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Introduction
Data structures form the backbone of computer science, serving as fundamental tools for efficient data organization. In the dynamic landscape of the C# programming language, developers have access to a versatile array of built-in and custom data structures. This exploration aims to provide an in-depth understanding of commonly used data structures in C#, accompanied by practical applications demonstrated through illustrative examples.
Navigating the intricacies of data structures is pivotal for any programmer seeking to optimize their code for performance, scalability, and maintainability. This guide will delve into the nuances of arrays, lists, stacks, queues, dictionaries, hashsets, and more, shedding light on their unique characteristics and real-world applications. Join us on this journey through C#’s data structures, where we unravel the power they bring to the table and empower developers to make informed decisions in crafting robust and efficient solutions.
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Arrays
Arrays are one of the most straightforward and widely employed data structures. They enable the storage of elements of the same type in contiguous memory locations, allowing easy access using indices.
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int[] numbers = { 1, 2, 3, 4, 5 }; // Accessing elements Console.WriteLine(numbers[2]); // Output: 3 // Modifying elements numbers[1] = 10; // Iterating through the array foreach (var num in numbers) { Console.Write(num + " "); } // Output: 1 10 3 4 5 |
Lists
Dynamic arrays, known as Lists, provide greater flexibility than fixed-size arrays. They can dynamically grow or shrink in size based on requirements.
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//Code List<string> fruits = new List<string> { "Apple", "Banana", "Orange" }; // Adding elements fruits.Add("Grapes"); // Removing elements fruits.Remove("Banana"); // Iterating through the list foreach (var fruit in fruits) { Console.Write(fruit + " "); } // Output: Apple Orange Grapes ``` |
Stack
Operating on the Last In, First Out (LIFO) principle, a stack ensures that the last element added is the first to be removed.
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//Code Stack<int> stack = new Stack<int>(); // Pushing elements onto the stack stack.Push(1); stack.Push(2); stack.Push(3); // Popping elements from the stack int poppedItem = stack.Pop(); Console.WriteLine(poppedItem); // Output: 3 ``` |
Queue
Conversely, a queue adheres to the First In, First Out (FIFO) principle, meaning the first element added is the first to be removed.
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//Code Queue<string> queue = new Queue<string>(); // Enqueuing elements queue.Enqueue("John"); queue.Enqueue("Jane"); queue.Enqueue("Doe"); // Dequeuing elements string dequeuedItem = queue.Dequeue(); Console.WriteLine(dequeuedItem); // Output: John ``` |
Dictionary
Dictionaries facilitate the storage of key-value pairs, ensuring fast access to values based on their associated keys.
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//Code Dictionary<string, int> ages = new Dictionary<string, int>(); // Adding key-value pairs ages["Alice"] = 25; ages["Bob"] = 30; // Accessing values int bobAge = ages["Bob"]; Console.WriteLine(bobAge); // Output: 30 ``` |
HashSet
A HashSet, an unordered collection of unique elements, proves beneficial for tasks requiring distinct values.
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//Code HashSet<int> uniqueNumbers = new HashSet<int>(); // Adding elements uniqueNumbers.Add(5); uniqueNumbers.Add(10); uniqueNumbers.Add(5); // Ignored, as 5 already exists // Iterating through the set foreach (var num in uniqueNumbers) { Console.Write(num + " "); } // Output: 10 5 ``` |
Conclusion
Whether opting for arrays, lists, dictionaries, or other structures, choosing the right data structure is pivotal for successful C# programming.
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FAQs
1. When should I use an array instead of a list?
ANS: – Arrays are suitable when the collection size is fixed or known in advance. Lists provide dynamic sizing, making them more flexible when the size may change during program execution.
2. What distinguishes a stack from a queue?
ANS: – A stack follows the Last In, First Out (LIFO) principle, while a queue adheres to the First In, First Out (FIFO) principle. Stacks are ideal for tasks like undo mechanisms, whereas queues are useful in scenarios like task scheduling.

WRITTEN BY Subramanya Datta
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