Swift Coding Test Course, Let’s try DDR

Hello, everyone! Today we will tackle an algorithm problem implemented in Swift. The topic is an algorithmic problem that arises in the ‘DDR (Dance Dance Revolution)’ game. This problem will be very useful for improving your understanding of Swift programming and algorithms. Let’s explain the problem first and then solve it together.

Problem Description

The problem is as follows:

Problem: DDR Pattern Analysis

In the DDR game, players score points by stepping on the arrows that appear on the screen. Each arrow appears at 1-second intervals, and when a pattern is given, write an algorithm to calculate how many arrows can be accurately stepped on within the given time.

The following information will be provided as input:

  • n: Total number of arrows (1 ≤ n ≤ 1000)
  • t: Given time (seconds, 1 ≤ t ≤ 100)
  • Pattern array: An array listing the activation times of each arrow (each item is 1 ≤ item ≤ t)

Write a program that calculates and outputs how many arrows can be stepped on within the given time based on the input pattern.

Example Input

5 3
1 2 3 4 5

Example Output

3

Solution Process

Now let’s approach the problem step by step. Follow the processes below to understand the solution method.

Step 1: Input Handling

First, we need to read the number of arrows, the time limit, and the activation times of the arrows given in the input. The input data will be stored in an array. For example, in Swift, you can do the following:

import Foundation

// Input handling
let input = readLine()!.split(separator: " ").map { Int($0)! }
let n = input[0]  // Total number of arrows
let t = input[1]  // Given time (seconds)
let arrows = readLine()!.split(separator: " ").map { Int($0)! } // Arrow activation times

Step 2: Understanding the Problem

The task is to find out how many arrows can be stepped on within the given time ‘t’. In other words, we need to count the number of arrows in the arrow arrangement array from 1 to t seconds.

Step 3: Sorting the Array and Validating

After receiving the input, we need to sort the arrow activation time array. This will simplify the counting based on valid time.

let sortedArrows = arrows.sorted()

Step 4: Writing the Counting Logic

Now we simply need to count the number of arrows that satisfy the conditions. The method for counting how many arrows correspond to the given time ‘t’ is very straightforward. We can increment the count each time we encounter an arrow that is less than or equal to t while traversing the array.

var count = 0
for arrow in sortedArrows {
    if arrow <= t {
        count += 1
    } else {
        break // No need to check further
    }
}

Step 5: Output the Result

After checking all the arrows, we print the count to the console.

print(count)

Complete Code

By integrating all the above steps, we can write a program as follows:

import Foundation

// Input handling
let input = readLine()!.split(separator: " ").map { Int($0)! }
let n = input[0]  // Total number of arrows
let t = input[1]  // Given time (seconds)
let arrows = readLine()!.split(separator: " ").map { Int($0)! } // Arrow activation times

// Sorting the arrows
let sortedArrows = arrows.sorted()

// Count variable
var count = 0
for arrow in sortedArrows {
    if arrow <= t {
        count += 1
    } else {
        break
    }
}

// Output the result
print(count)

Conclusion

Thus, we have solved the DDR arrow counting problem using Swift. Algorithm problems can initially seem difficult, but it is important to organize the problem well and approach it step by step. Keep practicing various problems and enhance your Swift programming skills! Thank you!

Swift Coding Test Course, Calculating ATM Withdrawal Time

Hello! In this article, we will cover a useful algorithm problem for preparing for coding tests, which is calculating the ATM withdrawal time. Through this problem, we will go step by step in solving it using arrays, sorting, and basic mathematical reasoning.

Problem Description

There are people lined up to withdraw money from an ATM. Each person knows the time (in seconds) it takes to use the ATM. Everyone will use the ATM in order of their line up. You need to write a program to calculate the total time taken for everyone to use the ATM.

