Qualcomm Senior Java Developer Interview Questions and Answers

Round duration - 75 minutes
Round difficulty - Medium

This was an online coding round where I had 2 questions to solve under 75 minutes. Both the coding questions were of Medium to Hard level of difficulty.

Q1. 
Smallest Window Problem Statement
Given two strings, S and X, your task is to find the smallest substring in S that contains all the characters present in X.
Example:
Input:
S = "abdd"
X = "bd"
Output:
...read more
Ans. 
Find the smallest substring in S that contains all characters in X.
• Use a sliding window approach to find the smallest substring in S that contains all characters in X.

• Keep track of the characters in X using a hashmap.

• Move the window by adjusting the start and end pointers until all characters in X are found.

• Return the smallest substring encountered.
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Q2. 
K - Sum Path In A Binary Tree
Given a binary tree where each node contains an integer value, and a value 'K', your task is to find all the paths in the binary tree such that the sum of the node values in ...read more
Ans. 
Find all paths in a binary tree where the sum of node values equals a given value 'K'.
• Traverse the binary tree using DFS and keep track of the current path and its sum.

• At each node, check if the current sum equals 'K' and add the path to the result.

• Continue traversal to the left and right child nodes recursively.

• Return the list of paths that sum up to 'K'.
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Round duration - 60 Minutes
Round difficulty - Medium

This round had 2 questions of DS/Algo to solve under 60 minutes and 2 questions related to Operating Systems.

Q1. 
Validate Partial Binary Search Tree (BST) Problem Statement
You are provided with a binary tree containing 'N' nodes. Your task is to determine if this tree is a Partial Binary Search Tree (BST). Return t...read more
Ans. 
Validate if a binary tree is a Partial Binary Search Tree (BST) by checking if each node's left subtree contains nodes with data less than or equal to the node's data, and each node's right subtree contains nodes with data greater than or equal to the node's data.
• Check if each node's left subtree follows BST property (data <= node's data) and right subtree follows BST property (data >= node's data)

• Recursively che...read more
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Q2. 
Longest Increasing Subsequence Problem Statement
Given an array of integers with 'N' elements, determine the length of the longest subsequence where each element is greater than the previous element. This...read more
Ans. 
Find the length of the longest strictly increasing subsequence in an array of integers.
• Use dynamic programming to solve this problem efficiently.

• Initialize an array to store the length of the longest increasing subsequence ending at each index.

• Iterate through the array and update the length of the longest increasing subsequence for each element.

• Return the maximum value in the array as the result.
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Q3. Can you define process and threads in operating systems?
Ans. 
Processes are instances of a program in execution, while threads are lightweight processes within a process.
• A process is a program in execution, with its own memory space and resources.

• Threads are lightweight processes within a process, sharing the same memory space and resources.

• Processes are independent of each other, while threads within the same process can communicate and share data.

• Example: A web browser running ...read more
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Q4. What are the different types of semaphores?
Ans. 
Different types of semaphores include binary semaphores, counting semaphores, and mutex semaphores.
• Binary semaphores: Can only have two states - 0 or 1. Used for mutual exclusion.

• Counting semaphores: Can have multiple states. Used for managing resources with limited capacity.

• Mutex semaphores: Similar to binary semaphores but with additional features like priority inheritance.

• Named semaphores: Can be shared between proc...read more
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Round duration - 60 Minutes
Round difficulty - Hard

In this round, I was asked 3 coding questions out of which I had to implement the first two and for the last question I was only asked the optimal approach. The main challenge in this round was to implement the first two questions in a production ready manner without any bugs and so I had to spent some time thinking about some Edge Cases which were important with respect to the question.

Q1. 
Next Greater Element Problem Statement
You are given an array arr of length N. For each element in the array, find the next greater element (NGE) that appears to the right. If there is no such greater ele...read more
Ans. 
The task is to find the next greater element for each element in an array to its right, if no greater element exists, return -1.
• Use a stack to keep track of elements for which the next greater element is not found yet.

