Swift Coding Test Course, Cocktail Making

In this post, we will discuss how to solve algorithm problems using the Swift language. The topic of the problem is ‘Making Cocktails’.

Problem Description

You are a bartender working at a cocktail bar. There are various ingredients, and customers want cocktails with specific flavors. You need to find the optimal combination of cocktails that satisfies the customers’ requests using the given ingredients.

The desired flavors are defined in terms of a certain level of sweetness, bitterness, and sourness. Each ingredient has specific levels of these flavors, and you can provide the cocktail if it meets the required flavor levels set by the customer.

Based on the given list of ingredients and the customer’s requirements, find and display the combinations that satisfy the customer’s flavor preferences among all possible combinations.

Input Format

The first line contains the number of ingredients N (1 ≤ N ≤ 100). The next N lines provide the sweetness, bitterness, and sourness levels of each ingredient. The last line gives the minimum required levels of sweetness, bitterness, and sourness desired by the customer.

Each flavor level is between 1 and 100 inclusive.

Output Format

Output the combinations of ingredients that meet the customer’s requirements. Only print combinations where the flavor levels satisfy the customer’s requirements. Print all possible combinations, the count of combinations, and the flavor values of each combination.

Example

Input:

3
3 4 2
2 1 5
5 2 1
4 5 3
            

Output:

1: 5 4 5
2: 3 4 5
            

Problem Solving Process

To solve the problem, we follow these steps.

1. Understanding the Problem

Read the problem and clearly identify the requirements. The main focus is to find ingredient combinations that satisfy the flavor levels requested by the customer.

2. Handling Input Values

Process the number of ingredients and their respective flavor levels from the input and store them in a data structure such as an array or list.

3. Generating Combinations

Generate combinations of the given ingredients. You can use backtracking or bit masking techniques for this purpose. Generate all combinations and calculate the flavor levels for each combination.

4. Checking Customer Requirements

Check if each generated combination meets the customer’s requirements. Verify that each flavor level is above or equal to the minimum required levels set by the customer.

5. Outputting the Final Results

Output all combinations that meet the customer’s requirements. The output format should comply with the requirements.

Swift Code Implementation

Below is an example of how to implement the above algorithm in the Swift language.

import Foundation

func findCocktailCombinations(ingredients: [(Int, Int, Int)], target: (Int, Int, Int)) -> [[Int]] {
    var result = [[Int]]()
    let n = ingredients.count
    let totalCombinations = 1 << n

    for i in 1..= target.0 && bitter >= target.1 && sour >= target.2 {
            result.append(currentCombination)
        }
    }
    return result
}

// Input receiving
let ingredientCount = Int(readLine()!)!
var ingredients: [(Int, Int, Int)] = []
for _ in 0..

Conclusion

This post detailed the process of solving a Swift algorithm problem. We learned how to generate all cocktail combinations that meet the customer's requirements by using combination generation and condition-checking methods. Keep in mind how crucial problem understanding and approach are when taking coding tests. Continuous practice and pursuing efficient problem-solving strategies are essential.

Swift Coding Test Course, Card Sorting

Problem

You need to sort specific cards. Each card may contain numbers and letters. Sort the given cards according to the following rules:

  • Letter cards must come before number cards.
  • For letter cards, sort them in alphabetical order.
  • For number cards, sort them in ascending order.

For example, if the given cards are ["A", "3", "B", "1", "2"], the result will be ["A", "B", "1", "2", "3"].

Solution Process

Step 1: Understanding the Problem

This problem involves separating the cards into letter cards and number cards and sorting them. You need to apply specific rules according to the requirements of the problem.

Step 2: Choosing a Data Structure

In Swift, you can use an array to store and manipulate the cards. Work based on the array provided as input.

Step 3: Setting Sorting Criteria

After separating letter cards and number cards, you need to define how to sort each of them. This will allow you to achieve the final result.

Step 4: Writing Swift Code

            
            import Foundation

            func sortCards(cards: [String]) -> [String] {
                var letters: [String] = []
                var numbers: [Int] = []

                // Separate cards
                for card in cards {
                    if let number = Int(card) {
                        numbers.append(number)
                    } else {
                        letters.append(card)
                    }
                }

                // Sort
                letters.sort()
                numbers.sort()

                // Combine results
                let sortedNumbers = numbers.map { String($0) }
                return letters + sortedNumbers
            }

            // Example
            let cards = ["A", "3", "B", "1", "2"]
            let sortedCards = sortCards(cards: cards)
            print(sortedCards) // ["A", "B", "1", "2", "3"]
            
        

Step 5: Analyzing Time Complexity

The time complexity of this algorithm is O(n log n). This is because both string sorting and number sorting have a time complexity of O(n log n). If we let n be the number of cards, in the worst case, up to n cards may be given, ensuring sufficient performance.

Step 6: Conclusion

This problem allows you to learn about basic array handling and sorting techniques in Swift. Additionally, understanding how to handle strings and numbers is important. Practicing problems like this can help you in coding interviews.

