D2K Technologies India Android App Developer Interview Questions and Answers

Q1. Agile, data class, how to initialize a class in activity?, dagger, difference between bind and provides annotation, unit test using mockito and junit
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Q1. What is intent?
Ans. 
Intent is a messaging object used to request an action from another app component.
• Intent is used to start activities, services, and broadcast receivers in Android.

• It can also be used to pass data between components.

• There are two types of intents: explicit intents and implicit intents.

• Explicit intents specify the component to start by name.

• Implicit intents specify the action to perform and let the system find the approp
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Q2. What is work manager?
Ans. 
Work Manager is an Android Jetpack library used for managing deferrable, asynchronous tasks.
• Work Manager is part of the Android Jetpack library.

• It is used for managing deferrable, asynchronous tasks that need to run even if the app is in the background.

• Work Manager provides various constraints and options for scheduling tasks, such as network availability, charging status, and more.

• It is recommended for tasks that are ...read more
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Q1. Explain activity life cycle
Ans. 
Activity life cycle refers to the stages an activity goes through from creation to destruction.
• An activity is created using onCreate() method

• It becomes visible using onStart() method

• It becomes interactive using onResume() method

• It goes to background using onPause() method

• It becomes invisible using onStop() method

• It gets destroyed using onDestroy() method
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Q2. What is difference between abstract class and interface
Ans. 
Abstract class is a class that can have both abstract and non-abstract methods while interface only has abstract methods.
• Abstract class can have constructors while interface cannot

• A class can implement multiple interfaces but can only inherit from one abstract class

• Abstract class can have instance variables while interface cannot

• Abstract class can provide default implementation for some methods while interface cannot

• Ex...read more
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Q1. Why are you looking for a change?
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Q2. Tell me about yourself.
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Q1. Scope functions in kotlin
Ans. 
Scope functions in Kotlin are functions that allow you to execute a block of code within the context of an object.
• There are five scope functions in Kotlin: let, run, with, apply, and also.

• Each scope function has a specific use case and can help improve code readability and reduce boilerplate code.

• Scope functions can be used to perform operations on an object and return a result or modify the object itself.

• For example, ...read more
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Q2. LazyRow vs RecyclerView
Ans. 
LazyRow is a Jetpack Compose component for displaying horizontally scrolling lists, while RecyclerView is a traditional Android view for displaying large data sets efficiently.
• LazyRow is part of Jetpack Compose, RecyclerView is part of the Android framework

• LazyRow is more declarative and easier to use for simple lists, RecyclerView is more powerful and customizable for complex lists

• LazyRow automatically handles recycli...read more
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Round duration - 180 min
Round difficulty - Hard

Q1. 
Longest Common Subsequence Problem Statement
Given two strings STR1 and STR2, determine the length of their longest common subsequence.
A subsequence is a sequence that can be derived from another sequen...read more
Ans. 
The problem involves finding the length of the longest common subsequence between two given strings.
• Use dynamic programming to solve the problem efficiently.

• Create a 2D array to store the lengths of common subsequences of substrings.

• Iterate through the strings to fill the array and find the length of the longest common subsequence.

• Example: For input STR1 = 'abcde' and STR2 = 'ace', the longest common subsequence is 'ac
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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 capacity 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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Q3. 
K Largest Elements Problem Statement
You are given an unsorted array containing 'N' integers. Your task is to find the 'K' largest elements from this array and return them in non-decreasing order.
Input:
T...read more
Ans. 
Yes, the problem can be solved in less than O(N*log(N)) time complexity using the Quick Select algorithm.
• Implement Quick Select algorithm to find the Kth largest element in O(N) time complexity.

• Partition the array around a pivot element and recursively search in the left or right partition based on the position of the pivot.

• Once you find the Kth largest element, return all elements greater than or equal to it in non-de
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Round duration - 60 Minutes
Round difficulty - Medium

Q1. 
Size of Largest BST in a Binary Tree
Given a binary tree with 'N' nodes, determine the size of the largest subtree that is also a Binary Search Tree (BST).
Explanation:
A Binary Search Tree (BST) is def...read more
Ans. 
Find the size of the largest BST subtree in a binary tree.
• Traverse the tree in a bottom-up manner to check if each subtree is a BST.

• Keep track of the size of the largest BST found so far.

• Recursively check if the current subtree is a BST and update the size accordingly.
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Q2. 
Matrix Chain Multiplication Problem
Given 'N' 2-dimensional matrices and an array ARR of length N + 1, where the first N integers denote the number of rows in each matrix and the last integer represents t...read more
Ans. 
Find the minimum number of multiplication operations required to multiply a series of matrices together.
• Use dynamic programming to solve this problem efficiently.

• Create a 2D array to store the minimum number of operations needed to multiply matrices.

• Iterate through different combinations of matrices to find the optimal solution.

• Consider the dimensions of the matrices to determine the number of operations required.

• Calcu...read more
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Q3. 
Rotate Linked List Problem Statement
Given a linked list consisting of 'N' nodes and an integer 'K', your task is to rotate the linked list by 'K' positions in a clockwise direction.
Example:
Input:
Li...read more
Ans. 
Rotate a linked list by K positions in a clockwise direction.
• Traverse the linked list to find the length and the last node.

