Swift Coding Test Course, Sorting Digits in Descending Order

In this article, we will explore how to solve a specific problem using Swift. The topic is Sorting Digits in Descending Order. This problem allows us to practice string manipulation, sorting algorithms, and handling data types in Swift.

Problem Description

Given an array of integers, write a function that converts each integer to a string, sorts the strings in descending order by their digits, and returns the result. For example, if the array is [321, 123, 456], it should convert each integer to a string resulting in ["321", "123", "456"] and sort it in descending order, returning ["321", "456", "123"].

Problem Examples

  • Input: [321, 123, 456] → Output: ["321", "456", "123"]
  • Input: [12, 345, 7, 89] → Output: ["89", "7", "345", "12"]
  • Input: [10, 2, 1] → Output: ["2", "10", "1"]

Problem Approach

The process to solve this problem can be divided into the following steps:

  1. Convert the integers to strings.
  2. Sort the strings in descending order by their digits.
  3. Return the sorted result.

Step 1: Convert Integer Array to String Array

To convert an integer to a string, you can use Swift’s String() initializer. This allows you to convert all integers in the array to strings. This conversion can be easily performed using the map() function.

Step 2: Sort Strings in Descending Order

When sorting strings, you need to provide a custom sorting logic using the sorted(by:) method. Here, you can compare the lengths of the strings, or in case of equal lengths, compare them lexicographically.

Step 3: Return the Sorted Result

After sorting, you simply return the resulting array of strings. The final implementation will look like this.

Swift Code Implementation

func sortDigitsDescending(_ numbers: [Int]) -> [String] {
        // Step 1: Convert integers to strings
        let stringNumbers = numbers.map { String($0) }
        
        // Step 2: Sort strings in descending order (by digits)
        let sortedNumbers = stringNumbers.sorted { 
            (lhs, rhs) in
            if lhs.count != rhs.count {
                return lhs.count > rhs.count // Compare number of digits
            } else {
                return lhs > rhs // Compare values if lengths are equal
            }
        }
        
        // Step 3: Return the sorted result
        return sortedNumbers
    }

Code Explanation

The Swift function above works as follows:

  • numbers.map { String($0) }: Converts each element of the given integer array to a string.
  • sorted { ... }: Applies custom sorting logic to sort in descending order. It first compares the number of digits, and if they are the same, it compares the string values.
  • Returns the sorted array of strings as the result.

Test Cases

You can run a few test cases to check if the function works correctly. Below are some example test codes using the function.

let testCase1 = [321, 123, 456]
let result1 = sortDigitsDescending(testCase1)
print(result1) // ["321", "456", "123"]

let testCase2 = [12, 345, 7, 89]
let result2 = sortDigitsDescending(testCase2)
print(result2) // ["89", "7", "345", "12"]

let testCase3 = [10, 2, 1]
let result3 = sortDigitsDescending(testCase3)
print(result3) // ["2", "10", "1"]

Conclusion

In this article, we covered the problem of converting integers to strings and sorting them in descending order by digits using Swift. This was a useful exercise to enhance understanding of string manipulation and sorting algorithms. Problems like this frequently appear in coding tests and can be beneficial in real-world applications.

The coding implementation process allows you to utilize various features of Swift and aims to help improve problem-solving skills. In the next course, we will tackle even more interesting problems!

Swift Coding Test Course, Calculate the Sum of Remainders

Recently, the importance of algorithm coding tests in the field of software development has been growing. This is because many companies evaluate candidates’ problem-solving abilities through coding tests during the interview process. In this article, we will solve the ‘Subarray Sum Remainder’ problem using the Swift language, covering everything from understanding the problem to the overall resolution process.

Problem Description

Given an integer array nums and an integer k, write a function to calculate the remainder of the sum of all subarrays of nums when divided by k, and return the total sum of these remainders.

Example Problem

  • Input: nums = [1, 2, 3, 4, 5], k = 3
  • Output: 10
  • Description: The sums of the subarrays are 1, 1+2=3, 1+2+3=6, 1+2+3+4=10, ..., and we need to find the remainders of each when divided by 3.

