Data Structures Study Notes

Abstract Data Types

Understand the distinction between abstract data types and their concrete implementations.

Common Array and String Problems

Classic array and string interview patterns like two-pointer and sliding window, with worked examples and complexity.

Arrays in Data Structures

How arrays store elements in contiguous memory and why that layout drives their performance characteristics.

AVL Trees

A self-balancing binary search tree that maintains O(log n) height via rotations after every insertion and deletion.

Big-O Notation

A precise guide to Big-O notation and the common complexity classes every developer must recognize.

Binary Search

The classic O(log n) algorithm for finding a target in a sorted array using repeated halving, with correct boundary handling.

Binary Search Trees

A binary tree variant that maintains an ordering invariant, enabling fast search, insert, and delete operations.

Binary Trees

A hierarchical data structure where each node has at most two children, forming the foundation for many advanced tree structures.

Choosing the Right Data Structure

A practical decision framework for picking between arrays, linked lists, hash tables, trees, graphs, and heaps.

Circular Linked Lists

A linked list variant where the last node points back to the first, forming a continuous loop with no None end.

Circular Queues

A fixed-size queue that reuses freed slots by wrapping indices with the modulo operator, avoiding wasted space.

Collision Handling in Hashing

Techniques like chaining and open addressing that resolve situations where two different keys hash to the same bucket.

Common Data Structures Pitfalls

Frequent mistakes candidates make with data structures in interviews and production code, and how to fix them.

Deques

A double-ended queue allowing O(1) insertion and removal from both the front and the back.

Doubly Linked Lists

A linked list where each node has both next and previous pointers, allowing efficient bidirectional traversal.

Common Data Structures Interview Questions

A curated set of frequently asked data structures interview questions with technically accurate, concise answers.

Fenwick Trees (Binary Indexed Trees)

A compact array-based structure using the lowbit trick to compute prefix sums and point updates in O(log n).

Graph Representation

Learn how to model graphs using adjacency lists, adjacency matrices, and edge lists in Python.

Graph Traversal: BFS and DFS

Master Breadth-First Search and Depth-First Search, the two fundamental algorithms for exploring graphs.

Hash Set and Hash Map Applications

Practical, real-world uses of hash sets and hash maps for deduplication, counting, caching, and fast lookups.

Hash Tables

A data structure that maps keys to values using a hash function for near-constant time lookups, insertions, and deletions.

Heap Sort and Counting Sort

How heap sort uses a binary heap for guaranteed O(n log n) in-place sorting, and how counting sort achieves linear time for bounded integers.

Heaps

A complete binary tree stored as an array that maintains a heap-order property, enabling O(log n) priority operations.

Introduction to Data Structures

A foundational overview of what data structures are, why they matter, and how they are classified.