• Connect the last node to the head to form a circular linked list.

• Find the new head by moving (length - K) steps from the last node.

• Break the circular list at the new head to get the rotated linked list.
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Round duration - 45 minutes
Round difficulty - Easy

Q1. 
Longest Palindromic Substring Problem Statement
You are provided with a string STR of length N. The task is to find the longest palindromic substring within STR. If there are several palindromic substring...read more
Ans. 
Given a string, find the longest palindromic substring within it.
• Iterate through the string and expand around each character to find palindromes

• Keep track of the longest palindrome found so far

• Return the longest palindromic substring
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Q1. IT WAS MCQ CODING OUTPUT BASED ROUND IN WHICH TOTAL 45 QUESTION
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Q1. IT WAS SUBJECTIVE CODING ROUND IN WHICH 1 OUTPUT BASED AND 3 CODING ROUND
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IT WAS 3RD CODING ROUND IN WHICH 3 CODING QUESTIONS AND DURATION 75MIN

Round duration - 60 minutes
Round difficulty - Medium

Students who qualified in first round gets link for this round, this round had 4 questions in total, out of which 1 was output based and 3 was DSA based.

Q1. 
Validate Binary Tree Nodes Problem
You are provided with 'N' binary tree nodes labeled from 0 to N-1, where node i has two potential children, recorded in the LEFT_CHILD[i] and RIGHT_CHILD[i] arrays. Dete...read more
Ans. 
The task is to determine if the given binary tree nodes form exactly one valid binary tree.
• Check if there is only one root node (a node with no parent)

• Check if each node has at most one parent

• Check if there are no cycles in the tree

• Check if all nodes are connected and form a single tree
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Round duration - 75 minutes
Round difficulty - Medium

This round was of 70-75 minutes and had 3 coding questions of easy to medium level. There was some restrictions like we cannot use built-in functions in both second and third subjective round.

Q1. 
Balanced Binary Trees Problem Statement
You are provided with an integer 'H'. Your task is to determine and print the maximum number of balanced binary trees possible with height 'H'.
A balanced binary t...read more
Ans. 
The maximum number of balanced binary trees possible with a given height is to be counted and printed.
• A balanced binary tree is one in which the difference between the left and right subtree heights is less than or equal to 1.

• The number of balanced binary trees can be calculated using dynamic programming.

• The number of balanced binary trees with height 'H' can be obtained by summing the product of the number of balanced...read more
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Round duration - 60 minutes
Round difficulty - Medium

This was face to face interview round of 60 minutes. It was mostly based on DSA, some questions was also asked related to my projects and DBMS. Interviewer was kind and good.

Q1. 
Wave Array Sorting Problem
Your goal is to sort a given unsorted array ARR such that it forms a wave array.
Explanation:
After sorting, the array should satisfy the wave pattern conditions:
• ARR[0] &...read more
Ans. 
The task is to sort an array in a wave form, where each element is greater than or equal to its adjacent elements.
• Iterate through the array and swap adjacent elements if they do not follow the wave pattern

• Start from the second element and compare it with the previous element, swap if necessary

• Continue this process until the end of the array

• Repeat the process for the remaining elements

• Return the sorted wave array
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Q2. 
Maximum Sum BST Problem Statement
You are presented with a Binary Tree 'root', which may not necessarily be a Binary Search Tree (BST). Your objective is to identify the maximum sum of node values in any ...read more
Ans. 
The task is to find the maximum sum of node values of any subtree that is a Binary Search Tree(BST).
• Traverse the binary tree in a bottom-up manner

• For each node, check if it forms a BST and calculate the sum of its subtree

• Keep track of the maximum sum encountered so far

• Return the maximum sum
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Round duration - 135 minutes
Round difficulty - Hard

This was the final technical round, it was around 2.5 hours long and based on mostly DSA and little bit Projects, DBMS, OS. Josh mainly focus on DSA and on Tree Data Structure in interview.

Q1. 
Pair Sum in BST Problem Statement
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 K.
Input:
An integer T, the nu...read more
Ans. 
The task is to check if there exist two unique elements in the given BST such that their sum is equal to the given target 'K'.
• Traverse the BST in-order and store the elements in a sorted array

• Use two pointers, one at the beginning and one at the end of the array

• Check if the sum of the elements at the two pointers is equal to the target 'K'

• If the sum is less than 'K', move the left pointer to the right

• If the sum is grea...read more
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Q2. 
Find Nodes at Distance K in a Binary Tree
Your task is to find all nodes that are exactly a distance K from a given node in an arbitrary binary tree. The distance is defined as the number of edges between ...read more
Ans. 
The task is to find all nodes in a binary tree that are at a distance K from a given node.
• Implement a function that takes the binary tree, target node, and distance K as input.

• Use a depth-first search (DFS) algorithm to traverse the tree and find the nodes at distance K.

• Keep track of the distance from the current node to the target node while traversing.

• When the distance equals K, add the current node to the result lis...read more
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Round duration - 20 minutes
Round difficulty - Easy

This was the simple 20 minutes round

All multiple-choice questions on object-oriented programming and pointers.

Questions related to linked lists and trees.

Three questions, all regarding LinkedIn, focusing on lists and trees.