Blinkit SDE Interview Questions and Answers

To find the top 10 selling products, sort the products by their sales count in descending order and select the first 10.

• Sort the products by their sales count in descending order

• Select the first 10 products from the sorted list

Design a valet parking lot with ticket assignment and car retrieval using best fit and nearest distance.

• Create a parking lot with designated spots for each size of car

• Assign a ticket to the customer upon entry and record the spot number

• Retrieve the car by searching for the nearest available spot of the appropriate size

• Use best fit algorithm to minimize empty spots

• Implement a system for payment upon exit

Find total possible valid unique combinations of given number of pairs of parenthesis without duplicity.

• Use recursion to generate all possible combinations

• Check for validity of each combination using a stack

• Use a set to avoid duplicity

Construct a binary tree from in-order traversal with nodes greater than left and right child.

• The root node will be the maximum value in the in-order traversal

• Recursively construct the left and right subtrees using the left and right portions of the in-order traversal

• Repeat until all nodes are added to the tree

An algorithm to find top 10 trending words inserted by users in sites like Twitter.

• Collect a large dataset of tweets

• Tokenize the tweets into individual words

• Remove stop words and punctuation

• Count the frequency of each word

• Sort the words by frequency in descending order

• Select the top 10 words

Find the first occurrence of 1 in a sorted binary array.

• Use binary search to find the first occurrence of 1.

• If the mid element is 1, check if it's the first occurrence or if the element before it is 0.

• If the mid element is 0, search in the right half of the array.

• If the mid element is 1 and the element before it is also 1, search in the left half of the array.

Remove duplicates from a string in O(n) without using hash

• Use an array of boolean values to keep track of characters already seen

• Iterate through the string and mark characters as seen in the array

• If a character has already been seen, remove it from the string

Find the first occurrence of 1 in a sorted infinite binary tree.

• Use binary search to traverse the tree.

• If the current node is 1, check if its left child is also 1. If yes, move to the left subtree, else return the current node.

• If the current node is 0, move to the right subtree.

• Repeat until the first occurrence of 1 is found or the tree is exhausted.

Find the second largest element in an array.

• Sort the array and return the second last element

• Iterate through the array and keep track of the two largest elements

• Use a priority queue to find the second largest element

Given a sorted array with repeated elements, find the occurrence of a given element using binary search.

• Use binary search to find the first occurrence of the element

• Use binary search to find the last occurrence of the element

• Calculate the occurrence by subtracting the indices of the last and first occurrences and adding 1

Implement a data structure and algorithm to print all files in a directory, including sub-directories.

• Use an n-ary tree or stack to represent the directory structure

• Implement a BFS or DFS algorithm to traverse the directory and print files

• Handle sub-directories recursively

• Consider using a queue or stack to keep track of directories to visit

Print a matrix diagonally.

• Start from the top left corner and print the diagonal elements

• Move down and right to print the next diagonal

• Repeat until all diagonals are printed

DFS is a traversal algorithm used to visit all nodes of a tree or graph. It can be applied to binary as well as n-ary trees.

• DFS stands for Depth First Search.

• In DFS, we start from the root node and visit its children recursively until we reach a leaf node.

• There are two types of DFS: Preorder (root, left, right) and Postorder (left, right, root).

• DFS can be implemented using recursion or a stack data structure.

• Example: I...read more

Heaps allow efficient insertion and deletion of elements, unlike arrays.

• Heaps are useful for implementing priority queues.

• Insertion and deletion of elements in a heap take O(log n) time, while in an array it takes O(n) time.

• Heaps are dynamically resizable, unlike arrays which have a fixed size.

• Heaps can be used to efficiently find the kth largest/smallest element in an array.

• Examples of heap data structures include bin

Find the 2nd minimum element from an array.

• Sort the array and return the second element.

• Use a loop to find the minimum and second minimum elements.

• Initialize two variables to store the minimum and second minimum elements.

Construct a mirror tree from a given tree and return the root of the mirror tree.

• Traverse the given tree in a recursive manner.

• Swap the left and right child of each node.

• Return the root of the mirror tree.

Level order traversal of a tree is a method to visit all the nodes of a tree level by level.

• Use a queue to store the nodes of the tree

• Start with the root node and enqueue it

• While the queue is not empty, dequeue a node and visit it

• Enqueue the left and right child of the visited node if they exist

• Repeat until all nodes are visited

Sort a stack using recursion.

• Pop the top element from the stack and recursively sort the remaining stack.

• Insert the popped element in the correct position in the sorted stack.