Additional Learning Resources

This appendix was created to help understand Swift coding tests. It is recommended to practice various algorithm problems to improve your skills.

Swift Coding Test Course, Card Game

In this course, we will tackle an algorithm problem to implement a card game using Swift. Through this problem, you can enhance your understanding of Swift and learn about approaches to algorithm problems.

Problem Description

In the card game, two players start with N cards each. Each player draws one card at a time to compare, and the player with the higher-numbered card takes both cards. Your task is to calculate the total sum of the cards taken by Player 1 at the end.

Input

  • The first line contains the number of cards N for Player 1 (1 ≤ N ≤ 1000).
  • The second line contains the N cards of Player 1, separated by spaces.
  • The third line contains the N cards of Player 2, separated by spaces.

Output

Output the total sum of the cards taken by Player 1.

Example Problem

Input

3
3 5 6
2 4 3

Output

14

Solution Process

To solve the problem, we first need to compare the cards of Player 1 and Player 2 to determine who wins each round. If Player 1 wins, they take both players’ cards. Here is a step-by-step approach to solving the problem.

Step 1: Handling Input

let n = Int(readLine()!)!
let player1Cards = readLine()!.split(separator: " ").map { Int($0)! }
let player2Cards = readLine()!.split(separator: " ").map { Int($0)! }

The code above processes the number of cards and the cards for Player 1 and Player 2. First, it receives the number of cards N, then stores each player’s cards in an array.

Step 2: Comparing Cards and Calculating Scores

To compare the cards, we use a for loop to check each pair of cards from both players. For each turn, if Player 1’s card is larger, we add the values of both cards to Player 1’s score; if Player 2’s card is larger, no value is added.

var player1Score = 0

for i in 0.. player2Cards[i] {
        player1Score += player1Cards[i] + player2Cards[i]
    }
}

Step 3: Outputting the Result

After comparing all the cards, we output Player 1’s total score.

print(player1Score)

Complete Code

let n = Int(readLine()!)!
let player1Cards = readLine()!.split(separator: " ").map { Int($0)! }
let player2Cards = readLine()!.split(separator: " ").map { Int($0)! }

var player1Score = 0

for i in 0.. player2Cards[i] {
        player1Score += player1Cards[i] + player2Cards[i]
    }
}

print(player1Score)

Considerations

This problem can be simply solved by iterating through the array and performing the necessary calculations, resulting in a time complexity of O(N). Of course, the way cards are added and the rules for winning may vary depending on the game’s rules, but the basic structure will be similar.

Conclusion

In this course, we solved a card game problem using Swift. Well-defined game rules and designing the appropriate algorithm are very useful practice for actual coding tests. Other algorithm problems can also be approached similarly, so I encourage you to practice and tackle various problems!

Swift Coding Test Course, Understanding Friend Relationships

Problem Description

This problem is related to graphs, which often appear in coding tests, and it will focus on understanding friendships.
Friendships can be represented as ‘bidirectional edges’, and in this problem, we will implement an algorithm to output
the friends of a specific friend based on given friendships.

Problem

Problem Description: There are N friends. Each friend considers each other a friend, and the friendships
are given in pairs. Given these friendships, write a program that outputs the friend list of a specific friend.
However, duplicate friends should be excluded.

Input Format:
– The first line contains two integers N (1 ≤ N ≤ 100) and M (1 ≤ M ≤ 1000).
– The next M lines consist of two integers A and B that represent the friendships.
– A and B are the numbers denoting friends, and A ≠ B always holds.

Output Format:
– Output the friend list of a specific friend K (1 ≤ K ≤ N) separated by spaces.

Example Input

5 5
1 2
1 3
2 4
3 4
4 5
3

Example Output

2 4

Problem Solving Process

Step 1: Understanding the Problem

To understand the problem, let’s think about how we can represent the given friendships.
Friendships can be represented as a graph, where ‘friends’ are ‘nodes’ and friendships are ‘edges’.
This allows us to easily find each friend’s friend list.

Step 2: Choosing a Data Structure

An ‘adjacency list’ is appropriate for representing friendships.
We can use a dictionary or an array to store each friend’s friend list.
In this problem, we will use an array with friend numbers as indices.

Step 3: Implementation

Now, let’s implement the code in Swift to solve the problem.
First, we will take the input and build an adjacency list to represent friendships, then write a program
that outputs the friend list of a specific friend K.


import Foundation

func main() {
    // Input
    let firstLine = readLine()!.split(separator: " ").map { Int($0)! }
    let N = firstLine[0] // Number of friends
    let M = firstLine[1] // Number of friendships
    
    // Array to store friendships (adjacency list)
    var friends = [[Int]](repeating: [], count: N + 1)
    
    // Input friendships
    for _ in 0..

Step 4: Code Explanation

The code can be divided into three main parts. The explanations for each section are as follows.

