Mentor Graphics Senior Member of Technical Staff 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
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Digital electronics, circuits , verilog , asic design flow

Q1. Explain the complete asic design flow process
Ans. 
ASIC design flow process involves steps like specification, design, verification, synthesis, and testing.
• Specification: Define requirements and constraints for the ASIC design.

• Design: Create a high-level design based on the specifications.

• Verification: Verify the design using simulations and tests.

• Synthesis: Convert the design into a netlist of gates and connections.

• Testing: Test the fabricated ASIC to ensure functiona...read more
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Q2. Power reduction techniques in CMOS
Ans. 
Power reduction techniques in CMOS involve various methods to minimize power consumption in CMOS circuits.
• Use of power gating to selectively turn off power to unused circuit blocks

• Implementing clock gating to disable clock signals to unused circuitry

• Utilizing voltage scaling to reduce power consumption at lower voltages

• Applying dynamic voltage and frequency scaling to adjust voltage and frequency based on workload

• Using...read more
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Q1. Basics and advance C++ concepts
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Q1. For 1 yr experience Java dev interview: Qs on core java, collections, internal working, code snippets related to OOPS were given and output had to be guessed. Basic Coding problem
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Q1. Write down the recursion tree for this code:
Ans. 
Recursion tree for a given code
• Identify the base case of the recursion

• Draw a tree structure with each recursive call as a node

• Label each node with the input parameters and return values
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Round duration - 90 minutes
Round difficulty - Easy

Timing - 10AM-11:30AM
Online proctored test

Q1. 
Binary Tree Right View Problem Statement
Given a binary tree of integers, your task is to print the right view of it. The right view represents a set of nodes visible when the tree is viewed from the righ...read more
Ans. 
The task is to print the right view of a binary tree, representing nodes visible from the right side in top-to-bottom order.
• Traverse the tree level by level and keep track of the rightmost node at each level

• Print the rightmost node of each level to get the right view of the tree

• Use a queue for level order traversal and a map to store the rightmost nodes
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Q2. 
0/1 Knapsack Problem Statement
A thief is planning to rob a store and can carry a maximum weight of 'W' in his knapsack. The store contains 'N' items where the ith item has a weight of 'wi' and a value of...read more
Ans. 
Yes, the 0/1 Knapsack problem can be solved using dynamic programming with a space complexity of not more than O(W).
• Use a 1D array to store the maximum value that can be stolen for each weight from 0 to W.

• Iterate through each item and update the array based on whether including the item would increase the total value.

• The final value in the array at index W will be the maximum value that can be stolen.
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Round duration - 45 minutes
Round difficulty - Medium

Timing : 4PM-5PM
Environment - Online

There was a panel of 3 interviewers

Q1. How can you find the size of an array in C or C++ without using sizeof or any standard function?
Ans. 
You can find the size of an array in C or C++ by dividing the total size of the array by the size of one element.
• Calculate the total size of the array by multiplying the number of elements by the size of each element.

• Divide the total size by the size of one element to get the size of the array.

• For example, if you have an array of strings arr[] = {'hello', 'world', 'example'}, you can find the size by dividing the total
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Q2. Explain how indexing in a database works using B+ trees.
Ans. 
B+ trees are used for indexing in databases to efficiently search and retrieve data.
• B+ trees are balanced trees where each node can have multiple keys and child pointers.

• Data is stored in leaf nodes, while non-leaf nodes are used for navigation.

• B+ trees are commonly used in databases because of their ability to efficiently search and retrieve data.

• Example: In a database table with an index on a specific column, B+ tree...read more
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Round duration - 45 mintues
Round difficulty - Easy

Timing - 11AM-12:15PM
Environment - online video call

Again there was a panel of 2 senior engineers

Q1. 
Maximum Path Sum Problem Statement
You are given an n-ary tree consisting of 'N' nodes. Your task is to determine the maximum sum of the path from the root to any leaf node.
Example:
Input:
For the giv...read more
Ans. 
Find the maximum sum of the path from the root to any leaf node in an n-ary tree.
• Traverse the tree from root to leaf nodes while keeping track of the sum of each path.

• At each node, calculate the sum of the path from the root to that node and update the maximum sum found so far.

• Consider using depth-first search (DFS) or breadth-first search (BFS) for tree traversal.

• Handle cases where nodes have negative values or where
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