Algorithms and Data Structures in C#: A Complete Developer's Guide

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Introduction to Algorithms and Data Structures in C#

Algorithms and data structures are the foundation upon which any quality software is built. In the .NET ecosystem and the C# language, understanding these concepts allows you not only to write more efficient code but also to competently choose tools from the rich standard library (BCL — Base Class Library). The speed of an application, memory consumption, and ultimately the user experience depend on the choice of data structure.

In this article, we will break down the key data structures and algorithms that every C# developer should know. We will look at their implementation, performance characteristics (Big O notation), and practical code examples. The article is suitable for both beginners and experienced programmers looking to systematize their knowledge.

Basic Data Structures in C#

Arrays and Lists (Array vs List<T>)

Array is a fixed-size data structure that stores elements of the same type in a contiguous memory region. Index access occurs in O(1), but inserting and deleting elements (except at the end) requires O(n) due to shifting.

int[] numbers = new int[5] { 10, 20, 30, 40, 50 };Console.WriteLine(numbers[2]); // 30

List<T> is a dynamic array. It automatically increases its capacity when elements are added. Internally, it uses an array, so index access speed is also O(1). However, insertion in the middle or at the beginning is O(n).

List<string> names = new List<string>() { "Anna", "Boris" };names.Add("Victor");names.Insert(1, "Gleb"); // O(n)Console.WriteLine(names[0]); // Anna

Stack and Queue (Stack<T> and Queue<T>)

Stack<T> works on the LIFO (Last In, First Out) principle. It is used for traversal algorithms, expression parsing, and call management.

Stack<int> stack = new Stack<int>();stack.Push(1);stack.Push(2);stack.Push(3);int top = stack.Pop(); // 3

Queue<T> works on the FIFO (First In, First Out) principle. It is used in task processing systems and data buffering.

Queue<string> queue = new Queue<string>();queue.Enqueue("Task 1");queue.Enqueue("Task 2");string next = queue.Dequeue(); // "Task 1"

Both structures are implemented based on an array (circular buffer) and provide insertion and deletion operations in O(1) on average.

Dictionary (Dictionary<TKey, TValue>)

Dictionary<TKey, TValue> is a hash table. It provides search, insertion, and deletion of elements by key in O(1) on average (with a good hash function). This is one of the most frequently used data structures in C#.

Dictionary<string, int> ages = new Dictionary<string, int>();ages["Alice"] = 30;ages["Bob"] = 25;

if (ages.ContainsKey("Alice")){    Console.WriteLine(ages["Alice"]); // 30}

Important: Keys in a Dictionary must be unique and implement the IEquatable<T> interface or have correctly overridden GetHashCode() and Equals() methods.

Linked List (LinkedList<T>)

LinkedList<T> is a doubly linked list. Unlike List, insertion and deletion in the middle of the list is performed in O(1) (if you have a reference to the node). However, index access is O(n). It is used less frequently but is indispensable for double-ended queues and LRU caches.

LinkedList<int> list = new LinkedList<int>();list.AddLast(1);list.AddLast(2);list.AddFirst(0);

LinkedListNode<int> node = list.Find(1);list.AddAfter(node, 10); // O(1)