Welcome to your DSA journey with JavaScript! This roadmap is designed to build strong problem-solving skills, improve algorithmic thinking, and prepare you for technical interviews.
- Master core data structures and algorithms using JavaScript
- Build strong intuition for optimizing time and space complexity
- Solve real-world coding problems and crack interviews with confidence
- [β ] Big O Notation (Time & Space)
- [β
] Common Complexities (
O(1),O(n),O(log n), etc.) - [β ] Analyzing Loops and Nested Structures
- [β ] Memory Usage
- [β ] Arrays
- [β ] Strings
- [β ] Stacks
- Queues
- Singly Linked Lists
- Doubly Linked Lists
- Trees (Binary Tree, BST)
- Heaps (Min/Max)
- Tries
- Graphs (Adjacency List, Matrix)
- Sets and Maps (Hash Tables)
- Recursion
- Iteration vs Recursion
- Backtracking
- Linear Search
- Binary Search
- BFS & DFS (Trees & Graphs)
- Bubble Sort
- Selection Sort
- Insertion Sort
- Merge Sort
- Quick Sort
- Two-Pointer Pattern
- Sliding Window
- Divide & Conquer
- Greedy Algorithms
- Dynamic Programming (Memoization & Tabulation)
- Easy: 30β40 LeetCode-style problems
- Medium: 40β50 real-world problems
- Hard: 20+ advanced problems
- Mock Interview Rounds
- Editor: VS Code or LeetCode Playground
- Track Progress: GitHub, Notion, or this README
- Practice Sites: LeetCode, HackerRank, CodeSignal
- Visual Tools: visualgo.net, bigocheatsheet.com
| Phase | Topic | Status |
|---|---|---|
| 1 | Time & Space Complexity | β Completed |
| 2 | Arrays | β¬ Not Started |
| 2 | Strings | β¬ Not Started |
| 3 | Sorting Algorithms | β¬ Not Started |
| 3 | Recursion | β¬ Not Started |
| 4 | Mock Interviews | β¬ Not Started |
"Data Structures + Algorithms = Programs." β Niklaus Wirth