Approach to the Problem

To solve this problem, we first need to generate all subarrays, calculate their sums, and then find the remainder when divided by k. However, generating all subarrays directly can lead to a time complexity of more than O(n^3), so a more efficient approach is needed.

We can accumulate the sums of the subarrays and use this to solve the problem. In this process, we can think about how to store the remainders.

Swift Implementation


func subarraySumRemainder(nums: [Int], k: Int) -> Int {
    var totalRemainderSum = 0
    let n = nums.count
    
    for start in 0..

Code Explanation

The above function subarraySumRemainder takes nums and k as inputs and calculates the sum of remainders.

  • totalRemainderSum: A variable that stores the sum of all subarray remainders.
  • n: Stores the size of the array.
  • for start in 0..: Sets the starting index for each subarray.
  • currentSum: A variable that stores the sum of the current subarray.
  • for end in start..: Sets the ending index for the subarray and updates the current sum.
  • totalRemainderSum += currentSum % k: Calculates the remainder and adds it to the total sum.

Time Complexity Analysis

The time complexity of this algorithm is O(n^2). This is because, in the worst case, we need to traverse all subarrays of the array. Since calculating the remainder can be done in constant time, the total complexity is determined by the time spent generating the subarrays.

Other Approaches

This problem can be solved in various ways. For example, using the prefix sum technique can provide better time complexity. By using prefix sums, we can quickly find the sum over a specific range, thus reducing the time required to calculate the remainder.

Method Using Prefix Sum


func subarraySumRemainderUsingPrefixSum(nums: [Int], k: Int) -> Int {
    var prefixSums = [Int](repeating: 0, count: nums.count + 1)
    for i in 1...nums.count {
        prefixSums[i] = prefixSums[i - 1] + nums[i - 1]
    }
    
    var totalRemainderSum = 0
    for start in 0..

Conclusion

In this article, we explored the method of solving the 'Subarray Sum Remainder' problem using the Swift language. We provided a comprehensive explanation from understanding the problem and approach to implementation and time complexity analysis. There are multiple approaches to algorithm problems, and they require creative thinking to solve. I hope you continue to develop your coding skills through consistent practice.

References

  • LeetCode (https://leetcode.com)
  • GeeksforGeeks (https://www.geeksforgeeks.org)
  • Algorithm Visualizer (https://algorithm-visualizer.org)

Swift Coding Test Course, Depth First Search

This course explains how to solve algorithm problems using the Depth-First Search (DFS) algorithm. In this article, we will address a real algorithm problem and detail the process and code to solve that problem.

Problem Description

We want to calculate the sum of all paths in a given binary tree. Each path is from the root to a leaf node. The binary tree is given in the following form:

        class TreeNode {
            var val: Int
            var left: TreeNode?
            var right: TreeNode?

            init(_ val: Int) {
                self.val = val
                self.left = nil
                self.right = nil
            }
        }
        

Here, each node has a value (val) and is connected to a left child (left) and a right child (right). If the following binary tree is given:

               1
              / \
             2   3
            / \
           4   5
        

The sum of the paths from the root node 1 to the leaf nodes 4 and 5 is 7 (1+2+4) and 8 (1+2+5), so the final answer will be 15.

Approach to the Problem

We will use the DFS algorithm to solve this problem. DFS works by starting from a specific node, exploring as deeply as possible, and returning when no further nodes can be reached. In this case, we will calculate the cumulative sum of each path and record that sum when we reach a leaf node.

The steps to solve the problem are as follows:

  1. Start from the root node and perform DFS.
  2. Add the value (val) of the current node to the cumulative sum.
  3. If the current node is a leaf node, add the cumulative sum to the result.
  4. If it is not a leaf node, proceed to the left child and the right child, recursively calling DFS.
  5. Repeat the above process for all paths to calculate the cumulative sum.

