Algorithms and Data Structures in C# (.NET)

The book "Algorithms and Data Structures in C# (.NET)" is a comprehensive practical guide that will help developers of any level master fundamental and advanced concepts of building efficient code. Unlike abstract textbooks, the material is focused on real-world tasks that C# developers face in their daily work: from processing collections to optimizing the performance of server applications on the .NET platform.

What this book is about

The book covers a full range of topics necessary for confident algorithmic thinking:

• Basics of complexity analysis: Big O, Omega and Theta notation; how to evaluate algorithm performance before writing code.
• Classic data structures: arrays, lists, stacks, queues, hash tables, trees (BST, AVL, red-black) and graphs — with implementation examples in C#.
• Sorting and searching algorithms: quicksort, merge sort, binary search, interpolation search and their adaptation for .NET.
• Working with LINQ and collections: how built-in data structures (List, Dictionary, HashSet, SortedSet) use algorithms under the hood.
• Dynamic programming and greedy algorithms: solving classic problems (knapsack problem, shortest path search, traveling salesman problem).
• Modern features of C# 12+ and .NET 8+: Span, Memory, indexed collections, records for immutable data structures.

Who this book is for

The publication will be useful for:

• Junior and Middle developers who want to systematize their knowledge and learn to write fast, predictable code.
• Students and graduates studying Computer Science and wanting to apply theory in practice within the .NET ecosystem.
• Senior engineers who need a reference for non-trivial use cases of data structures and algorithms in high-load systems.
• Technical interviewers and those preparing for interviews at major IT companies (the book covers typical problems from real interviews).

What you will learn

• How to choose a data structure for a specific task to avoid premature optimization.
• How to implement your own iterator, LRU cache, or priority queue without third-party libraries.
• How to use asynchronous algorithms (Parallel LINQ, Task-based approaches) to speed up big data processing.
• How to test and benchmark algorithms using BenchmarkDotNet.
• How to avoid common memory and GC pressure mistakes when working with collections.

Each chapter contains practical examples ready for use in projects and exercises to reinforce the material. The code is available for download and has been tested under .NET 8 and Visual Studio 2022.

Igor Semyonov is a software architect with 10 years of experience in C# development. He has participated in creating high-load financial systems and cloud services on Azure. Author of algorithm courses for developers and a regular speaker at industry conf