20+ Utility Hub Interview Questions and Answers

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

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 binary trees for each possible left and right subtree hei...read more

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

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 greater than 'K', move the right pointer to the left

• Repeat the...read more

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

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 list.

• Continue the DFS traversal to explore other nodes in the...read more

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.

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-decreasing order.

Find the majority element in an array, return -1 if no majority element exists.

• Iterate through the array and keep track of the count of each element using a hashmap.

• Check if any element's count is greater than floor(N/2) to determine the majority element.

• Return the majority element or -1 if no majority element exists.

Find maximum profit by buying and selling stocks multiple times.

• Iterate through the array and find all increasing sequences of stock prices.

• Calculate profit by buying at the start and selling at the end of each increasing sequence.

• Sum up all profits to get the maximum profit achievable.

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.

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 'ace' with a length of 3.

Calculate the height of a binary tree given its level order traversal.

• Traverse the binary tree level by level and keep track of the height as you go down the tree.

• Use a queue data structure to perform level order traversal efficiently.

• The height of a binary tree is the maximum number of edges from the root to any leaf node.

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

• Return the height of the binary tree as a single integer.

Count the number of islands in a 2D matrix of 1s and 0s.

• Use Depth First Search (DFS) or Breadth First Search (BFS) to traverse the matrix and count the number of connected components.

• Maintain a visited array to keep track of visited cells to avoid counting the same island multiple times.

• Iterate through each cell in the matrix and if it is a land (1) and not visited, perform DFS/BFS to explore the connected land cells.

• Increment the island count each time a new island is encoun...read more

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.

• Calculate the minimum number of operations by considering all p...read more

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

Find the length of the longest pair chain that can be formed using the given pairs.

• Sort the pairs based on the second element in ascending order.

• Iterate through the sorted pairs and keep track of the maximum chain length.

• Update the chain length if the current pair can be added to the chain.

• Return the maximum chain length at the end.

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.

Designing a web crawler involves defining the scope, selecting a crawling strategy, implementing the crawler, handling data storage, and ensuring politeness.

• Define the scope of the web crawler by determining the websites to crawl and the depth of the crawl.

• Select a crawling strategy such as breadth-first or depth-first search based on the requirements.

• Implement the web crawler using a programming language like Python or Java, utilizing libraries like Scrapy or BeautifulSoup.

• H...read more

Software development life cycle (SDLC) is a process used by software developers to design, develop, and test software.

• 1. Planning: Define the project scope, requirements, and objectives.

• 2. Analysis: Gather and analyze user requirements.

• 3. Design: Create a detailed design of the software.

• 4. Implementation: Develop the software based on the design.

• 5. Testing: Test the software for bugs and issues.

• 6. Deployment: Release the software to users.

• 7. Maintenance: Update and maintain t...read more

Use a binary tree traversal algorithm to find the next sibling on the right side of a given value.

• Implement an in-order traversal algorithm to traverse the binary tree

• Keep track of the parent node and the direction of traversal to find the next sibling on the right side

• If the given value is the right child of its parent, move up the tree until finding a node that is the left child of its parent

API stands for Application Programming Interface. It is a set of rules and protocols that allows different software applications to communicate with each other.

• APIs define the methods and data formats that applications can use to request and exchange information.

• APIs can be used to access services provided by other software applications, such as retrieving data from a database or sending notifications.

• Examples of APIs include the Google Maps API, which allows developers to in...read more

Delete a node from a binary tree.

• Find the node to be deleted

• If the node has no children, simply delete it

• If the node has one child, replace it with its child

• If the node has two children, find the minimum value in its right subtree, replace the node with that value, and delete the minimum value node

Use Floyd's Tortoise and Hare algorithm to detect a loop in a linked list.

• Initialize two pointers, slow and fast, at the head of the linked list.

• Move slow pointer by one step and fast pointer by two steps.

• If they meet at any point, there is a loop in the linked list.