Swift Code Implementation

Now let’s implement the above algorithm in code using Swift.

        class TreeNode {
            var val: Int
            var left: TreeNode?
            var right: TreeNode?

            init(_ val: Int) {
                self.val = val
                self.left = nil
                self.right = nil
            }
        }

        class Solution {
            func sumNumbers(_ root: TreeNode?) -> Int {
                return dfs(root, 0)
            }

            private func dfs(_ node: TreeNode?, _ currentSum: Int) -> Int {
                guard let node = node else { return 0 }
                let newSum = currentSum * 10 + node.val

                if node.left == nil && node.right == nil {
                    return newSum
                }

                return dfs(node.left, newSum) + dfs(node.right, newSum)
            }
        }
        

The above code recursively performs DFS to calculate the sum of the paths. The sumNumbers function takes the root node as an argument, while the dfs function takes the current node and cumulative sum as arguments and returns the final sum. The process is as follows:

  1. When the sumNumbers function is called, DFS starts with a current cumulative sum of 0.
  2. For each node, the current sum is multiplied by 10 and the node value is added to create a new sum.
  3. When a leaf node is reached, that sum is returned, and after adding the sums of the left and right children, the final result is returned.

Test Cases

Let’s create a few test cases to verify that the code works correctly. Here are examples of various binary tree structures.

        let root = TreeNode(1)
        root.left = TreeNode(2)
        root.right = TreeNode(3)
        root.left!.left = TreeNode(4)
        root.left!.right = TreeNode(5)

        let solution = Solution()
        print(solution.sumNumbers(root)) // Output: 15
        

In the above test case, we calculate the sum of all paths starting from 1, passing through 2, and reaching 4 and 5. As a result, the sum of 1-2-4 and 1-2-5 adds up to 15.

Performance and Optimization

This problem has a time complexity of O(N) using the DFS method, where N is the number of nodes. The space complexity is O(H), where H is the height of the tree. Since DFS uses a stack, in the worst case, we may need to visit all nodes, resulting in memory usage proportional to the height.

Alternatively, we could use the BFS (Breadth-First Search) method to solve the problem, but for this specific problem of calculating the sum of paths to leaf nodes, DFS is more intuitive and efficient.

Conclusion

In this lecture, we addressed the problem of calculating the path sum to leaf nodes in a binary tree using depth-first search. We understood the concept of the DFS algorithm and implemented it in Swift. Such problems frequently appear in many coding tests, so we encourage you to practice more with various variations of the problem.

Now that we have covered basic DFS, challenge yourself with more complex problems. For example, consider exploring graph traversal, finding connected components, or shortest path problems. We hope you develop more proficient coding skills through practice.

We hope this article has been helpful in your preparation for code testing. If you have any questions or additional comments, please leave them below.

Swift Coding Test Course, Exploring Geometry

Introduction

Hello! In this tutorial, we will learn how to solve geometric algorithm problems using Swift. Geometric problems are one of the frequently asked topics in coding tests, and the ability to solve problems related to points, lines, and surfaces in a coordinate system is crucial. In this article, we will present fundamental concepts of geometry, along with algorithmic problems that utilize these concepts, and we will explain the process of solving those problems in detail.

Basics of Geometry

Geometry is a branch of mathematics that studies shapes and the relationships between those shapes. The geometric objects mainly dealt with in algorithm problems include points, lines, triangles, and polygons. Various problems can be solved by utilizing the properties of these geometric figures. For example, calculating the distance between two points, whether lines intersect, and determining the perimeter and area of polygons are key aspects of geometric problems.

Problem Description

The problem at hand is to calculate the area of a polygon. You will need to write an algorithm that calculates the area of a polygon formed by connecting N given points.

Problem

Given N points, write an algorithm to calculate the area of the polygon formed by connecting these points. The points are provided in a two-dimensional plane, and their coordinates are expressed as integers.

Input

  • The first line contains an integer N (3 ≤ N ≤ 10^6).
  • In the next N lines, the X and Y coordinates of each point are given as integers.

Output

Print the area of the polygon rounded to the second decimal place.