  • Input and Initialization:

    • First, the number of friends N and the number of friendships M are read in from the first line.
    • Next, an empty array of size N+1 is created to store each friend's friend list.
  • Input Friendships:

    • The friendships are read from the next M lines and stored in the adjacency list to maintain bidirectional relationships.
  • Output Friend List of K:

    • The friend list of a specific friend K is sorted and printed, separated by spaces.

Step 5: Testing the Code

Various input cases should be considered to test the written code.
For example, let's try the following test case:

Example Input 1

5 5
1 2
1 3
2 4
3 4
4 5
3

Example Output 1

2 4

Example Input 2

4 4
1 2
2 3
3 4
4 1
1

Example Output 2

2 4

Example Input 3

4 4
1 2
3 4
2 3
1 4
2

Example Output 3

1 3

Conclusion

In this tutorial, we implemented an algorithm to understand friendships and output the
friend list of a specific friend using Swift.
Graph problems have various applications, so it's essential to practice thoroughly to enhance
understanding of algorithms.

We hope you continue to improve your skills by solving more problems.

Swift Coding Test Course, Finding the Longest Common Subsequence

Hello! In this blog post, we will take a deep dive into how to solve the Longest Common Subsequence (LCS) problem using the Swift programming language. The LCS problem involves finding the longest subsequence that appears in both of two strings. This can be solved through various algorithms and dynamic programming. In this article, I will guide you through understanding the problem and implementing the algorithm in detail.

1. Understanding the Problem

The Longest Common Subsequence (LCS) problem is to find the longest subsequence that is common to both sequences while maintaining the original order. For example, given the two strings “ABCBDAB” and “BDCAB”, their LCS is “BDAB”, and its length is 4.

2. Problem Description

Let’s write a function to determine the length of the LCS for the given two strings S1 and S2. Let’s assume the two strings are defined as follows:

S1 = "ABCBDAB"
S2 = "BDCAB"

Now, let’s explore a general approach to find the LCS.

3. Problem-Solving Methodology

The most well-known method to solve the LCS problem is Dynamic Programming. This approach involves breaking the problem down into subproblems, solving those, and reusing the results to derive a solution for the entire problem. I will explain this process step by step.

3.1 Initializing the Dynamic Programming Table

First, let’s denote the lengths of the two strings S1 and S2 as m and n, respectively. We create and initialize a 2D array (dp) of size m+1 x n+1. Each element dp[i][j] represents the length of LCS of the first i characters of S1 and the first j characters of S2. The initialization process is as follows:

for i in 0 to m: 
    dp[i][0] = 0
for j in 0 to n: 
    dp[0][j] = 0

3.2 Dynamic Programming Recurrence Relation

Now let’s define the recurrence relation to update the LCS values for each character. If the i-th character of S1 and the j-th character of S2 are the same, the length of LCS up to that character is the previous LCS length plus 1. That is:

if S1[i-1] == S2[j-1] then
    dp[i][j] = dp[i-1][j-1] + 1
else
    dp[i][j] = max(dp[i-1][j], dp[i][j-1])

This recurrence relation allows us to calculate all elements, and ultimately, we can obtain the length of LCS at dp[m][n].

4. Implementing the Swift Code

Now, based on the above process, let’s implement LCS in Swift. Below is the function that calculates the longest common subsequence.

func longestCommonSubsequence(_ S1: String, _ S2: String) -> Int {
    let s1Array = Array(S1)
    let s2Array = Array(S2)
    let m = s1Array.count
    let n = s2Array.count
    var dp = Array(repeating: Array(repeating: 0, count: n + 1), count: m + 1)

    for i in 1...m {
        for j in 1...n {
            if s1Array[i - 1] == s2Array[j - 1] {
                dp[i][j] = dp[i - 1][j - 1] + 1
            } else {
                dp[i][j] = max(dp[i - 1][j], dp[i][j - 1])
            }
        }
    }

    return dp[m][n]
}

The above function takes two strings S1 and S2 as arguments and returns the length of the longest common subsequence.

5. Test Cases

Let’s create a few test cases to test the function.

let S1 = "ABCBDAB"
let S2 = "BDCAB"
let result = longestCommonSubsequence(S1, S2)
print("The length of the longest common subsequence is \(result).") // Output: 4

Through testing, we can verify that our algorithm returns the correct results.

6. Time Complexity Analysis

The time complexity of this algorithm using dynamic programming is O(m*n), and the space complexity is also O(m*n). Here, m and n represent the lengths of the two strings. This complexity can grow rapidly as the length of the strings increases, so optimization techniques such as memoization can be applied to reduce space complexity.

7. Conclusion

In this article, we explored using dynamic programming techniques to solve the longest common subsequence problem and how to implement it in Swift. The LCS problem is widely used in computer science and plays an important role in various applications. This algorithm can be utilized in many scenarios, enhancing our ability to solve programming problems.

I hope that by continuing to solve various algorithm problems, you will find it helpful in preparing for coding tests. Thank you!