• Iterate through the array from right to left and pop elements from the stack until a greater element is found.

• Store the next greater element for each element in a separate array.

• If the stack is empty afte...read more
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Q2. 
Power Set Generation
Given a sorted array of 'N' integers, your task is to generate the power set for this array. Each subset of this power set should be individually sorted.
A power set of a set 'ARR' i...read more
Ans. 
Generate power set of a sorted array of integers with individually sorted subsets.
• Use recursion to generate all possible subsets by including or excluding each element in the array.

• Sort each subset before adding it to the power set.

• Handle base case when all elements have been considered to add the subset to the power set.
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Q3. 
Counting Sort Problem Statement
Ninja is learning about sorting algorithms, specifically those that do not rely on comparisons. Can you help Ninja implement the counting sort algorithm?
Example:
Input:
...read more
Ans. 
Implement counting sort algorithm to sort an array of integers without comparisons.
• Count the frequency of each element in the input array.

• Create a prefix sum array to determine the position of each element in the sorted array.

• Iterate through the input array and place each element in its correct position based on the prefix sum array.

• Time complexity of counting sort is O(n+k), where n is the number of elements and k is ...read more
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Q1. Salary discussion
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Hirepro , 2 easy to medium coding questions with technical questions

Q1. DSA questions were asked they were easy
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Q2. Insert a node at the middle of a linked list
Ans. 
To insert a node at the middle of a linked list, find the middle node and adjust pointers accordingly.
• Find the middle node using slow and fast pointers

• Adjust pointers to insert the new node at the middle
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Q1. Puzzle and general question
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Q1. Last Project details
Ans. 
Designed and implemented a cloud-based data analytics platform for real-time monitoring of network performance.
• Led a team of 5 engineers in developing the platform using AWS services such as EC2, S3, and Lambda functions

• Integrated data visualization tools like Tableau for generating reports and dashboards

• Implemented machine learning algorithms for predictive analysis of network outages

• Collaborated with stakeholders to ...read more
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Q2. SV -UVM questions
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Basic aptitude, c and data structures

Q1. C and data structures
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Q2. Operating system and puzzle
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Round duration - 75 minutes
Round difficulty - Medium

This was an online coding round where I had 2 questions to solve under 75 minutes. Both the coding questions were related to DP and were of Medium to Hard level of difficulty.

Q1. 
Longest Common Prime Subsequence Problem Statement
Imagine Ninja is tackling a puzzle during his long summer vacation. He has two arrays of integers, each with lengths 'N' and 'M'. Ninja's task is to dete...read more
Ans. 
Find the length of the longest subsequence common to two arrays consisting only of prime numbers.
• Iterate through both arrays to find prime numbers

• Use dynamic programming to find the longest common subsequence

• Consider edge cases like empty arrays or no common prime numbers
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Q2. 
Maximum Sum Problem Statement
You are given an array ARR of N integers. Your task is to perform operations on this array until it becomes empty, and maximize the sum of selected elements. In each operatio...read more
Ans. 
Given an array, select elements to maximize sum by removing adjacent elements. Return the maximum sum.
• Iterate through the array and keep track of the frequency of each element.

• Select the element with the highest frequency first, then remove adjacent elements.

• Repeat the process until the array becomes empty and calculate the sum of selected elements.
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Round duration - 60 minutes
Round difficulty - Medium

This round had 2 Algorithmic questions wherein I was supposed to code both the problems after discussing their approaches and respective time and space complexities . After that , I was grilled on some OOPS concepts related to C++.