• Repeat until the entire stack is sorted.

• Use a helper function to insert the element in the correct position.

• Time complexity: O(n^2), space complexity: O(n) due to recursion.

• Example: Input stack - [5, 2, 7, 1], Output stack - [1, 2, 5, 7]

Populate sibling of a tree node with next node in same level with O(1) space complexity.

• Traverse the tree level by level using BFS.

• For each node, check if it has a sibling to its right.

• If yes, populate the sibling pointer of the current node with the right sibling.

• If no, move to the next level.

• Repeat until all levels are traversed.

When you type amazon.com in a browser, it sends a request to the Amazon servers, which then respond by sending back the website's content to be displayed on your screen.

• Browser sends a DNS request to resolve the domain name 'amazon.com' to an IP address

• Browser establishes a TCP connection with the Amazon servers

• Browser sends an HTTP request to the Amazon servers for the website content

• Amazon servers process the request...read more

The longest continuous patch of a road being repaired by a contractor is determined.

• Iterate through the updates and keep track of the start and end points of each patch

• Calculate the length of each patch and update the longest patch if necessary

• Return the start and end points of the longest patch

The program counts the number of tree structures that can be made using n nodes.

• Use dynamic programming to solve the problem efficiently

• Break down the problem into subproblems and store their solutions in an array

• Iterate through the array to calculate the number of tree structures

• The time complexity of the program is O(n^2)

Arrange nuts and bolts so that every nut fits perfectly with the bolt in the same position.

• Sort both arrays in the same order using a comparison function

• Use a binary search to find the matching bolt for each nut

• Repeat until all nuts are matched with bolts

Seeking new challenges and growth opportunities

• Desire for career advancement

• Limited growth opportunities in current role

• Seeking new challenges and learning experiences

A tree is a data structure consisting of nodes connected by edges, with a single root node and no cycles.

• Nodes represent elements of the tree, and edges represent the relationships between them.

• Each node can have zero or more child nodes, and each child node can have its own children.

• Trees are commonly used in computer science for organizing and searching data, such as in binary search trees.

• Examples of trees include f...read more

Graphs are non-linear data structures with cycles while trees are hierarchical data structures without cycles.

• Graphs can have cycles while trees cannot

• Graphs can have multiple root nodes while trees have only one

• Graphs can have disconnected components while trees are always connected

• Graphs can have directed or undirected edges while trees have only directed edges

• Examples of graphs include social networks, road networks...read more

A graph can be called a tree if it is connected and has no cycles.

• A tree is a type of graph with no cycles.

• It must be connected, meaning there is a path between any two vertices.

• It has n-1 edges, where n is the number of vertices.

• Examples include family trees, file directory structures, and decision trees.

Program to determine if a graph is a tree using adjacency matrix

• A graph is a tree if it is connected and has no cycles

• Check if the graph is connected by performing a depth-first search or breadth-first search

• Check if the graph has cycles by performing a depth-first search and tracking visited nodes

Seeking better growth opportunities and a more challenging role.

• Limited growth opportunities in my current company

• Looking for a more challenging role to enhance my skills

• Seeking a company with a better work culture and values

• Exploring options that align better with my long-term career goals

A thread is a unit of execution within a process that can run independently and concurrently with other threads.

• Threads allow for concurrent execution of tasks within a program.

• Threads share the same memory space and resources of the process they belong to.

• Threads can communicate and synchronize with each other through shared data structures like locks and semaphores.

• Threads can improve performance by utilizing multipl...read more

Memory leakage is a situation where a program fails to release memory it no longer needs.

• Memory leakage can cause a program to slow down or crash due to insufficient memory.

• It is caused by programming errors such as not freeing allocated memory or losing references to it.

• Examples include forgetting to close a file or database connection, or not releasing memory allocated for a variable.

• Memory leakage can be detected us...read more

Design a system using Max Heap to find the costliest element from a box when an element is picked.

• Implement a Max Heap data structure to store the elements in the box.

• Whenever an element is picked, the costliest element can be found at the root of the Max Heap.

• After picking an element, update the Max Heap by removing the root and reorganizing the heap.

• Ensure the Max Heap property is maintained during insertion and dele...read more

LRU cache is a data structure that stores most recently used items and discards least recently used items.

• LRU stands for Least Recently Used

• It is implemented using a doubly linked list and a hash map

• When an item is accessed, it is moved to the front of the list

• When the cache is full, the least recently used item is removed from the end of the list

• Example: A web browser cache that stores recently visited web pages