Android Application Development Lab Book Data Structures and Algorithms

In today’s learning activities, you will be introduced to the highest in-demand job skill we see employers asking for in job ads: Data Structures and Algorithms.

Lab Introduction: Data Structures and Algorithms in Demand

In today's learning activities, we are excited to introduce you to one of the most in-demand job skills that employers are seeking from new graduates: Data Structures and Algorithms. Data structures and algorithms form the backbone of efficient and scalable software solutions, and having a strong understanding of them is crucial for success in the tech industry.
As the demand for mobile applications continues to rise, employers are increasingly looking for graduates who possess a solid foundation in data structures and algorithms. These skills are essential for developing high-performance, robust, and user-friendly mobile applications. Let's explore five practical use cases where data structures and algorithms are heavily utilized in the mobile application development landscape:
Optimizing Storage and Retrieval: Mobile applications often need to manage large amounts of data, such as user profiles, images, or audio files. By applying data structures like arrays or lists, developers can efficiently store and retrieve this data, ensuring optimal performance and user experience.
Enhancing User Experience: Algorithms play a significant role in improving user experience in mobile applications. For example, algorithms for searching, sorting, and filtering can enhance the efficiency and responsiveness of search functionality, product recommendations, or chat message organization.
Efficient Networking and Data Transfer: Mobile applications frequently rely on network communication to interact with servers or exchange data with other devices. Data structures like queues or priority queues can be used to manage network requests, ensuring a fair and efficient distribution of resources and reducing latency.
Real-Time Updates and Notifications: Data structures such as trees and graphs are invaluable when dealing with real-time updates and notifications. They allow for efficient organization and traversal of data, enabling applications to deliver timely and relevant information to users.
Route Planning and Location-Based Services: Algorithms like Dijkstra's algorithm or A* search algorithm are essential for route planning and location-based services in mobile applications. They enable efficient pathfinding, real-time traffic updates, and optimal navigation suggestions.
By acquiring proficiency in data structures and algorithms, you will be equipped with the skills that employers highly value in the competitive job market. These skills not only enhance your problem-solving capabilities but also enable you to design and develop mobile applications that are efficient, scalable, and user-friendly.
Throughout the lab activities, you will gain hands-on experience with various data structures and algorithms, learn how to apply them to solve practical problems, and understand their impact on mobile application development. Remember, mastering these skills will not only make you a sought-after candidate in the job market but also empower you to create innovative and impactful mobile applications.
So, let's dive into the lab activities and explore the fascinating world of data structures and algorithms in mobile application development!

Student Lab Learning Workbook: Android Application Development with Kotlin


Welcome to the Student Lab Learning Workbook on Android Application Development with Kotlin. In this workbook, you will be guided through a series of lab activities that will help you learn and practice Android application development using Kotlin. Each lab activity will provide you with complete Kotlin code, and you will learn how to take inputs from the screen, process them using various data structures and algorithms (DSA) techniques, and output the results back to the screen.
Before starting with this workbook, you should have a basic understanding of Kotlin programming language and Android Studio. Familiarity with fundamental concepts of data structures and algorithms will also be beneficial.
Lab Activity 1: Setting Up the Development Environment
Install Android Studio and set up a new project.
Familiarize yourself with the project structure and key components.
Lab Activity 2: Creating the User Interface (UI)
Design the user interface using XML layouts.
Create necessary activities and link them with their respective layouts.
Implement UI elements to capture user inputs.
Lab Activity 3: Handling User Input
Retrieve user input from UI elements.
Validate and sanitize user input, if required.
Pass the input data to the appropriate DSA techniques for processing.
Lab Activity 4: Implementing DSA Techniques
Choose appropriate DSA techniques for processing user input.
Implement data structures (e.g., arrays, lists, maps) to store and manipulate data.
Apply algorithms (e.g., sorting, searching, graph traversal) to process the input data.
Lab Activity 5: Processing Input and Generating Output

Here's an example Kotlin code snippet that demonstrates the use of stacks and queues to process the input of student names and classes and return the output: In this example, the code reads and writes from the command prompt. Can you extend the code to interact directly with the Android GUI? If not, we will cover this together next week.

kotlinCopy code
import java.util.*

fun main() {
val scanner = Scanner(System.`in`)

// Creating a stack and a queue
val stack = Stack<String>()
val queue = LinkedList<String>()

// Taking input from the user
println("Enter the names of 10 students and their corresponding classes:")

for (i in 1..10) {
print("Student $i name: ")
val name = scanner.nextLine()

print("Student $i class: ")
val className = scanner.nextLine()

// Pushing the student name to the stack

// Enqueueing the student class to the queue

// Processing the input using stacks and queues
println("\nProcessing the input using stacks and queues:")

println("Processing student names from the stack:")
while (!stack.isEmpty()) {
val name = stack.pop()
println("Name: $name")

println("\nProcessing student classes from the queue:")
while (!queue.isEmpty()) {
val className = queue.poll()
println("Class: $className")

In this code, we use a Stack to store the student names and a Queue (implemented using LinkedList) to store the corresponding class names. The user is prompted to enter the names and classes for 10 students. The names are pushed onto the stack using the push method, and the classes are enqueued using the offer method.
After taking input, the code processes the input by printing the student names from the stack and the class names from the queue. The pop method is used to retrieve names from the stack, and the poll method is used to retrieve class names from the queue.
Feel free to modify the code to suit your specific requirements or integrate it into your Android application as per the lab activities in the workbook.

