Litera Software Developer Interview Questions and Answers

Merge Sort is a divide and conquer algorithm that sorts an array by dividing it into two halves, sorting them separately, and then merging the sorted halves.

• Divide the array into two halves

• Recursively sort the two halves

• Merge the sorted halves

Find pairs of integers in a BST whose sum is equal to a given number.

• Traverse the BST and store the values in a hash set.

• For each node, check if (X - node.value) exists in the hash set.

• If yes, add the pair (node.value, X - node.value) to the result.

• Continue traversal until all nodes are processed.

Merge overlapping time intervals into mutually exclusive intervals.

• Sort the intervals based on their start time.

• Iterate through the intervals and merge overlapping intervals.

• Output the mutually exclusive intervals.

• Example: [(1,3), (2,6), (8,10), (15,18)] -> [(1,6), (8,10), (15,18)]

Different types of hashing and alternative for Linear Chaining

• Different types of hashing include division, multiplication, and universal hashing

• Alternative for Linear Chaining is Open Addressing

• Open Addressing includes Linear Probing, Quadratic Probing, and Double Hashing

An AVL tree is a self-balancing binary search tree where the heights of the left and right subtrees differ by at most one.

• AVL tree is a binary search tree with additional balance factor for each node.

• The balance factor is the difference between the heights of the left and right subtrees.

• Insertion and deletion operations in AVL tree maintain the balance factor to ensure the tree remains balanced.

• Rotations are performed ...read more

Find the minimum number of squares whose sum equals to a given number n.

• Use dynamic programming to solve the problem efficiently.

• Start with finding the square root of n and check if it is a perfect square.

• If not, then try to find the minimum number of squares required for the remaining number.

• Repeat the process until the remaining number becomes 0.

• Return the minimum number of squares required for the given number n.

Insertion sort for a singly linked list.

• Traverse the list and compare each node with the previous nodes

• If the current node is smaller, swap it with the previous node

• Repeat until the end of the list is reached

• Time complexity is O(n^2)

Search an element in sorted rotated array.

• Use binary search to find the pivot point where the array is rotated.

• Divide the array into two subarrays and perform binary search on the appropriate subarray.

• Handle the cases where the target element is at the pivot point or not present in the array.

Find the Kth largest element in an array.

• Sort the array in descending order and return the element at index K-1.

• Use a max heap to find the Kth largest element efficiently.

• Implement a quickselect algorithm to find the Kth largest element in linear time.

Reverse a linked list in groups of n elements.

• Divide the linked list into groups of n elements.

• Reverse each group individually.

• Connect the reversed groups to form the final linked list.

• Handle cases where the number of elements is not a multiple of n.

• Example: 1->2->3->4->5->6->7->8, n=3 -> 3->2->1->6->5->4->8->7

Find the median of two sorted arrays.

• Merge the two arrays into one sorted array and find the median.

• Use binary search to find the median in O(log(min(m, n))) time complexity.

• Handle edge cases like empty arrays or arrays of different lengths.

Count number of paths from (0, 0) to (m, n) in a matrix while crossing through some indexes were not allowed.

• Use dynamic programming to solve the problem

• Create a 2D array to store the number of paths

• Traverse the matrix and update the array based on the allowed paths

• Return the value at the last index of the array

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.