AeonX Digital SAP Abap Consultant Interview Questions, Process, and Tips

Round duration - 60 minutes
Round difficulty - Medium

Technical interview round with questions based on DSA.

Q1. 
Binary Tree Traversals
Your task is to compute the In-Order, Pre-Order, and Post-Order traversals for a given Binary Tree with 'N' nodes, where each node has an integer value.
Input:
T
For each test cas...read more
Ans. 
Compute In-Order, Pre-Order, and Post-Order traversals for a given Binary Tree with 'N' nodes.
• Implement tree traversal algorithms: In-Order, Pre-Order, and Post-Order.

• Use recursion to traverse the binary tree efficiently.

• Handle null nodes represented by -1 in the input.

• Follow the order of nodes as they appear in the level order traversal.

• Ensure the output is space-separated lists for each traversal type.
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Q2. 
LRU Cache Design Question
Design a data structure for a Least Recently Used (LRU) cache that supports the following operations:
1. get(key) - Return the value of the key if it exists in the cache; otherw...read more
Ans. 
Design a Least Recently Used (LRU) cache data structure that supports get and put operations with capacity constraint.
• Use a combination of hashmap and doubly linked list to implement the LRU cache.

• Keep track of the least recently used item and update it accordingly.

• Ensure to handle cache capacity by evicting the least recently used item when the cache is full.
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Round duration - 60 minutes
Round difficulty - Medium

Technical Interview round with questions on DSA, OS etc.

Q1. 
Number of Islands II Problem Statement
You have a 2D grid of dimensions 'N' rows by 'M' columns, initially filled with water. You are given 'Q' queries, where each query contains two integers 'X' and 'Y'....read more
Ans. 
The task is to determine the number of islands present on a 2D grid after each query of converting water to land.
• Create a function that takes the grid dimensions, queries, and coordinates as input.

• For each query, convert the water at the given coordinates to land and update the grid.

• Use depth-first search (DFS) to find connected lands and count the number of islands.

• Return the number of islands after each query.
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Q2. Why are synchronized blocks needed in Java?
Ans. 
Synchronized blocks are needed in Java to ensure thread safety by allowing only one thread to access a block of code at a time.
• Prevents multiple threads from accessing critical sections of code simultaneously

• Ensures data consistency and prevents race conditions

• Improves performance by reducing contention for shared resources

• Example: synchronized block in a method that updates a shared variable
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Round duration - 90 minutes
Round difficulty - Easy

This test has 2 sections :
Section 1 ( Technical objective questions) 
– 25 mcq’s mainly focusing on c , c++ , os , data structures , algorithms
Section 2 ( 2 Coding questions )
– Code was supposed to be written on paper.

Q1. 
Next Greater Number Problem Statement
Given a string S which represents a number, determine the smallest number strictly greater than the original number composed of the same digits. Each digit's frequenc...read more
Ans. 
Given a number represented as a string, find the smallest number greater than the original with the same set of digits.
• Sort the digits in non-increasing order to find the next greater number.

• Swap the last two digits to get the smallest greater number.

• If no greater number exists, return -1.
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Q2. 
Reverse Words in a String: Problem Statement
You are given a string of length N. Your task is to reverse the string word by word. The input may contain multiple spaces between words and may have leading o...read more
Ans. 
Reverse words in a string by reversing the order of words while maintaining spaces.
• Split the input string by spaces to get individual words

• Reverse the order of the words

• Join the reversed words with a single space in between
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Round duration - 60 minutes
Round difficulty - Easy

First round of interview was based on basic data structures. Concepts related to binary search tree , uses and comparing complexity were asked. He also asked about Hashing , Collisions.

Q1. 
K Largest Elements Problem Statement
Given an unsorted array containing 'N' integers, you are required to find 'K' largest elements from the array and return them in non-decreasing order.
Input:
The fir...read more
Ans. 
Find K largest elements in an unsorted array and return them in non-decreasing order.
• Sort the array in non-decreasing order

• Return the last K elements of the sorted array
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Round duration - 60 minutes
Round difficulty - Medium

The interview started with a programming question. Then he asked me a puzzle. There was a small discussion about my projects then .Then he started asking questions about operating system. The interviewer wanted to test my understanding about semaphores and asked some tricky and confusing questions .

Q1. 
Level Order Traversal Problem Statement
Given a binary tree of integers, return the level order traversal of the binary tree.
Input:
The first line contains an integer 'T', representing the number of te...read more
Ans. 
Return the level order traversal of a binary tree given in level order with null nodes represented by -1.
• Parse the input to create the binary tree using level order traversal

• Use a queue to perform level order traversal and print the nodes in the order visited

• Handle null nodes represented by -1 appropriately
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Q2. Explain the Producer-Consumer problem and how it can be solved using semaphores.
Ans. 
Producer-Consumer problem involves multiple threads sharing a common buffer. Producers add items to the buffer while consumers remove them.
• Producers and consumers need to synchronize their access to the shared buffer to avoid race conditions.

• Semaphores can be used to control access to the buffer. Two semaphores are used - one to track the empty slots in the buffer and one to track the filled slots.

• Producers increment t...read more
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Round duration - 60 minutes
Round difficulty - Medium

Technical Interview round with questions based on DSA.

Q1. 
Peak Element Finder
For a given array of integers arr, identify the peak element. A peak element is an element that is greater than its neighboring elements. Specifically, if arr[i] is the peak, then both...read more
Ans. 
Find the peak element in an array of integers.
• Iterate through the array and check if the current element is greater than its neighbors.