Q1. 
Cycle Detection in a Linked List
Your task is to determine if a given Singly Linked List of integers forms a cycle.
Explanation: A cycle in a linked list occurs when there is a node in the list that conn...read more
Ans. 
Detect if a given singly linked list of integers forms a cycle.
• Use Floyd's Tortoise and Hare algorithm to detect cycle in linked list

• Maintain two pointers, one moving at double the speed of the other

• If they meet at some point, there is a cycle in the linked list
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Q2. 
Check If Preorder Traversal Is Valid
Determine whether a given array ARR of positive integers is a valid Preorder Traversal of a Binary Search Tree (BST).
A binary search tree (BST) is a tree structure w...read more
Ans. 
Check if a given array of positive integers is a valid Preorder Traversal of a Binary Search Tree (BST).
• Create a stack to keep track of nodes.

• Iterate through the array and compare each element with the top of the stack.

• If the current element is less than the top of the stack, push it onto the stack.

• If the current element is greater than the top of the stack, pop elements from the stack until a greater element is found ...read more
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Q3. What are Vtable and VPTR in C++?
Ans. 
Vtable and VPTR are used in C++ for implementing polymorphism through virtual functions.
• Vtable (Virtual Table) is a table of function pointers used to implement dynamic dispatch for virtual functions.

• VPTR (Virtual Pointer) is a pointer that points to the Vtable of an object.

• Vtable is created by the compiler for each class that has virtual functions.

• VPTR is added as a hidden member in each object of a class with virtual...read more
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Q4. What are friend functions in C++?
Ans. 
Friend functions in C++ are functions that are not members of a class but have access to its private and protected members.
• Friend functions are declared inside a class with the keyword 'friend'.

• They can access private and protected members of the class.

• They are not member functions of the class, but have the same access rights as member functions.

• Friend functions are useful when you want to allow a function external to...read more
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Round duration - 60 minutes
Round difficulty - Medium

This was also a DS/Algo round where I was given 2 questions to solve and I was expected to come up with the optimal approach as far as possible. I solved both the questions with the optimal time and space complexities and then I was asked some more questions related to DBMS towards the end of the interview.

Q1. 
Top View of a Binary Tree
You are given a binary tree. Your task is to print the Top View of the Binary Tree, displaying the nodes from left to right order.
Input:
The first line contains an integer 't'...read more
Ans. 
The task is to print the Top View of a Binary Tree from left to right order.
• Use a map to store the horizontal distance of each node from the root.

• Perform a level order traversal of the tree and keep track of the horizontal distance of each node.

• Print the nodes in the map in ascending order of their horizontal distance.

• Handle the case where multiple nodes have the same horizontal distance by printing the one that appear...read more
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Q2. 
Count Palindromic Substrings Problem Statement
Given a string STR, determine the total number of palindromic substrings within STR.
Input:
The first line contains an integer 't' representing the number ...read more
Ans. 
Count the total number of palindromic substrings in a given string.
• Iterate through each character in the string and expand around it to find palindromic substrings.

• Use dynamic programming to store previously calculated palindromic substrings.

• Consider both odd and even length palindromes while counting.

• Example: For input 'abbc', palindromic substrings are ['a', 'b', 'b', 'c', 'bb']. Total count is 5.
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Q3. What is the difference between the DELETE and TRUNCATE commands in a DBMS?
Ans. 
DELETE removes specific rows from a table, while TRUNCATE removes all rows and resets auto-increment values.
• DELETE is a DML command, while TRUNCATE is a DDL command.

• DELETE can be rolled back, while TRUNCATE cannot be rolled back.

• DELETE triggers delete triggers, while TRUNCATE does not trigger any triggers.

• DELETE is slower as it maintains logs, while TRUNCATE is faster as it does not maintain logs.

• Example: DELETE FROM t...read more
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Q4. What is meant by normalization and denormalization?
Ans. 
Normalization is the process of organizing data in a database to reduce redundancy and improve data integrity, while denormalization is the process of intentionally introducing redundancy to improve performance.
• Normalization involves breaking down a table into smaller tables and defining relationships between them to reduce redundancy and dependency.

• Denormalization involves combining tables and duplicating data to impr...read more
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