Utilize the DSA techniques to process the input data.
Generate the desired output based on the processed data.
Prepare the output for display on the screen.
Lab Activity 6: Displaying Output on the Screen
Retrieve the processed output from DSA techniques.
Format the output data appropriately for display.
Update the UI elements with the final output.

Here's an example of how you can implement Lab Activity 6 to display the processed output on the screen in an Android Kotlin application:

Assuming you have a TextView element with the ID "outputTextView" in your XML layout file, here's the corresponding Kotlin code:
kotlinCopy code
import android.os.Bundle
import android.widget.TextView

class MainActivity : AppCompatActivity() {

private lateinit var outputTextView: TextView

override fun onCreate(savedInstanceState: Bundle?) {

// Initialize the outputTextView
outputTextView = findViewById(

// Process the input and get the processed output from DSA techniques
val processedOutput = getProcessedOutput()

// Format the output data appropriately for display
val formattedOutput = formatOutput(processedOutput)

// Update the UI elements with the final output

private fun getProcessedOutput(): String {
// Perform the necessary DSA techniques to process the input
// Replace this with your own logic to process the input and get the output
val processedOutput = "Processed output"

return processedOutput

private fun formatOutput(output: String): String {
// Format the output data as per your requirements
// You can apply any necessary formatting or transformations here
// For example, you can add line breaks or additional text to the output
val formattedOutput = "Formatted output: $output"

return formattedOutput

private fun updateUI(output: String) {
// Update the UI elements with the final output
outputTextView.text = output

In this code, the onCreate method is called when the activity is created. Inside this method, we initialize the outputTextView by finding it using findViewById.
Next, we call the getProcessedOutput function to retrieve the processed output from DSA techniques. You should replace this function with your own logic to process the input and obtain the output.
Then, we pass the processed output to the formatOutput function to format the output data appropriately. Modify this function as per your formatting requirements.
Finally, we call the updateUI function to update the outputTextView with the final formatted output. This function sets the text property of the outputTextView to the formatted output.
Make sure to replace activity_main with the appropriate layout file name from your project, and adjust the IDs and variable names according to your XML layout file.
This code demonstrates the basic structure for displaying the output on the screen. You can further enhance it based on your specific requirements and the complexity of the data structures and algorithms techniques used in your application.
Lab Activity 7: Testing and Debugging
Test the application with various inputs to ensure correctness.
Debug any issues or errors encountered during testing.
Refine the code and UI based on testing results.
Lab Activity 8: Enhancements and Advanced Topics (optional)
Implement additional features or functionalities based on your interests.
Explore advanced DSA techniques and incorporate them into your application.

Let's explore an additional DSA technique called "Binary Search" and incorporate it into the Android Kotlin application. Binary search is an efficient algorithm used to search for an element in a sorted array by repeatedly dividing the search space in half.

Here's an example Kotlin code that demonstrates the use of binary search to search for a target number in a sorted array:
kotlinCopy code
import java.util.*

fun main() {
val scanner = Scanner(System.`in`)

// Taking input from the user
println("Enter a sorted array of numbers (space-separated):")
val input = scanner.nextLine().trim().split(" ").map { it.toInt() }.toIntArray()

println("Enter the target number to search:")
val target = scanner.nextInt()

// Applying binary search
val index = binarySearch(input, target)

// Displaying the result
if (index != -1) {
println("Target number $target found at index $index")
} else {
println("Target number $target not found in the array")

fun binarySearch(arr: IntArray, target: Int): Int {
var left = 0
var right = arr.size - 1

while (left <= right) {
val mid = left + (right - left) / 2

when {
arr[mid] == target -> return mid
arr[mid] < target -> left = mid + 1
else -> right = mid - 1

return -1

In this code, we first take input from the user, assuming a sorted array of numbers. The array is stored in the input variable. We then prompt the user to enter the target number to search, which is stored in the target variable.
The binarySearch function implements the binary search algorithm. It takes the array arr and the target number target as input and returns the index of the target number in the array or -1 if the number is not found.
Finally, we call the binarySearch function with the input array and target number and display the result based on the returned index.
You can integrate this binary search code into your Android Kotlin application by adapting it to your specific use case. For example, you can create a separate function to perform binary search on an array obtained from user input and update the UI with the search results.

Let's explore an additional DSA technique called "Depth-First Search (DFS)" and incorporate it into the Android Kotlin application. DFS is a graph traversal algorithm that explores as far as possible along each branch before backtracking.
Here's an example Kotlin code that demonstrates the use of Depth-First Search (DFS) to traverse a graph:
kotlinCopy code
import java.util.*

class Graph(private val numVertices: Int) {
private val adjacencyList: Array<LinkedList<Int>> = Array(numVertices) { LinkedList<Int>() }

fun addEdge(source: Int, destination: Int) {

fun dfs(startVertex: Int) {
val visited = BooleanArray(numVertices)

dfsUtil(startVertex, visited)

private fun dfsUtil(vertex: Int, visited: BooleanArray) {
visited[vertex] = true
print("$vertex ")

val neighbors = adjacencyList[vertex]
for (neighbor in neighbors) {
if (!visited[neighbor]) {
dfsUtil(neighbor, visited)

fun main() {
val scanner = Scanner(System.`in`)

// Taking input from the user
println("Enter the number of vertices in the graph:")
val numVertices = scanner.nextInt()

val graph = Graph(numVertices)

println("Enter the number of edges in the graph:")
val numEdges = scanner.nextInt()

println("Enter the edges (source and destination vertices):")
repeat(numEdges) {
val source = scanner.nextInt()
val destination = scanner.nextInt()
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