• Handle edge cases for the first and last elements of the array.

• Return the peak element found.
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Round duration - 60 minutes
Round difficulty - Easy

This round was a telephonic interview with the CTO of the company. The he started with a small discussion about my projects and research paper .He then moved on to data structures and asked me how to choose a relevant data structure for a given problem. I gave him advantages of every data structure and certain problems where specific data structures could be useful .Then he gave a question and asked me for what data structure should be used keeping time complexity in mind. He asked me a few HR questions in the end .

Q1. 
Average Marks Problem Statement
Given the initial letter of a student's name and three integer marks for that student, calculate and display the student's initial letter followed by the integer part of th...read more
Ans. 
Calculate and display the student's initial letter followed by the integer part of their average marks.
• Calculate the average of the three marks provided for each student.

• Display the initial letter of the student's name followed by the integer part of the average marks.

• Round down the average to the nearest integer to get the integer part.
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Round duration - 60 minutes
Round difficulty - Medium

Technical Interview round with questions on DSA.

Q1. 
Running Median Problem
Given a stream of integers, calculate and print the median after each new integer is added to the stream.
Output only the integer part of the median.
Example:
Input:
N = 5  
Stre...read more
Ans. 
Calculate and print the median after each new integer is added to the stream.
• Use two heaps - a max heap to store the smaller half of the numbers and a min heap to store the larger half.

• Keep the sizes of the two heaps balanced to efficiently calculate the median.

• If the total number of elements is odd, the median will be the top element of the max heap.

• If the total number of elements is even, the median will be the avera
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Q2. 
Pair Sum in Binary Search Tree
Given a Binary Search Tree (BST) and a target value 'K', determine if there exist two unique elements in the BST such that their sum equals the target 'K'.
Explanation:
A ...read more
Ans. 
Given a BST and a target value, determine if there exist two unique elements in the BST such that their sum equals the target.
• Traverse the BST in-order to get a sorted array of elements.

• Use two pointers approach to find the pair sum in the sorted array.

• Keep track of visited elements to ensure uniqueness.

• Handle edge cases like null nodes and empty tree.

• Example: For input BST [20, 10, 35, 5, 15, 30, 42, -1, 13, -1, -1, -
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Q3. 
Statistics From A Large Sample Task
Calculate various statistical measures given a large sample of integers in the range [0, 255]. For efficiency, you are provided with an array 'count' where the i-th ele...read more
Ans. 
Calculate various statistical measures given a large sample of integers in the range [0, 255] using the provided frequency array.
• Iterate through the 'count' array to calculate minimum and maximum values.

• Calculate the mean by summing up all values and dividing by the total count.

• Find the median by sorting the sample and determining the middle element(s).

• Identify the mode by finding the element with the highest frequency...read more
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Round duration - 60 minutes
Round difficulty - Medium

Technical Interview round with questions on DSA. A puzzle was also asked.

Q1. 
LRU Cache Design Question
Design a data structure for a Least Recently Used (LRU) cache that supports the following operations:
1. get(key) - Return the value of the key if it exists in the cache; otherw...read more
Ans. 
Design a Least Recently Used (LRU) cache data structure that supports get and put operations with capacity constraint.
• Use a combination of hashmap and doubly linked list to efficiently implement the LRU cache.

• Keep track of the least recently used item and update it accordingly when inserting new items.

• Ensure to handle the capacity constraint by evicting the least recently used item when the cache is full.
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Q2. 
Sorting of a Rotated Sorted Array Problem Statement
You are provided with a rotated sorted array of size N. Your task is to sort the given array in increasing order.
Example:
Input:
N = 4
Array = [2, 3,...read more
Ans. 
Implement a function to sort a rotated sorted array in increasing order without using the sort() function.
• Find the pivot element in the rotated sorted array.

• Split the array into two subarrays based on the pivot element.

• Sort each subarray separately.

• Merge the sorted subarrays to get the final sorted array.
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Q3. You have 5 pirates and 100 gold coins. The challenge is to determine how the pirates will divide the coins among themselves based on their ranking and the rules they follow.
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Round duration - 30 minutes
Round difficulty - Easy

HR round with typical behavioral problems.

5 DSA Questions 2 Easy, 2Medium, 1 Hard, hackerrank

Q1. 3 DSA question were asked of medium level
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Q2. Largest vertical rectangle in array
Ans. 
Find the largest vertical rectangle in an array of strings
• Iterate through each column in the array

• For each column, find the consecutive vertical rectangles of '1's

• Calculate the area of each rectangle and keep track of the largest one
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Q1. 1 DSA and around OS, DBMS, Resume
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Q1. Around projects, Multithreading, LLD, HLD
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Few questions that would involve problem solving. Basic 10th std math would suffice

Had few DSA questions.

Q1. Technical interview
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Q1. About job, expection etc
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Simple question on maths

Q1. Explain OOPS concept
Ans. 
OOPS (Object-Oriented Programming) is a programming paradigm based on the concept of objects, which can contain data and code.
• OOPS focuses on creating objects that interact with each other to solve complex problems

• Key principles include encapsulation, inheritance, polymorphism, and abstraction

• Encapsulation ensures that the internal state of an object is hidden from the outside world

• Inheritance allows a class to inherit...read more
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Q2. Coding array questions
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