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Google SDE Sheet: Interview Questions and Answers

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  • Difficulty Level :Medium
  • Last Updated :13 Sep, 2022
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Google is an American multinational technology company specializing in search engine technology, online advertising, cloud computing, computer software, quantum computing, e-commerce, and artificial intelligence. It is a dream of many people to work for Google. This sheet will assist you to land a job at Google, we have compiled all the interview questions and answers..

Google SDE Sheet

For top companies like Google, one must have solid Data Structure concepts, good communication skills, and an analytical mindset. Steps to follow to get a chance at Google are:

  • Online Application
  • Online assessments: After Google approves your application (resume/cover letter), you will be required to take an online assessment. Here’s an overview of the online assessment:
    Number of questions: 2 questions
    Time allowed: 90 minutes
    Topics: typical algorithm/data structure questions
  • Technical Phone Screen: (30-60 minutes) Google’s interview process begins with a technical phone interview for experienced software engineers. During this stage, tech leads conduct interviews via Google Meet or Hangouts.
  • Onsite: Onsite is the last stop. On average, 4 to 6 rounds should be finished in a day. Each round should take around 45 minutes and include questions on both system design and code. Interviewees note that more coding is done than system design, and expectations change depending on your skill level.
  • Behavioral Skills(Googleyness): As part of its hiring process, Google wants to determine whether a potential employee has “Googleyness”, a value that the company uses to describe those who are culturally fit.

Google SDE Roadmap


Why this sheet?

Google coding interviews can be a tough nut to crack. The questions in google interviews cover a wide range of topics and are difficult and specific to Google. This sheet is like a helping hand for those preparing to get a job at Google. It covers all the important and popular technical questions asked in Google Interviews so far. Questions in this sheet are grouped topic-wise and cover all major DSA topics that have weightage in Google interviews.

Computer Science Concepts: Google focuses on the following Computer Science Subjects in their interviews:

Data Structure & Algorithms

Array: An array is a collection of items stored at contiguous memory locations. The idea is to store multiple items of the same type together.

Wave ArraySolve
Subarray with given sumSolve
Majority ElementSolve
Peak elementSolve
Three Sum ClosestSolve
Number of subarrays having sum exactly equal to kSolve
Kadane’s AlgorithmSolve
Find the element that appears onceSolve
Find the minimum element in a sorted and rotated arraySolve
Search a Word in a 2D Grid of charactersSolve
Max sum of M non-overlapping subarrays of size KSolve
Find Surpasser Count of each element in arraySolve
Smallest Absolute DifferenceSolve
Sum of bit differences among all pairsSolve
Count More than n/k OccurrencesSolve
Capacity To Ship Packages Within D DaysSolve

String: Strings are defined as an array of characters. The difference between a character array and a string is the string is terminated with a special character ‘\0’.

Valid ExpressionSolve
Multiply Large Numbers represented as StringsSolve
Minimum indexed characterSolve
Find Maximum number possible by doing at-most K swapsSolve
How to replace a substring of a stringSolve
Uncommon charactersSolve
License Key FormattingSolve
Minimum insertions to form a palindromeSolve
Longest Repeating SubsequenceSolve
Alien DictionarySolve
Anagram PalindromeSolve
Longest Palindromic SubstringSolve
Rabin-Karp Algorithm for Pattern SearchingSolve
Longest prefix which is also suffixSolve

Linked List: A linked list is a linear data structure, in which the elements are not stored at contiguous memory locations.

Nth node from end of linked listSolve
Reverse a linked listSolve
Detect loop in a linked listSolve
Delete a Node from linked list without head pointerSolve
Find length of LoopSolve
Insert in a Sorted ListSolve
Pairwise Swap Nodes of a given Linked ListSolve
Sort a linked list of 0s, 1s and 2sSolve
Reverse a sublist of a linked listSolve

Stack and Queue:

  • Stack: A stack is a linear data structure in which elements can be inserted and deleted only from one side of the list, called the top. A stack follows the LIFO (Last In First Out) principle.
  • Queue: A queue is a linear data structure in which elements can be inserted only from one side of the list called rear, and the elements can be deleted only from the other side called the front. The queue data structure follows the FIFO (First In First Out) principle.
The Celebrity ProblemSolve
Maximum Rectangular Area in a HistogramSolve
Max rectangleSolve
Length of the longest valid substringSolve
Find the first circular tour that visits all petrol pumpsSolve
LRU Cache ImplementationSolve
Minimum time required to rot all orangesSolve
Sliding Window Maximum (Maximum of all subarrays of size k)Solve

Searching: Searching Algorithms are designed to check for an element or retrieve an element from any data structure where it is stored.

