iwantcoding.com
🔥 Daily 👥 Rooms 🏆 Top Log in Sign up
Next »

Summary

By · Reviewed & last updated · Part of Data Structures & Algorithms

Wrapping up the DSA track with what you can solve and where to push next.

What you learned + LRU cache

EXAMPLE
# DSA summary

You can now:

- Read a problem and recognise the underlying pattern
- Walk through brute force + complexity before coding
- Apply two pointers, sliding window, prefix sums on arrays
- Use hashing for set/dedup/index problems
- Traverse trees and graphs (BFS/DFS) and choose the right one
- Use union-find for connectivity problems
- Apply 1D and 2D dynamic programming when overlapping subproblems show up
- Reason about heaps for top-K and merge-K
- Design simple systems: LRU cache, rate limiter, mini scheduler

# Your next step - an LRU cache in TypeScript

class LRU<K, V> {
  private map = new Map<K, V>();
  constructor(private capacity: number) {}

  get(key: K): V | undefined {
    if (!this.map.has(key)) return undefined;
    const value = this.map.get(key)!;
    this.map.delete(key);
    this.map.set(key, value);   // move to end (most recent)
    return value;
  }

  set(key: K, value: V): void {
    if (this.map.has(key)) this.map.delete(key);
    else if (this.map.size >= this.capacity) {
      const first = this.map.keys().next().value;
      this.map.delete(first);   // evict oldest
    }
    this.map.set(key, value);
  }
}

Why it matters

Patterns transfer. Memorising 300 problems does not. If you can articulate which pattern fits before you code, you have the skill the interviews are really testing.

Tip: Tweak the snippet with Try it Yourself », then sit the quiz at the bottom of the page.

Example

Example
// Next: segment trees, persistent data structures, advanced graph algos, competitive programming.
Try it Yourself »

Discussion

Loading…

Next »