5 Days.
75 Problems.
1 Offer.
Structured day-by-day roadmap from arrays to system design. Every NeetCode 75 problem with brute-force → optimal solution. System design with ratios, trade-offs, and bottlenecks.
Master the HashMap pattern — it solves 40% of all array problems.
Binary search is a mindset — use it whenever you see 'sorted' or 'minimum/maximum k'.
Trees are the most common SDE 2 topic. Know recursive DFS cold.
DP = recursion + memoization. Draw the recurrence tree first.
System design wins SDE 2. Spend 5h on this day. Think in trade-offs.
Fundamentals & Numbers
Latency, CAP, availability, ratios, estimation
URL Shortener
Base62, hashing, caching, redirection at scale
Twitter / News Feed
Fan-out, celebrity problem, feed ranking
Uber
Geospatial matching, surge pricing, live location
Media pipeline, CDN, feed ranking, stories
Zomato
Restaurant search, order state machine, delivery matching
Rate Limiter
Token bucket, sliding window, Redis atomicity
Distributed Cache
Redis vs Memcached, eviction, consistency
Notification System
Multi-channel, dedup, retry, priority queues
| Problem Trigger | Pattern to Use | Complexity |
|---|---|---|
| Pair/triplet summing to X | Two Pointers or HashMap | O(n) |
| Longest/shortest subarray with constraint | Sliding Window | O(n) |
| Sorted array, find element | Binary Search | O(log n) |
| Tree path / depth | DFS (recursion) | O(n) |
| Shortest path (unweighted) | BFS (queue) | O(V+E) |
| Shortest path (weighted) | Dijkstra (min-heap) | O(E log V) |
| Detect cycle in graph | DFS with states / Union-Find | O(V+E) |
| Order with dependencies | Topological Sort | O(V+E) |
| Min/max over subproblems | Dynamic Programming | O(n²)–O(n·m) |
| K largest/smallest | Min-Heap of size K | O(n log k) |
| Overlapping intervals | Sort by start + stack/heap | O(n log n) |
| Palindrome / match | Expand from center / Two Pointers | O(n) |