EGDK Interview Questions and Answers

Abstraction is the process of hiding complex implementation details and exposing only the necessary information.

• Abstraction helps in reducing complexity and increasing efficiency.

• It allows us to focus on the essential features of an object or system.

• Abstraction can be achieved through abstract classes, interfaces, and encapsulation.

• For example, a car can be abstracted as a vehicle with certain properties and methods.

• Ab...read more

Hiding implementation means keeping the internal details of a class or function hidden from the outside world.

• It is a fundamental principle of object-oriented programming.

• It helps in achieving encapsulation and abstraction.

• It prevents the user from accessing the internal workings of a class or function.

• Examples include private variables and methods in a class.

• It allows for easier maintenance and modification of code.

• It...read more

Print the level order traversal of binary tree in spiral form

• Perform level order traversal of the binary tree

• Alternate the direction of traversal for each level

• Use a stack to reverse the order of nodes in each level

• Print the nodes in the order of traversal

Find the maximum element in each subarray of size k in a given array.

• Iterate through the array from index 0 to n-k.

• For each subarray of size k, find the maximum element.

• Store the maximum elements in a separate array.

• Return the array of maximum elements.

To find the Kth largest element in two sorted arrays, we can use the merge step of merge sort algorithm.

• Merge the two arrays into a single sorted array using a modified merge sort algorithm.

• Return the Kth element from the merged array.

Merge two sorted arrays into one sorted array with expected time complexity of (m+n).

• Use a two-pointer approach to compare elements from both arrays and merge them into the first array.

• Start comparing elements from the end of both arrays and place the larger element at the end of the first array.

• Continue this process until all elements from the second array are merged into the first array.

The algorithm finds the position of the 3rd occurrence of 'B' in an n-ary tree from a given index in constant time complexity.

• Traverse the n-ary tree using a depth-first search (DFS) algorithm

• Keep track of the count of 'B' occurrences

• When the count reaches 3, return the current position

• If the end of the tree is reached before the 3rd 'B', return -1

Check if a given string is a composite of two words from a limited dictionary.

• Create a hash set of all the words in the dictionary.

• Iterate through all possible pairs of substrings in the given string.

• Check if both substrings are present in the hash set.

• If yes, return true. Else, return false.

Switch adjacent nodes in a single linked list.

• Traverse the linked list and swap adjacent nodes.

• Keep track of previous node to update its next pointer.

• Handle edge cases for first two nodes and last node.

• Example: 1->2->3->4 becomes 2->1->4->3.

Traverse only the left sub-tree of a binary search tree.

• Start at the root node

• If the left child exists, visit it and repeat the process

• If the left child does not exist, return to the parent node

• Continue until all nodes in the left sub-tree have been visited

Design an efficient data structure for two lifts in a building of n floors.

• Use a priority queue to keep track of the floors each lift is heading to

• Implement a scheduling algorithm to determine which lift to assign to a new request

• Consider adding a weight limit to each lift to prevent overloading

• Use a hash table to keep track of the current location of each lift

To find the maximum number that can be formed from the digits of an integer.

• Convert the integer to a string

• Sort the characters in descending order

• Join the sorted characters to form the maximum number