Round 1: Coding Interview
Questions:
Problem 1: Contiguous Sequence Sums to Given Integer
Given an array of integers and a target sum, determine if a contiguous subarray sums up to the target.
Problem 2: Range Sum in a Binary Search Tree
Given a BST and a range [low, high], return the sum of all values in the BST within that range.
Problem 3: Copy Linked List with Random Pointer
Given a singly linked list where each node has an additional random pointer, create a deep copy of the list.
Problem 4: Populate Next Pointer in a Binary Tree
Given a binary tree, populate each node’s next pointer to its right neighbor at the same level.
Candidate's Approach
- For Problem 1, I used a prefix sum approach with a hash set for an efficient solution. However, I missed the sliding window approach when the interviewer asked to optimize space to O(1).
- For Problem 2, I implemented a DFS approach to traverse the tree and accumulate the sum efficiently.
- For Problem 3, I discussed both a hashmap-based approach and an in-place modification strategy, mentioning the interweaven approach as well.
- For Problem 4, I utilized a level-order traversal approach with a queue to link nodes efficiently.
Interviewer's Feedback
No feedback provided.
Round 2: System Design Interview
Questions:
LeetCode System Design
Discussed how to design an online coding judge that supports multiple concurrent competitions.
Ad Click Aggregator
Designed a system to aggregate ad clicks and generate real-time analytics for advertisers.
Candidate's Approach
- For the online coding judge, I focused on scalable architecture, leaderboard updates, and handling real-time scoring.
- For the ad click aggregator, I discussed event-driven architecture, partitioning strategies, and data consistency challenges.
Interviewer's Feedback
No feedback provided.
Round 3: Behavioral Interview
Questions:
- Tell me about yourself
- The project you’re most proud of
- The most difficult person you had to deal with
- Many follow-up questions digging deeper into my responses
Candidate's Approach
I used CARL (Context, Action, Result, Learning) instead of STAR (Situation, Task, Action, Result) because it aligns with how I process and share information. CARL helped me highlight not just the events but also the key takeaways from each experience.
Interviewer's Feedback
No feedback provided.