300+ Amazon Software Developer Interview Questions and Answers

Given a string of lowercase characters, rearrange it so that no two adjacent characters are identical. Return the rearranged string or 'NO SOLUTION'.

• Iterate through the string and count the frequency of each character.

• Sort the characters based on their frequency in non-increasing order.

• Place the characters with highest frequency first, alternating with other characters.

• If there are more than half of the characters with the same frequency, 'NO SOLUTION' is returned.

Design a data structure to efficiently return the k-th largest number from an infinite stream of numbers.

• Implement a max heap to store the numbers in the stream.

• Keep the heap size limited to k to efficiently find the k-th largest number.

• Update the heap when adding new numbers or querying for the k-th largest number.

Determine the gender of the Kth child in the Nth generation based on a unique family structure.

• Every male member has a male child first followed by a female child, and every female member has a female child first followed by a male child.

• Given generation number N and position of the child K, determine the gender of the Kth child in the Nth generation.

• Output 'Male' if the child is male, otherwise 'Female'.

• Start the family tree from the male member, Aakash.

Clone a linked list with random pointers by creating deep copy of the original list without duplicating references.

• Create a deep copy of the linked list by instantiating new nodes for each node in the original list.

• Ensure that the random pointers in the cloned list point to the corresponding nodes in the new list.

• Do not duplicate references to original nodes while creating the clone.

• Implement the function to clone the linked list without using additional space.

• Verify that the...read more

Find the area of the largest rectangle that can be formed within the bounds of a given histogram.

• Iterate through the histogram bars and maintain a stack to keep track of increasing heights.

• Calculate the area of the rectangle formed by each bar as the smallest height in the stack times the width.

• Update the maximum area found so far and return it as the result.

Determine if a given binary tree is a binary heap tree or not based on certain properties.

• Check if the binary tree is a complete binary tree where every level, except the last level, is completely filled and the last level is as far left as possible.

• Ensure that every parent node is greater than all its children nodes, forming a max-heap.

• If any node does not have a left or right child, it should be represented as -1 in the input.

Group anagrams in an array of strings based on their characters.

• Iterate through the array of strings and sort each string to group anagrams together.

• Use a hashmap to store the sorted string as key and the list of anagrams as value.

• Return the values of the hashmap as the grouped anagrams.

Count the number of islands in a grid of 0s and 1s connected horizontally, vertically, or diagonally.

• Iterate through the grid and perform depth-first search (DFS) to mark visited land cells and count islands

• Use a visited array to keep track of visited cells to avoid double counting

• Check all neighboring cells (horizontally, vertically, and diagonally) of a land cell during DFS

• Increment island count whenever a new island is encountered

Construct the largest number by concatenating positive integers in the array exactly once.

• Sort the array of integers in a way that the concatenation of the numbers forms the largest possible number.

• Use a custom comparator function to sort the numbers based on their concatenation value.

• Join the sorted array elements to form the final largest number.

Convert infix expression to postfix expression.

• Use a stack to keep track of operators and operands.

• Follow the rules of precedence for operators (* and / before + and -).

• Handle parentheses by pushing them onto the stack and popping when necessary.

Return the level order traversal of a binary tree given in level order with null nodes represented by -1.

• Create a queue to store nodes for level order traversal

• Start with the root node and enqueue it

• While the queue is not empty, dequeue a node, print its value, and enqueue its children

• Repeat until all nodes are traversed in level order

Return the bottom view of a binary tree when viewed from left to right.

• Traverse the tree in level order and keep track of the horizontal distance and depth of each node

• For each horizontal distance, update the node in the map if it is deeper than the current node

• Return the values of the map in sorted order of horizontal distance

Check if a binary tree is 'special' if every node has zero or two children.

• Traverse the binary tree and check if each non-leaf node has exactly two children.

• Use a recursive approach to check each node's children.

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

Find the length of the longest common subsequence between two given strings.

• Use dynamic programming to solve this problem efficiently.

