Learn Smarter with Real Mentors

Let’s be real for a second: preparing for a Google interview isn’t easy. It’s not just about solving problems, it’s about solving the right problems in the right way — under pressure, with clean code, and while explaining your thinking out loud. That takes more than just grind; it takes strategy.

As someone navigating the early stages of my career, I know how overwhelming it can feel. There are hundreds of questions, dozens of topics, and too little time. That’s why having a clear roadmap matters. And even better? Having mentors who’ve already walked the path.

This blog is my attempt to simplify your journey. Below, you’ll find 50 of the most frequently asked Data Structures & Algorithms (DSA) questions that appear in Google’s coding interviews. I’ve also included how to practice smart, not just hard.

💡 Want guidance from real IITian mentors who’ve cracked these interviews? Check out CodingWithIITians.com — structured learning, live classes, and real results.

Why Google Cares About DSA

Google’s coding interviews are designed to test more than your ability to write code. They want to see how you:

  • Think under time pressure
  • Solve problems logically and optimally
  • Handle edge cases
  • Communicate your thought process clearly

You don’t just need the answer. You need to justify why it’s the best one. That’s why strong foundations in DSA matter so much. Let’s look at the questions.

The Top 50 DSA Questions (Grouped by Topic)

Arrays & Strings

  1. Two Sum
  2. Longest Substring Without Repeating Characters
  3. Merge Intervals
  4. Trapping Rain Water
  5. Product of Array Except Self
  6. Container With Most Water
  7. Maximum Subarray (Kadane’s Algorithm)
  8. Longest Palindromic Substring
  9. Set Matrix Zeroes
  10. Rotate Image

Linked Lists

  1. Reverse Linked List
  2. Detect Cycle in Linked List
  3. Merge Two Sorted Lists
  4. Remove N-th Node From End
  5. Copy List with Random Pointer
  6. Intersection of Two Linked Lists
  7. Add Two Numbers

Trees & BSTs

  1. Inorder Traversal (Recursive & Iterative)
  2. Validate Binary Search Tree
  3. Lowest Common Ancestor
  4. Level Order Traversal
  5. Serialize & Deserialize Binary Tree
  6. Maximum Path Sum
  7. Convert Sorted Array to BST

Recursion & Backtracking

  1. Subsets
  2. Permutations
  3. Combination Sum
  4. N-Queens Problem
  5. Sudoku Solver
  6. Word Search

Dynamic Programming

  1. Climbing Stairs
  2. House Robber
  3. Longest Increasing Subsequence
  4. 0/1 Knapsack
  5. Coin Change
  6. Palindromic Substrings
  7. Edit Distance
  8. Target Sum
  9. Best Time to Buy & Sell Stock (I, II, III)

Graphs & Greedy

  1. Number of Islands
  2. Clone Graph
  3. Course Schedule (Topological Sort)
  4. Dijkstra’s Algorithm
  5. Detect Cycle in Directed Graph
  6. Minimum Spanning Tree (Kruskal/Prim)
  7. Word Ladder

Heaps & Advanced Topics

  1. Merge K Sorted Lists
  2. Find Median from Data Stream
  3. Top K Frequent Elements
  4. K Closest Points to Origin

How to Practice Effectively (From Someone Still Learning Too)

If you’re like me, you’ve probably felt the pressure to “finish the whole LeetCode list” in one go. Truth is, you don’t need to solve all the questions to succeed — you just need to solve the right ones well.

Here’s what works:

  • Start with concepts. Don’t memorize solutions.
  • Brute-force first, then optimize step-by-step.
  • Use a timer. Practice solving under 30 minutes.
  • Speak aloud. Pretend you’re explaining to an interviewer.
  • Revisit problems after 1–2 weeks to retain logic.

And most importantly? Track what you’re weak at. For me, that was Graphs. For you, it might be DP or Backtracking. Identify it early.

Why I Recommend CodingWithIITians.com

I stumbled upon CodingWithIITians.com during a late-night prep session, and I genuinely think it’s worth checking out. Here’s why:

  • Mentors from Amazon, Google, Uber (IIT alumni)
  • Live structured DSA classes with assignments
  • Mock interviews & resume reviews
  • 12-week roadmap built for FAANG-level prep

I wanted more than YouTube tutorials. I wanted real feedback, real deadlines, and mentors who’ve sat in Google interview rooms. That’s what this platform gives.

Final Thoughts: You Don’t Need to Be a Genius

If you’ve read this far, you’re already serious about your prep. And that’s what matters.

You don’t need to be a genius. You just need:

  • Curiosity
  • Consistency
  • And the courage to keep going even when it’s tough

Solve a few problems every day. Be okay with failing. Keep learning. And trust that all the effort will add up.

📌 Ready to get serious with your prep? Explore the programs at CodingWithIITians.com

Let’s crack it together.

❓ FAQ 1: Why does Google focus so much on Data Structures & Algorithms in interviews?

Google wants to see how candidates think, analyze, and solve problems efficiently. Data Structures & Algorithms (DSA) are the backbone of scalable systems. By testing them, interviewers assess your ability to:
1. Write optimized code
2. Handle large-scale data
3. Apply logical problem-solving under pressure

❓ FAQ 2: How can I prepare effectively for Google’s DSA interview?

1. Master the basics: Arrays, Strings, Linked Lists, Trees, Graphs, Stacks, Queues.
2. Practice problem-solving on platforms like LeetCode, HackerRank, or Codeforces.
3. Focus on time & space complexity analysis.
4. Simulate interviews: Do timed mock interviews to build confidence.

❓ FAQ 3: Do I need to memorize all 50+ DSA problems for Google interviews?

No 🚫, you don’t need to memorize answers. Instead, focus on patterns and problem-solving strategies. Google interviewers often twist problems. If you know how to approach recursion, dynamic programming, and graph traversal, you’ll handle variations easily.

❓ FAQ 4: How much time should I spend preparing for a Google interview?

It depends on your current level:
Beginner: 6–8 months (daily practice)
Intermediate: 3–4 months (focused revision & problem sets)
Experienced engineers: 1–2 months (brushing up on weak areas + mock interviews)
Consistency is more important than cramming. 🚀

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