Problem Solving Process

To design an algorithm for solving the problem, one must first understand how to calculate the area of a polygon. Generally, the most widely known method for calculating the area of a polygon is the ‘Shoelace Theorem’ (or ‘Surveyor’s Formula’). This method uses the following formula:

Shoelace Theorem

Given points (x1, y1), (x2, y2), …, (xN, yN), the area of the polygon can be calculated as follows:

= ( ( x _ i · y _ i+1 ) ( y _ i · x _ i+1 ) ) 2

To put this very simply, you take the absolute value of the sum obtained by applying the above formula to all the points of the polygon, and divide by 2 to get the area. Now, let’s implement this in Swift.

Swift Implementation

            
                import Foundation

                struct Point {
                    var x: Int
                    var y: Int
                }

                func polygonArea(points: [Point]) -> Double {
                    var area = 0
                    let n = points.count

                    for i in 0..

With the above code, we have implemented the functionality to calculate the area of a polygon. We use structs to represent the coordinates of the points, and the polygonArea function calculates the area for the given list of points. Finally, we handle the input of these points and output the area in the main function.

Conclusion

Through this tutorial, we have learned about geometric problems and the algorithms for solving them. We wrote a program to calculate the area of a polygon using Swift, which is a very useful technique in coding tests. There are various variations of geometric problems, so it is important to have a thorough understanding of the basic concepts and to practice. Keep challenging yourself with various geometric problems to build your skills!

© 2023 Swift Coding Test Course

Swift Coding Test Course, Radix Sort

Hello! Today, we will discuss the Radix Sort algorithm using Swift. Radix Sort is an efficient algorithm that sorts by grouping similar numbers together, primarily used for sorting a set of integers.

Overview of Radix Sort

Radix Sort is a comparison-based sorting algorithm that sorts numbers or strings by breaking them into digits. Radix Sort works as follows:

  • It decomposes the given number into specific digit places.
  • It sorts starting from the least significant digit (LSB).
  • It repeats this process for higher digit places.

Radix Sort is a stable sorting algorithm, and its average and worst-case time complexity is O(nk), where n is the number of elements and k is the maximum number of digits.

Problem Description

Now let’s solve the following problem using Radix Sort.

Problem:

Sort the following integer array in ascending order using the Radix Sort algorithm:

[170, 45, 75, 90, 802, 24, 2, 66]

Solution

To solve the problem, we will implement the Radix Sort algorithm step by step. We will write the code using pre-defined functions and structures in Swift.

Step 1: Separating by Digit Places

As the first step of Radix Sort, we separate based on each digit place. To perform this task, we will create a function to extract digits according to their place value.

func getDigit(number: Int, digitIndex: Int) -> Int {
    return (number / Int(pow(10.0, Double(digitIndex)))) % 10
}

Step 2: Implementing the Radix Sort Algorithm

Now let’s implement the complete Radix Sort algorithm. We need to create an array to group by digit places and sort accordingly.

func radixSort(array: [Int]) -> [Int] {
    let maxNumber = array.max() ?? 0
    let maxDigits = String(maxNumber).count
    
    var sortedArray = array
    
    for digitIndex in 0..
func countingSort(array: [Int], digitIndex: Int) -> [Int] {
    let countArraySize = 10
    var countArray = [Int](repeating: 0, count: countArraySize)
    var outputArray = [Int](repeating: 0, count: array.count)
    
    for number in array {
        let digit = getDigit(number: number, digitIndex: digitIndex)
        countArray[digit] += 1
    }
    
    for index in 1..

Step 3: Outputting the Result

Now let's output the results using the Radix Sort algorithm. We will call the functions we implemented above to sort the given array.

let unsortedArray = [170, 45, 75, 90, 802, 24, 2, 66]
let sortedArray = radixSort(array: unsortedArray)

print("Sorted array: \(sortedArray)")

Conclusion

Radix Sort is an effective method for grouping and sorting data based on specific digit places. We were able to sort an integer array in ascending order using this algorithm. By implementing Radix Sort in Swift, we gained an understanding of the principles of the algorithm and how to systematically solve problems.

References

  • Introduction to Algorithms - Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest
  • GeeksforGeeks Radix Sort article
  • Swift official documentation