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

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

Merge two sorted linked lists into a single sorted linked list without using additional space beyond constant space complexity.

• Create a dummy node to start the merged list

• Iterate through both linked lists and compare nodes to merge them in sorted order

• Update the next pointers accordingly

• Handle cases where one list is empty or both lists are empty

• Return the head of the merged linked list

Detect if an array contains a Pythagorean triplet.

• Iterate through all possible triplets in the array and check if they form a Pythagorean triplet.

• Use a nested loop to generate all possible combinations of three numbers in the array.

• Check if the sum of squares of two numbers is equal to the square of the third number.

Find the largest palindrome number strictly less than the given palindrome number.

• Iterate from the middle towards the start of the number and copy the digits to the left side to create the next smaller palindrome.

• Handle cases where the middle digit is not 0 by decrementing it and mirroring the left side to the right side.

• If the number is all 9s, change the first and last digits to 1 and fill the middle with 0s.

Maximize memory usage by pairing downloads and games within memory limit 'K'.

• Sort the downloads and games in descending order.

• Iterate through the sorted arrays to find the optimal pairs within memory limit 'K'.

• Return the indices of the selected download and game pairs.

To check if a number k lies in a sequence formed by adding previous 2 elements, start with a=0 and b=1 and iterate until k is found or exceeded.

• Start with a=0 and b=1

• Iterate through the sequence until k is found or exceeded

• If k is found, return true. If exceeded, return false

Find the minimum number of dice throws required to reach the last cell on a 'Snake and Ladder' board.

• Use Breadth First Search (BFS) algorithm to find the shortest path from the starting cell to the last cell.

• Maintain a queue to keep track of the cells to be visited next.

• Consider the effect of snakes and ladders on the movement of the player.

• Return the minimum number of dice throws required to reach the last cell, or -1 if unreachable.

Given an array of integers and a target sum, find a contiguous subarray with the sum equal to the target.

• Iterate through the array while keeping track of the current sum and start index.

• Use a hashmap to store the cumulative sum and its corresponding index.

• If the current sum - target sum exists in the hashmap, a subarray with the target sum is found.

• Return the start index and current index as the end index of the subarray.

Return the boundary nodes of a binary tree in Anti-Clockwise direction starting from the root node.

• Traverse the left boundary nodes in a top-down manner

• Traverse the leaf nodes from left to right

• Traverse the right boundary nodes in a bottom-up manner

• Handle cases where duplicates occur in the boundary nodes

• Implement the function without printing as printing is already managed

Identify the duplicate integer in an array containing numbers between 1 and N-1.

• Iterate through the array and keep track of the frequency of each number using a hashmap.

• Return the number with a frequency greater than 1 as the duplicate integer.

• Time complexity can be optimized to O(N) using Floyd's Tortoise and Hare algorithm.

• Example: For input [1, 2, 3, 4, 4], the output should be 4.

Determine if a binary string can be sorted in decreasing order by removing non-adjacent characters.

• Check if the count of '1's in the string is equal to the length of the string, as it can be sorted in decreasing order by removing non-adjacent characters.

• If the count of '1's is not equal to the length of the string, check if the string can be rearranged to form a decreasing order by removing non-adjacent characters.

• Consider edge cases like all '0's or all '1's in the string.

Find the smallest sum achievable by selecting one element from each row of a 2D matrix, following certain constraints.

• Iterate through each row and find the minimum element that does not violate the constraints.

• Keep track of the minimum sum achieved by selecting elements from each row.

• Avoid selecting elements directly beneath previously selected elements.

The minimum number of swaps required to make a string K-periodic by replacing characters with elements from an array.

• Iterate through the string and check if each character matches the character K positions ahead.

• Count the number of characters that need to be swapped to make the string K-periodic.

• Use the array elements to swap characters in the string.

• Return the total number of swaps needed for each test case.

Given a number represented as a string, find the smallest number greater than the original with the same set of digits.

• Iterate from right to left to find the first digit that can be swapped with a larger digit to make the number greater.

