Data Structures Core Notes

A single-page, at-a-glance revision project for core data structures and algorithmic thinking.

This project is designed as a fast reference and structured summary sheet covering essential data structure concepts without unnecessary depth.
It focuses on clarity, time and space trade-offs, real-world usage, and interview-ready fundamentals.

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Purpose

• Quick revision before interviews
• Rapid recall of core data structures and patterns
• Strong mental model of time complexity and space complexity
• Practical, decision-driven reminders for choosing the right structure
• Clear implementations mindset (primary C++ focus, concept-first notes)

Coverage

Foundations

• What is a data structure
• Abstract Data Type (ADT) vs data structure
• Time complexity and Big O
• Space complexity
• Worst-case vs average-case thinking
• Amortized analysis basics
• Common trade-offs (speed vs memory)

Linear Data Structures

• Arrays (static vs dynamic)
• Vectors and resizing concept
• Linked list (singly, doubly, circular)
• Stack
• Queue
• Deque

Hash Based Structures

• Hash table fundamentals
• Hash functions and collisions
• Collision resolution (chaining, open addressing concepts)
• Load factor and rehashing
• Set vs Map

Trees

• Tree basics and terminology
• Binary tree
• Binary search tree
• Traversals (DFS, BFS)
• Balanced tree concept (intro)
• Heap (min heap, max heap)
• Priority queue

Graphs

• Graph fundamentals
• Directed vs undirected
• Weighted vs unweighted
• Graph representations (adjacency list, adjacency matrix)
• BFS and DFS
• Cycle detection concept
• Topological sort concept
• Shortest path idea (intro)

Advanced Structures

• Trie
• Disjoint set (Union Find)
• Segment tree (concept level)
• Fenwick tree (intro level)

Algorithmic Patterns

• Two pointers
• Sliding window
• Fast and slow pointers
• Binary search pattern
• Divide and conquer concept
• Recursion basics and stack cost
• Backtracking concept
• Greedy basics
• Dynamic programming intro

Complexity Master Section

• Time vs space trade-offs
• Cache locality intuition
• Worst case traps and when Big O lies
• Common performance mistakes

Tech Stack

• React
• Vite
• styled-components

Project Type

Single page only
Section-based navigation
Searchable and expandable content
No blog-style content, only structured notes

Each section is modular and collapsible for fast scanning.

Run Locally

npm install
npm run dev

Goal

Complete data structures fundamentals in one scrollable page. No fluff. No repetition. Just essentials.