation fails
                if (stack.Count == 0 || parentheses[stack.Pop()] != c)
                {
                    return false;
                }
            }
        }

        // If the stack is empty, it's a valid parentheses string
        return stack.Count == 0;
    }
}

class Program
{
    static void Main()
    {
        string input = "{[()]}";
        bool result = ValidParentheses.IsValid(input);
        Console.WriteLine($"\"{input}\" is it a valid parentheses string? {result}");
    }
}
    

4. Algorithm Analysis

The above code uses a stack to traverse the string once, resulting in a time complexity of O(n), where n is the length of the string. The space complexity is also O(n) because up to n opened parentheses can be stored on the stack. This algorithm can operate efficiently even as the input string length increases.

Conclusion

In this article, we explored how to solve the valid parentheses string problem using C#. When solving algorithm problems, it is important to analyze the problem well and choose the appropriate data structures. Utilizing simple data structures like stacks can help efficiently solve complex problems. I hope this helps in developing algorithmic thinking through a variety of problems.

Problem Description

There is a tank that can hold water in a specific area. Each wall of the tank has a different height. When it rains, water will accumulate, and the problem is to determine how much water can be held between each wall.

Input

The first line contains an integer N (1 ≤ N ≤ 100,000). N represents the number of walls.
The second line contains N integers h_i (1 ≤ h_i ≤ 1,000,000), which represent the height of each wall.

Output

Print the amount of water that can be held on one line.

Example Problem

Problem Solving Process

To solve this problem, we will use two arrays. One will store the maximum height of walls to the left of the current position, and the other will store the maximum height of walls to the right.

1. Problem Analysis

The amount of water that can be held at each position is the difference between the minimum of the maximum heights of the walls on the left and right, and the current wall height.
For example, the amount of water at position i can be calculated as follows:
water[i] = max(0, min(left_max[i], right_max[i]) - height[i])
where left_max represents the maximum height of walls to the left of i, and right_max represents the maximum height of walls to the right.

2. Algorithm Design

We can design the algorithm in the following steps:

1. Receive the input.
2. Create an array left_max to store the maximum heights of the left walls.
3. Create an array right_max to store the maximum heights of the right walls.
4. Calculate the amount of water that can be held at each position.
5. Finally, output the total amount of water.

3. Code Implementation

Below is the code that implements the above algorithm in C#.

using System;

class Program
{
    static void Main(string[] args)
    {
        int N = int.Parse(Console.ReadLine());
        int[] height = Array.ConvertAll(Console.ReadLine().Split(), int.Parse);

        // Left maximum height array
        int[] left_max = new int[N];
        left_max[0] = height[0];

        for (int i = 1; i < N; i++)
        {
            left_max[i] = Math.Max(left_max[i - 1], height[i]);
        }

        // Right maximum height array
        int[] right_max = new int[N];
        right_max[N - 1] = height[N - 1];

        for (int i = N - 2; i >= 0; i--)
        {
            right_max[i] = Math.Max(right_max[i + 1], height[i]);
        }

        // Calculate the amount of water
        int water = 0;
        for (int i = 0; i < N; i++)
        {
            water += Math.Max(0, Math.Min(left_max[i], right_max[i]) - height[i]);
        }

        Console.WriteLine(water);
    }
}
    

4. Code Explanation

The algorithm used in the above C# code is as follows:

• int N = int.Parse(Console.ReadLine());
  – Takes the input for N and stores the number of walls.
• int[] height = Array.ConvertAll(Console.ReadLine().Split(), int.Parse);
  – Takes the height input and converts it into an array.
• left_max array stores the maximum height from the left. To do this, after setting the height of the first wall, a loop is run to compare the height of each wall and store the maximum value.
• right_max array does the same to store the maximum height from the right.
• Finally, the amount of water that can be held at each wall position is calculated to find the total amount of water.

5. Complexity Analysis

The time complexity of this algorithm is O(N). It performs operations proportional to the number of walls N, so it operates efficiently within the provided input range. The space complexity is also O(N) as it needs space to store the two arrays.

Conclusion

In this article, we solved the problem of calculating the amount of water using C#. Through the process of designing and implementing the algorithm step by step, we were able to confirm problem types that are frequently encountered in coding tests.
I hope this lecture helps you in your preparation for coding tests.