• Swap this digit with the smallest digit to its right that is larger than it.

• Sort the digits to the right of the swapped digit in ascending order to get the smallest number greater than the original.

• If no such number exists, return -1.

• Example: ...read more

Rearrange array elements in a zig-zag manner where every odd index element is greater than its neighbors.

• Iterate through the array and swap elements to satisfy the zig-zag condition.

• Ensure that for every odd index i, ARR[i] > ARR[i-1] and ARR[i] > ARR[i+1].

• Multiple correct answers may exist for a given array.

Find the node where two linked lists merge, return -1 if no merging occurs.

• Traverse both lists to find their lengths and the difference in lengths

• Move the pointer of the longer list by the difference in lengths

• Traverse both lists simultaneously until they meet at the merging point

The task is to find the minimum number of operations required to convert one string into another using delete, replace, and insert operations.

• Use dynamic programming to solve the problem efficiently.

• Create a 2D array to store the edit distances between substrings of the two input strings.

• Fill up the array based on the minimum of three possible operations: insert, delete, or replace.

• The final answer will be the value at the bottom right corner of the array.

• Example: For strings...read more

Identify the K most frequent words in a list, sorted by frequency and lexicographical order.

• Use a hashmap to store word frequencies

• Use a min heap to keep track of K most frequent words

• Sort the heap based on frequency and lexicographical order

Find the K closest points to the origin in a 2-D plane using Euclidean Distance.

• Calculate the Euclidean Distance of each point from the origin

• Sort the points based on their distances from the origin

• Return the first K points as the closest points

Find the Lowest Common Ancestor (LCA) of two nodes in a binary tree.

• Traverse the binary tree to find the paths from the root to nodes X and Y.

• Compare the paths to find the last common node, which is the LCA.

• Handle cases where one node is an ancestor of the other.

• Consider edge cases like when X or Y is the root node.

• Implement a recursive or iterative solution to find the LCA efficiently.

Implement a binary tree class from scratch to handle insert, delete, and random retrieval queries.

• Create a binary tree class with insert and delete methods.

• Implement a method to randomly retrieve a node from the tree.

• Ensure equal chance of selection for each node during random retrieval.

• Handle different types of queries ('I', 'D', 'R') on the binary tree.

• Return the value of the randomly chosen node for each test case.

Find all the bridges in an undirected graph.

• Use Tarjan's algorithm to find bridges in the graph.

• A bridge is an edge whose removal increases the number of connected components.

• Check for bridges by removing each edge and checking the number of connected components.

• Return the edges that are bridges in non-decreasing order.

Implement functions to calculate mean, median, and mode of an integer array.

• Calculate mean by summing all elements and dividing by total count

• Calculate median by sorting array and finding middle element(s)

• Calculate mode by finding element with highest frequency

Compute the maximum length of a string that can be formed by joining given strings based on a condition.

• Iterate through each string and store the count of strings ending with 'R' and 'B'.

• Check if there are any strings ending with 'R' and 'B' that can be combined to form a longer string.

• Return the maximum length of the string that can be formed or 0 if no combination is possible.

Return all prime numbers less than or equal to a given positive integer N.

• Iterate from 2 to N and check if each number is prime using a helper function.

• A number is prime if it is not divisible by any number from 2 to its square root.

• Return the prime numbers in increasing order for each test case.

Construct a binary tree from preorder traversal and leaf node information.

• Create a binary tree using preorder traversal and leaf node information.

• Use a stack to keep track of nodes and their children.

• Handle leaf nodes appropriately to construct the tree.

• Traverse the preorder list to construct the binary tree.

Create a deep copy of a linked list with random pointers.

• Iterate through the original linked list and create a new node for each node in the list.

• Store the mapping of original nodes to new nodes in a hashmap to handle random pointers.

• Update the random pointers of new nodes based on the mapping stored in the hashmap.

• Return the head of the copied linked list.

Sort a linked list containing values 0, 1, and 2 exclusively.