In other words, when given an input like the following:

  • Input: [3, 1, 4, 3, 2]
  • Output: 32

If the first person takes 3 seconds, the second person takes 1 second, the third takes 4 seconds, and so on, the total time taken for everyone to use the ATM would be 3 + (3 + 1) + (3 + 1 + 4) + (3 + 1 + 4 + 3) + (3 + 1 + 4 + 3 + 2) = 32 seconds.

Approach to the Problem

To solve this problem, you can follow these steps:

  1. Sort the times taken in ascending order.
  2. Accumulate each person’s withdrawal time to calculate the total withdrawal time.

Implementation Steps

Step 1: Define and Sort Input

First, let’s sort the given times so that the fastest withdrawal times come first. To do this, we can use Swift’s sort() method.

let withdrawalTimes = [3, 1, 4, 3, 2]
let sortedTimes = withdrawalTimes.sorted()

Step 2: Calculate Total Time

Now, let’s use the sorted array to calculate the cumulative time based on each person’s withdrawal order.

var totalTime = 0
var accumulatedTime = 0

for time in sortedTimes {
    accumulatedTime += time
    totalTime += accumulatedTime
}

Step 3: Complete Code

Combining all the steps, the Swift program can be written as follows:

func calculateTotalWithdrawalTime(withdrawalTimes: [Int]) -> Int {
    let sortedTimes = withdrawalTimes.sorted()
    var totalTime = 0
    var accumulatedTime = 0

    for time in sortedTimes {
        accumulatedTime += time
        totalTime += accumulatedTime
    }
    
    return totalTime
}

let times = [3, 1, 4, 3, 2]
let total = calculateTotalWithdrawalTime(withdrawalTimes: times)
print("Total withdrawal time: \(total) seconds")

Code Explanation

The above code first receives a list of withdrawal times and sorts it, then uses a for loop to accumulate each user’s time and calculate the total time. Let’s take a closer look at each step.

  • calculateTotalWithdrawalTime(withdrawalTimes: [Int]) -> Int: A function that takes withdrawal times as input and returns the total time taken.
  • let sortedTimes = withdrawalTimes.sorted(): Sorts the array in ascending order using Swift’s sort feature.
  • accumulatedTime += time: Accumulates each person’s withdrawal time for calculation.
  • totalTime += accumulatedTime: Adds the accumulated time to the total time.

Results Confirmation

When the above code is executed, it will output that the total withdrawal time for the given times [3, 1, 4, 3, 2] is 32 seconds.

This method allows for sufficient testing with various inputs. For example:

let testTimes = [2, 5, 3, 1, 4]
let testTotal = calculateTotalWithdrawalTime(withdrawalTimes: testTimes)
print("Test withdrawal time: \(testTotal) seconds")

This will produce results corresponding to the test case.

Conclusion

In this article, we explored the process of solving the ATM withdrawal time calculation problem. This problem is a great example for practicing the basics of handling arrays, sorting, and calculating cumulative sums. Implementing the problem in Swift has deepened my understanding of the algorithm. It’s important to practice various problems of this level while preparing for coding tests.

I hope this has been helpful in your coding test preparations. If you have additional questions or problems, feel free to leave them in the comments!

Swift Coding Test Course, Ax + By = C

Problem Description

Problem: Write a program to check whether there exists a solution for Ax + By = C given the integers A, B, and C. You should also provide a method to find all possible solutions.

Input:

– Integers A, B, C (-(10^9) ≤ A, B, C ≤ 10^9)

Output:

– If a solution exists, print “A solution exists.” and output an arbitrary solution in the form of x, y.

– If no solution exists, print “No solution exists.”

Problem Approach

This problem is about determining whether a linear equation has a solution. There are various theories that can indicate whether a solution exists based on the values of A, B, and C, but we will approach it through a basic method commonly used in systems of equations.

Basic Theory

First, the equation Ax + By = C can be graphically interpreted in a two-dimensional coordinate system. If both A and B are 0, the equation does not hold, and if either A or B is 0, there is a single solution. Excluding these cases, typical scenarios can have different solutions.