Subarray with given sumSolve
Kth smallest elementSolve
Find a peak elementSolve
Search in a Rotated ArraySolve
The Painter’s Partition Problem-IISolve
Minimum number of times A has to be repeated such that B is a substring of itSolve
Koko Eating BananasSolve
Next greater number set digitsSolve
Median of 2 Sorted Arrays of Different SizesSolve
Maximum no of 1’s rowSolve
Elements in the RangeSolve

Sorting: A Sorting Algorithm is used to rearrange a given array or list of elements according to a comparison operator on the elements. The comparison operator is used to decide the new order of elements in the respective data structure.

Floor in a Sorted ArraySolve
Find all triplets with zero sumSolve
Count InversionsSolve
Sort an array of 0s, 1s and 2sSolve
Minimum PlatformsSolve
Count the number of possible trianglesSolve
At least two greater elementsSolve
Maximum Intervals OverlapSolve
Next Greater Even NumberSolve
Count Smaller elementsSolve
Chocolate Distribution ProblemSolve

Hash and Heap:

  • Hash: Hashing is a technique or process of mapping keys, and values into the hash table by using a hash function. It is done for faster access to elements. The efficiency of mapping depends on the efficiency of the hash function used
  • Heap: A Heap is a special Tree-based data structure in which the tree is a complete binary tree. Heap and hash is an efficient implementation of a priority queue. The linear hash function monotonically maps keys to buckets, and each bucket is a heap.
Count pairs with given sumSolve
Longest Consecutive SubsequenceSolve
Triplet Sum in ArraySolve
Largest subarray of 0’s and 1’sSolve
Find median in a streamSolve
Longest K unique characters substringSolve
Winner of an electionSolve
Binary Heap OperationsSolve
Kth element in MatrixSolve
Game with StringSolve
Rearrange charactersSolve

Trees: A tree is non-linear and a hierarchical data structure consisting of a collection of nodes such that each node of the tree stores a value, a list of references to nodes (the “children”). :

Print leaf nodes from preorder traversal of BSTSolve
Height of Binary TreeSolve
ZigZag Tree TraversalSolve
Left View of Binary TreeSolve
Boundary Traversal of binary treeSolve
Lowest Common Ancestor in a Binary TreeSolve
Bottom View of Binary TreeSolve
Mirror TreeSolve
Sorted Link List to BSTSolve
k-th smallest element in BSTSolve
Merge two BST ‘sSolve
Maximum path sum from any nodeSolve
Maximum sum of Non-adjacent nodesSolve
Root to leaf paths sumSolve
Maximum Path Sum between 2 Leaf NodesSolve
Count BST nodes that lie in a given rangeSolve
Connect Nodes at Same LevelSolve

Graph: A Graph is a non-linear data structure consisting of nodes and edges. The nodes are sometimes also referred to as vertices and the edges are lines or arcs that connect any two nodes in the graph.

Dijkstra’s shortest path algorithmSolve
Find the number of islandsSolve
Unit Area of largest region of 1’sSolve
Word BoggleSolve
Prerequisite TasksSolve
Flood fill AlgorithmSolve
X Total ShapesSolve
Number of ProvincesSolve
Word Ladder ISolve
Knight WalkSolve
Course ScheduleSolve
Assignment ProblemSolve
Clone GraphSolve
Find the StringSolve

Dynamic Programming: Dynamic Programming is mainly an optimization over plain recursion. Wherever we see a recursive solution that has repeated calls for same inputs, we can optimize it using Dynamic Programming.

Trapping Rain WaterSolve
Maximum Product SubarraySolve
Stock buy and sellSolve
Interleaved StringsSolve
Stickler ThiefSolve
Smallest window in a string containing all the characters of another stringSolve
Max rectangleSolve
Activity SelectionSolve
Jump GameSolve
Knapsack with Duplicate ItemsSolve
Wildcard Pattern MatchingSolve
Total Decoding MessagesSolve
Matrix Chain MultiplicationSolve
Count occurences of a given word in a 2-d arraySolve
Brackets in Matrix Chain MultiplicationSolve
Burst Balloon to maximize coinsSolve


Thoroughly revise all the work you have done till now in your projects. The grilling about projects can sometimes be very deep. Also, choose your words before you speak. Mention only those topics where you think you are fine to be grilled upon. If you haven’t made a project then take an idea from GFG Projects and start working on it.

System Design

System Design is the process of designing the architecture, components, and interfaces for a system so that it meets the end-user requirements. System Design for tech interviews is something that can’t be ignored!

Almost every IT giant whether it be Facebook, Amazon, Google, or any other asks various questions based on System Design concepts such as scalability, load-balancing, caching, etc. in the interview.

This specifically designed System Design tutorial & System Design Course will help you to learn and master System Design concepts in the most efficient way from basics to advanced level.

Behavioral Skills

Many people are very afraid of behavioural interview questions in technical interviews as they seem to be just something most programmers are not good at. Do you know that less than 10% of candidates passed their on-site interviews as reported in Silicon Valley? Don’t forget that those who failed have already passed the phone screen.

My Personal Notesarrow_drop_up
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