Data Structures & Algorithms Roadmap¶

• Roadmap: https://roadmap.sh/datastructures-and-algorithms

1. Pick a Language¶

• 1.1 JavaScript
• 1.2 Java
• 1.3 Go
• 1.4 C#
• 1.5 C++
• 1.6 Python
• 1.7 Rust
• 1.8 Ruby

01. Introduction to DSA¶

What DSA is, why it matters, how to study it, how problems map to data structures.

02. Programming Fundamentals¶

• 2.1 Language Syntax
• 2.2 Pseudo Code
• 2.3 Control Structures
• 2.4 Functions
• 2.5 OOP Basics

03. What are Data Structures?¶

04. Why are Data Structures Important?¶

05. Basic Data Structures¶

• 5.1 Array
• 5.2 Linked Lists
• 5.3 Queues
• 5.4 Stacks
• 5.5 Hash Tables

06. Algorithmic Complexity¶

6.1 Time vs Space Complexity¶

6.2 How to Calculate Complexity?¶

6.3 Common Runtimes¶

• 6.3.1 Constant
• 6.3.2 Logarithmic
• 6.3.3 Linear
• 6.3.4 Polynomial
• 6.3.5 Exponential
• 6.3.6 Factorial

6.4 Asymptotic Notation¶

• 6.4.1 Big-O Notation
• 6.4.2 Big-θ Notation
• 6.4.3 Big-Ω Notation

07. Sorting Algorithms¶

• 7.1 Bubble Sort
• 7.2 Merge Sort
• 7.3 Insertion Sort
• 7.4 Quick Sort
• 7.5 Selection Sort
• 7.6 Heap Sort

08. Search Algorithms¶

• 8.1 Linear Search
• 8.2 Binary Search

09. Trees¶

• 9.1 Binary Tree
• 9.2 Binary Search Tree (BST)
• 9.3 AVL Tree
• 9.4 Red-Black Tree
• 9.5 Trie
• 9.6 Segment Tree
• 9.7 Fenwick Tree (BIT)
• 9.8 B-Tree

10. Heaps & Priority Queues¶

• 10.1 Binary Heap
• 10.2 Priority Queue
• 10.3 Fibonacci Heap
• 10.4 D-Ary Heap

11. Graphs¶

• 11.1 Representation (matrix, list)
• 11.2 BFS
• 11.3 DFS
• 11.4 Dijkstra
• 11.5 Bellman-Ford
• 11.6 Floyd-Warshall
• 11.7 Topological Sort
• 11.8 Tarjan's SCC
• 11.9 A* Search
• 11.10 Minimum Spanning Tree (Kruskal, Prim)

12. Disjoint Set (Union-Find)¶

• 12.1 Union-Find
• 12.2 Path Compression
• 12.3 Union by Rank
• 12.4 Offline LCA

13. Dynamic Programming¶

• 13.1 Memoization vs Tabulation
• 13.2 Knapsack (0/1, unbounded)
• 13.3 LCS / LIS
• 13.4 Edit Distance
• 13.5 Interval DP
• 13.6 Bitmask DP
• 13.7 Tree DP
• 13.8 Digit DP

14. Greedy Algorithms¶

• 14.1 Activity Selection
• 14.2 Huffman Coding
• 14.3 Fractional Knapsack
• 14.4 Job Scheduling
• 14.5 Exchange Argument

15. Divide & Conquer¶

• 15.1 Merge Sort
• 15.2 Quicksort
• 15.3 Master Theorem
• 15.4 Karatsuba Multiplication
• 15.5 FFT

16. Backtracking¶

• 16.1 N-Queens
• 16.2 Sudoku Solver
• 16.3 Permutations & Subsets
• 16.4 Constraint Satisfaction

17. String Algorithms¶

• 17.1 KMP
• 17.2 Z-Function
• 17.3 Rabin-Karp
• 17.4 Suffix Arrays
• 17.5 Aho-Corasick
• 17.6 Edit Distance
• 17.7 Tries (string-focused)

18. Bit Manipulation¶

• 18.1 Bit Tricks
• 18.2 XOR Pairing
• 18.3 Bitmask Enumeration
• 18.4 Bit-Parallel Algorithms

19. Number Theory¶

• 19.1 GCD / LCM
• 19.2 Modular Arithmetic
• 19.3 Prime Sieves
• 19.4 Fermat's Little Theorem / Euler's Totient
• 19.5 Chinese Remainder Theorem (CRT)

20. Computational Geometry¶

• 20.1 Convex Hull
• 20.2 Line Intersection
• 20.3 Point in Polygon
• 20.4 KD-Tree
• 20.5 Sweep Line

21. Advanced Data Structures¶

• 21.1 LRU Cache
• 21.2 Bloom Filter
• 21.3 Skip List
• 21.4 LSM Tree
• 21.5 Merkle Tree
• 21.6 Rope

22. Randomized Algorithms¶

• 22.1 Reservoir Sampling
• 22.2 MinHash
• 22.3 Monte Carlo vs Las Vegas
• 22.4 Treap
• 22.5 Randomized Quicksort

23. Platforms to Practice¶

• 23.1 Leetcode
• 23.2 Edabit
• 23.3 Codeforces
• 23.4 HackerRank
• 23.5 AtCoder