The conditions for Ax + By = C to have a solution are as follows:

  • If A = 0 and B = 0, there are infinitely many solutions if C is 0; otherwise, there is no solution.
  • If A = 0, to have a solution (with respect to B), it must be a multiple of B.
  • If B = 0, to have a solution (with respect to A), it must be a multiple of A.
  • In all other cases, a solution exists.

Solution Algorithm

  1. Check the existence of a solution using the values of A and B.
  2. Output appropriately based on the existence of a solution.
  3. If a solution exists, derive the solution using the slope and intercept of the line that includes the origin.

Swift Code

The following Swift code implements the algorithm described above.

import Foundation

func findSolution(A: Int, B: Int, C: Int) {
    if A == 0 && B == 0 {
        if C == 0 {
            print("A solution exists. (Infinitely many solutions)")
        } else {
            print("No solution exists.")
        }
    } else if A == 0 {
        // When B is not 0
        if C % B == 0 {
            let y = C / B
            print("A solution exists. (x is a free variable) -> x: any integer, y: \(y)")
        } else {
            print("No solution exists.")
        }
    } else if B == 0 {
        // When A is not 0
        if C % A == 0 {
            let x = C / A
            print("A solution exists. (y is a free variable) -> x: \(x), y: any integer")
        } else {
            print("No solution exists.")
        }
    } else {
        print("A solution exists. (Arbitrary solution - x: 0, y: \(C / B))")
    }
}

// Input values
let A = 2
let B = 3
let C = 6

findSolution(A: A, B: B, C: C)

Execution and Result

When the above Swift code is executed, it will output whether a solution exists for Ax + By = C. For example, if A = 2, B = 3, C = 6, the output will be as follows:

A solution exists. (Arbitrary solution - x: 0, y: 2)

Conclusion

In this tutorial, we explored the existence of solutions for linear equations in the form of Ax + By = C and the process of finding such solutions. By understanding the basics of algorithm problem-solving and writing code based on this, you can develop useful skills for coding tests or real programming situations.

Additionally, experimenting with various values of A, B, and C to analyze the patterns of solutions can be very helpful. In fact, providing various examples of both existing and non-existing solutions will greatly aid in understanding the problem.

Swift Coding Test Course, 2 N Tile Filling

Hello, everyone! In this post, we will discuss one of the coding test problems using Swift called “2*N Tile Filling.” This problem is one of the very useful problems for understanding the basics of dynamic programming. Below, I will detail the problem description and the process of solving it.

Problem Description

The problem is as follows. We need to find the number of ways to fill a rectangle that is 2 units high and N units wide with tiles of size 2×1 or 1×2. In other words, we need to count the number of ways to completely fill a 2*N rectangle using 2×1 and 1×2 tiles.

Examples

Here are examples for a few small values of N.

  • N=1: 1 (filling with one 1×2 tile)
  • N=2: 2 (filling with two 2×1 tiles or two 1×2 tiles)
  • N=3: 3 (filling with a combination of 1×2 and 2×1 tiles)
  • N=4: 5

Problem Solving Approach

This problem can be solved using dynamic programming. First, we need to set up the recurrence relation to solve the problem. In this problem, we can consider the following two cases.

  1. If the last column has a 1×2 tile: In this case, the size of the remaining problem is 2*(N-1).
  2. If the last row has a 2×1 tile: In this case, the size of the remaining problem is 2*(N-2).

By combining these two cases, we obtain the following recurrence relation.

f(N) = f(N-1) + f(N-2)

The initial cases are as follows.

