DSA Roadmap
Data Structures and Algorithms is the discipline of selecting the right representation and procedure for each problem. This roadmap covers complexity, classic structures, graph problems, and optimization patterns used in technical interviews and production systems.
DSA Study Progress:
| # | DSA | Topic | Description |
|---|---|---|---|
| Phase 1: Foundations | |||
| 01 | Algorithms | Core concepts, categories, and trade-offs across common algorithm families. | |
| 02 | Complexity Analysis | Asymptotic analysis, Big O, and practical runtime/memory profiling. | |
| 03 | Data Structures | Arrays, linked structures, hash maps, stacks, queues, trees, and heaps. | |
| Phase 2: Core Techniques | |||
| 04 | Searching | Linear, binary, and structured search strategies. | |
| 05 | Sorting | Comparison and non-comparison sorts with stability/performance trade-offs. | |
| 06 | Trees & Heaps | Traversal patterns, balancing ideas, and priority queue operations. | |
| Phase 3: Advanced Problem Solving | |||
| 07 | Graph Algorithms | Graph traversal, shortest path, and connectivity methods. | |
| 08 | Dynamic Programming | Subproblem decomposition, memoization, and tabulation workflows. | |
| 09 | Greedy Algorithms | Local-optimum strategies and proofs of correctness. | |
| 10 | Advanced Techniques | Backtracking, branch-and-bound, randomized and approximation methods. | |