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Data Structures

Master the art of organizing data efficiently. Learn how arrays, linked lists, trees, graphs, and hash tables shape the performance of every program you write.

Expanding your solution toolkit

Data structures can help you understand a broader range of solutions for your programs. In software development, we're always dealing with data, and sometimes choosing the right way to organize it is an excellent start. While the good old array solves most problems, sometimes we need to take a step further.

Why data structures matter

  • Performance: The wrong structure turns instant operations into ones too slow for production
  • Scalability: Code that works locally can fail with real data if the structure doesn't scale
  • Resource consumption: Memory and CPU are finite - the structure defines how much you need of each
  • Maintainability: Appropriate structures make code simpler and bugs easier to find

Mastering data structures is about developing intuition to choose the right tool based on your problem's real needs.

What you'll learn

Each article in this category explores:

  • How the structure organizes data in memory
  • Available operations and their time/space complexities
  • When to choose it over alternatives
  • Real-world applications and common pitfalls
12 articles
Data Structures01 / 12

Introduction to Data Structures

Understand how data structures transform random bytes into meaningful patterns. Explore contiguous vs scattered memory, linear vs non-linear structures, and the tradeoffs that shape your code's performance.

4 minutes read
Data Structures02 / 12

Arrays

Learn how arrays store elements in contiguous memory for instant access. Understand indexing, memory layout, and the tradeoffs that make arrays the foundation of most data structures.

11 minutes read
Data Structures03 / 12

Linked Lists

Discover how linked lists trade instant access for flexible insertion. Learn node structure, pointer manipulation, singly vs doubly variants, and when to choose linked lists over arrays.

11 minutes read
Data Structures04 / 12

Stacks

Learn how stacks enforce LIFO order to manage data. Explore push, pop, and peek operations, array vs linked list implementations, and why stacks underpin function calls and expression parsing.

10 minutes read
Data Structures05 / 12

Queues

Learn how queues enforce FIFO order to manage data. Explore enqueue, dequeue, and peek operations, circular buffer vs linked list implementations, and why queues drive task scheduling and BFS.

11 minutes read
Data Structures06 / 12

Hash Tables

Learn how hash tables achieve O(1) average lookups by mapping keys to array slots. Explore hash functions, collision resolution with chaining and open addressing, load factor, and rehashing.

28 minutes read
Data Structures07 / 12

Trees

Learn how trees organize data hierarchically with one parent per node. Explore root, depth and height, the V-1 edge rule, and how Go represents children in memory.

17 minutes read
Trees08 / 12

Binary Trees

Learn what the two-child limit buys you. Explore full, complete, perfect, balanced and degenerate shapes, why height governs cost, and how a binary tree fits in a flat array.

17 minutes read
Trees09 / 12

Binary Search Trees

Learn how one ordering rule turns a binary tree into a search structure. Explore the recursive invariant, search, insert, the three delete cases, and why sorted input ruins everything.

16 minutes read
Trees10 / 12

Balanced Trees

Learn how rotations put a floor under a binary search tree. Explore the balance factor, AVL's four cases, why libraries chose red-black, and what balancing costs.

15 minutes read
Trees11 / 12

Heap

Learn how a weaker invariant answers "what is the smallest right now". Explore the Priority Queue ADT, sifting up and down, the tree that fits in an array with no pointers, and why build-heap is O(n).

24 minutes read
Data Structures12 / 12

Graphs

Learn how graphs model relationships between nodes. Explore directed, weighted and cyclic graphs, and how adjacency lists and matrices trade space for lookup speed in Go.

22 minutes read