  • f(1) = 1
  • f(2) = 2

Swift Code Implementation

Now, let’s implement the recurrence relation in Swift. During the implementation, we will use the memoization technique for efficiency.


    func tileWays(_ n: Int) -> Int {
        // Array for memoization
        var memo = Array(repeating: 0, count: n + 1)

        // Setting initial cases
        memo[1] = 1
        if n > 1 {
            memo[2] = 2
        }

        for i in 3...n {
            memo[i] = memo[i - 1] + memo[i - 2]
        }
        
        return memo[n]
    }

    // Example test
    let n = 4
    print("The number of ways to fill a height 2 and width \(n) with tiles: \(tileWays(n))")
    

Code Explanation

The above code works as follows:

  1. First, it declares a memo array initialized to 0. This array stores the number of ways to fill the tiles for each N.
  2. It sets the initial cases. It sets 1 for N=1 and 2 for N=2.
  3. It iterates from 3 to N, updating the memo array. For each case, it applies the recurrence relation to store values in the memo array.
  4. Finally, it returns memo[n] to provide the answer for N.

Time Complexity

This algorithm has a time complexity of O(N), which is proportional to N. By using memoization, we avoid redundant calculations and efficiently compute each case only once using the array.

Conclusion

In this post, we covered the “2*N Tile Filling” problem using Swift. Through understanding the problem and the solving process, we learned the basics of dynamic programming. I encourage you to solve more problems through practice.

In the next post, we will deal with another interesting algorithm problem. Thank you!

Swift Coding Test Course, 022 Sorting Numbers 3

Hello! This time, let’s solve a coding test problem based on Swift called “Sorting Numbers 3”. This problem may seem simple as it involves sorting numbers, but it has specific conditions and constraints, making it a good practice for coding tests. In this article, we will explore the problem definition, input and output formats, algorithmic approaches, and optimization methods in detail.

Problem Description

The requirement of the problem is to sort the given numbers, but the range of numbers to be sorted is limited. Specifically, the range of numbers is integers between 1 and 100,000, and the objective is to sort these integers in ascending order and output them.

For example, let’s assume the following numbers are given:

  • 5
  • 3
  • 8
  • 1
  • 2

In this case, the output should be displayed as follows:

  • 1
  • 2
  • 3
  • 5
  • 8

Input Format

The input is provided in the following format:

  1. The first line will contain the number of integers N. (1 ≤ N ≤ 100,000)
  2. The second line contains N integers separated by spaces.

Output Format

The output should print each sorted number on a new line.

Solution Approach

This problem involves sorting numbers, so we can use the most basic sorting algorithms. However, since the maximum value of N is 100,000, we cannot use inefficient algorithms like Bubble Sort or Selection Sort that have a time complexity of O(N^2).

We will use the Counting Sort algorithm to solve this problem. Counting Sort is a method that sorts efficiently when the range of given numbers is limited. This algorithm involves the following steps:

  1. Create an array corresponding to the range of input numbers.
  2. Record the count of each input number at the respective index.
  3. Finally, output the sorted numbers based on their counts.

Code Implementation

Now let’s write code to solve the problem in Swift. Since Swift allows the use of arrays as fields, implementing Counting Sort is very straightforward. Below is an example of the implementation:


    import Foundation

    func countingSort(numbers: [Int]) -> [Int] {
        // Since the range of numbers is 1 to 100,000, initialize an array of size 100,001
        var counts = Array(repeating: 0, count: 100001)

        // Count the occurrences of each number
        for number in numbers {
            counts[number] += 1
        }

        var sortedNumbers: [Int] = []
        
        // Generate sorted numbers based on the counts
        for (number, count) in counts.enumerated() {
            for _ in 0..

Example Execution

Let's use the code above to provide input. For instance, suppose we provide the following input:


    5
    5 3 8 1 2
    

The output result should be as follows:


    1
    2
    3
    5
    8
    

Complexity Analysis

The time complexity of this algorithm is O(N + K). Here, N is the number of input integers, and K is the range of numbers. In this case, K is fixed at 100,000, making the algorithm highly efficient. The space complexity also requires O(K), taking up O(100,000) space.

Conclusion

In this article, we examined the problem "Sorting Numbers 3" and implemented a solution using Counting Sort. Problems like these enhance understanding of basic algorithms and are frequently encountered in actual coding tests, so be sure to practice them. In the next tutorial, we will tackle more challenging problems. Thank you!