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Here Be Dragons

Data Structures

Overview

A data structure is a way of organizing data so the operations you need on it are efficient. In coding interviews (Blind 75, NeetCode 150, Cracking the Coding Interview, LeetCode company tags), a small set of structures covers roughly 90% of problems. This topic is a reference for that set: what each structure is, how it’s typically implemented, the time complexity of its core operations, and the canonical problems it solves.

The top ten

  1. Arrays
  2. Strings
  3. Hash Tables
  4. Linked Lists
  5. Stacks
  6. Queues
  7. Binary Trees & BSTs
  8. Heaps / Priority Queues
  9. Graphs
  10. Tries

How each subtopic is organized

Every subtopic follows a consistent structure so they’re easy to scan:

  • Intro, what it is and why it exists
  • In-depth description, how it’s typically implemented and the key invariants
  • Time complexity, average- and worst-case for the main operations
  • Common uses in DSA, five interview-relevant problem patterns it unlocks

Picking the right structure

A rough decision flow:

  • Need O(1) lookup by value? → Hash Table
  • Need order preserved and random access? → Array
  • Need FIFO (breadth, levels, streams)? → Queue
  • Need LIFO (nesting, backtracking, matching)? → Stack
  • Need top-K or always-min/max? → Heap
  • Need ordered map / in-order iteration? → Binary Search Tree
  • Need hierarchical data or “explore from a node”? → Tree or Graph
  • Need fast prefix queries? → Trie
  • Need O(1) insert/delete at a known node? → Linked List (usually as part of a composite like LRU)

References

Why the name "Here Be Dragons"?