Viewics Senior Java Developer Interview Questions and Answers

Convert a sorted array to balanced binary search tree

• Find the middle element of the array and make it the root of the tree

• Recursively construct the left subtree using the left half of the array

• Recursively construct the right subtree using the right half of the array

• Repeat until all elements are added to the tree

Reverse a singly linked list in groups of k in­place

• Divide the linked list into groups of k nodes

• Reverse each group of k nodes

• Connect the reversed groups to form the final linked list

A recursive routine to calculate a ^ n

• The base case is when n is 0, in which case the result is 1

• For any other value of n, the result is a multiplied by the result of a^(n-1)

• The recursive function should call itself with a^(n-1) as the new input

Design optimal data structure for never-ending stream of numbers for insertion, deletion, searching, kth largest and kth smallest.

• Use a balanced binary search tree like AVL or Red-Black tree for efficient insertion, deletion, and searching.

• Maintain two heaps, one for kth largest and one for kth smallest.

• For finding kth largest, use a min heap of size k and for kth smallest, use a max heap of size k.

• Alternatively, use a...read more

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