4 mins to read Google is known for asking challenging and creative interview questions that assess a candidate’s problem-solving abilities, analytical thinking, and coding skills. While the specific questions may vary, here are 13 tough and frequently asked questions that have been reported in Google interviews:
1. Reverse a Linked List:
This question typically asks you to reverse a singly linked list in place. You need to traverse the list while reassigning pointers to reverse the order of nodes.
The iterative approach involves maintaining three-pointers (current, previous, and next) to reverse the list efficiently.
Recursive solutions are also possible but might require additional space on the call stack.
Key concepts: Linked lists, pointers, in-place reversal.
2. Find the Missing Number:
Given an array of distinct numbers from 0 to n with one number missing, you’re asked to find the missing number.
A common solution involves calculating the expected sum of the numbers from 0 to n and subtracting the actual sum of the array elements.
Alternatively, you can use XOR operations to find the missing number.
Key concepts: Array manipulation, mathematical reasoning.
3. Merge Intervals:
Given a collection of intervals (e.g., [1,3], [2,6], [8,10]), you’re asked to merge overlapping intervals into non-overlapping ones (e.g., [1,6], [8,10]).
Sort the intervals by their start times and then merge overlapping intervals while iterating through the sorted list.
Key concepts: Sorting, interval merging.
4. Design a Distributed System:
This is a system design question where you need to design a distributed system that can handle a specific use case or load. The complexity can vary based on the scenario given.
Focus on scalability, fault tolerance, data consistency, and other distributed system principles.
Key concepts: System design, distributed systems, trade-offs.
5. Implement a Search Engine:
You’re tasked with designing and implementing a basic search engine, which involves components like web crawling, indexing, and ranking algorithms.
Discuss data storage, retrieval, and scalability aspects.
Key concepts: Information retrieval, data structures, algorithms.
6. Find the Shortest Path in a Graph:
Given a graph, find the shortest path between two nodes. Dijkstra’s algorithm and A* search algorithm are common approaches.
Consider the type of graph (weighted, unweighted), and discuss trade-offs between algorithms.
Key concepts: Graph algorithms, shortest path.
7. Design a Cache:
Design a cache that efficiently stores and retrieves data with defined eviction policies like LRU (Least Recently Used) or LFU (Least Frequently Used).
Explain how your cache would handle different workloads.
Key concepts: Cache design, eviction policies.
8. Serialize and Deserialize a Binary Tree:
Implement functions to serialize a binary tree into a string and deserialize it back into a binary tree.
Various serialization formats (e.g., preorder traversal) can be used.
Key concepts: Binary trees, tree traversal.
9. Detect a Loop in a Linked List:
Determine if a linked list has a loop, and if so, find the starting node of the loop.
Use Floyd’s Tortoise and Hare algorithm for cycle detection.
Key concepts: Linked lists, cycle detection.
10. Substring with Concatenation of All Words:
Given a string and a list of words, find all starting indices of substrings that are concatenations of all words in the list.
Implement a sliding window approach to efficiently search for valid substrings.
Key concepts: String manipulation, sliding window.
11 Implement a Regular Expression Parser:
Create a function to implement regular expression matching with support for ‘.’ (matches any character) and ‘*’ (matches zero or more occurrences of the preceding character).
This typically involves dynamic programming or recursion.
Key concepts: Regular expressions, dynamic programming.
12. Find the Maximum Subarray Sum:
Given an integer array, find the contiguous subarray with the largest sum (the “maximum subarray”).
Implement Kadane’s algorithm or a divide-and-conquer approach to solve this efficiently.
Key concepts: Dynamic programming, array manipulation.
13. Design a Recommendation System:
In this system design question, you need to design a recommendation system for a specific use case like content or product recommendations.
Consider user profiling, recommendation algorithms (e.g., collaborative filtering), and scalability.
Key concepts: System design, recommendation algorithms.
Each of these questions assesses different skills and knowledge areas, so it’s crucial to thoroughly understand the underlying concepts and practice solving similar problems before a Google interview.