Algorithms and Data Structures in C# (.NET)

This book is a practical guide to fundamental algorithms and data structures implemented in C# within the .NET ecosystem. It is designed for developers who want not just to write working code, but also to understand how to make it as efficient, scalable, and maintainable as possible.

Unlike abstract academic textbooks, the material is presented through the lens of real-world problems that every .NET developer encounters. You will not only study the theory but also see how specific algorithms are applied to process big data, build high-load services, work with collections, and optimize queries.

What you will learn from the book:

• Basic and advanced data structures: from arrays, lists, and stacks to trees (binary, AVL, red-black), graphs, hash tables, and heaps. Each structure is examined in terms of its internal structure, add/delete/search operations, and complexity estimation (Big O).
• Classic sorting and searching algorithms: quicksort, merge sort, binary search, depth-first and breadth-first search (DFS/BFS) for graphs. You will learn to choose the optimal algorithm for a specific task.
• Graph algorithms: shortest path search (Dijkstra, Bellman-Ford), minimum spanning tree (Kruskal, Prim), topological sorting. You will be able to model and solve routing, network planning, and dependency analysis problems.
• Dynamic programming and greedy algorithms: analysis of classic problems (knapsack problem, longest common subsequence, coin change problem). You will master the technique of breaking complex problems into subproblems.
• Memory and performance in .NET: specifics of garbage collection, the impact of data structures on allocations, using Span and Memory for zero-allocation scenarios. You will learn to profile and optimize your code.

Who this book is for:

• Junior and Middle .NET developers who want to level up their skills and prepare for technical interviews at top companies.
• Backend developers working with high-load systems and microservices in C#.
• Students and graduates of technical specialties studying programming on the .NET platform.
• Developers transitioning from other languages (Java, Python, C++) to C# and wanting to understand the specifics of algorithm implementation in .NET.

Each chapter contains not only theoretical explanations but also ready-made code examples, practical exercises, and problems for independent solving. By the end of the book, you will be able to confidently design efficient solutions, write code that runs fast and consumes minimal resources, and successfully pass algorithmic sections of interviews.

The book is written in simple and clear language with an emphasis on practice. All examples are relevant for the latest versions of .NET (including .NET 8/9) and C# 12+.