🚀 Day 15 of my journey to becoming an L5-L6 developer!
📚 Topics Covered So Far:
Array & Hashing
Two Pointers
Sliding Window
Stack
Binary Search
Queue
Priority Queue
Linked List
Trees
Recursion
Graphs
Dynamic Programming
Backtracking
🎩 Pro Tips & Personal Insights:
Two Pointers: Like sliding windows, but with limited pointers. Great for optimizing solutions.
Sliding Window: Start with a valid window, add items, and remove them if the window becomes invalid.
Stack: Think of it as a place to store things for later, in reverse recursive order.
Binary Search: The magic of reducing your domain on every step to find the item efficiently.
Linked List: A node that knows only about its adjacent nodes.
Trees: Do things for one node, then make it recursive for all. Like a domino effect!
Recursion: A powerful tool to solve problems by breaking them down into smaller, manageable pieces.
Dynamic Programming: Solve via recursion, add cache, convert into iterative solution, then optimize space. Voila!
Backtracking: When you need to explore all possible solutions without getting lost. Think of it as your problem-solving GPS.
Here’s a neat trick for backtracking:
def rec(i):
backtrack_arr.append(s[i])
rec(i+1)
backtrack_arr.pop()
🚀 Excited to dive deeper into DSA and reach my goal of becoming an L5-L6 developer! 💪 Follow along for more updates and tips!
📖 Following the roadmap on https://neetcode.io to master DSA!