• Use three pointers to keep track of nodes with values 0, 1, and 2 separately.

• Traverse the linked list and move nodes to their respective positions based on their values.

• Finally, concatenate the three lists in the order 0 -> 1 -> 2 to get the sorted linked list.

Find the maximum sum that can be obtained from a path in a matrix from the first row to the last row.

• Use dynamic programming to keep track of the maximum sum at each cell.

• Consider moving down, down-left, and down-right to calculate the maximum sum.

• Start from the second row and update the values based on the maximum sum from the row above.

• At the end, find the maximum sum in the last row to get the final result.

Group anagrams together in a list of strings.

• Iterate through the list of strings and sort each string to group anagrams together.

• Use a hashmap to store the sorted string as key and the original string as value.

• Return the values of the hashmap as the grouped anagrams.

The task is to calculate the total number of unique paths from the top-left to bottom-right corner of an M x N matrix by moving only right or down.

• Use dynamic programming to solve this problem efficiently.

• Create a 2D array to store the number of unique paths for each cell in the matrix.

• Initialize the first row and first column with 1 as there is only one way to reach each cell in the first row and column.

• For each cell (i, j), the number of unique paths is the sum of the paths...read more

Check if a given singly linked list of integers is a palindrome or not.

• Traverse the linked list to find the middle element using slow and fast pointers.

• Reverse the second half of the linked list.

• Compare the first half with the reversed second half to check for palindrome.

• Handle odd and even length linked lists separately.

• Example: For input 1 2 1 -1, the linked list is a palindrome.

Rotate a matrix to the right 'K' times by shifting each column to the right 'K' times.

• Iterate 'K' times to perform right rotation on the matrix

• Shift each column to the right by one position in each rotation

• Handle the edge cases where 'K' is greater than the number of columns

Find all possible paths for a rat in a maze from source to destination.

• Use backtracking to explore all possible paths in the maze.

• Keep track of visited cells to avoid revisiting them.

• Recursively try moving in all directions (up, down, left, right) until reaching the destination.

• Return the list of valid paths sorted in alphabetical order.

Given a 2D matrix with sorted rows and columns, determine if a given integer is present in the matrix.

• Iterate through the matrix starting from the top right corner or bottom left corner to efficiently search for the target integer.

• Use the sorted property of rows and columns to eliminate rows or columns based on the comparison with the target integer.

• If the target integer is greater than the current element, move down in the matrix. If it is smaller, move left.

• Continue this pr...read more

Determine if a robot can reach a specified destination in a matrix by moving only downwards or rightwards.

• Start at (0,0) and move towards the destination (x, y) only downwards or rightwards.

• Check if the path is clear (1) and avoid obstacles (0) while staying within matrix boundaries.

• Return true if the robot can reach the destination, false otherwise.

• Example: For input matrix [[1, 0, 1], [1, 1, 1], [1, 1, 5]] with destination (2, 2), the output is true.

Implement a BSTIterator class to traverse a Binary Search Tree in inorder manner.

• Implement a constructor to initialize the iterator with the root of the BST.

• Implement next() and hasNext() methods to traverse the BST in inorder.

• Implement prev() and hasPrev() methods to access the previous element in the inorder traversal.

• Use level-order traversal format to represent the tree input.

• Output the inorder traversal of the binary search tree for each test case.

Calculate the distance between two nodes in a binary tree.

• Traverse the tree to find the paths from the root to each node

• Find the lowest common ancestor of the two nodes

• Calculate the distance by adding the distances from the LCA to each node

Reverse a linked list in groups of size K by reversing nodes in each group.

• Iterate through the linked list in groups of size K

• Reverse each group of nodes

• Handle cases where the last group may not have K elements

Calculate the total amount of rainwater that can be trapped between given elevations in an array.

• Iterate through the array and calculate the maximum height on the left and right of each bar.

• Calculate the amount of water that can be trapped at each bar by taking the minimum of the maximum heights on the left and right.

• Sum up the trapped water at each bar to get the total trapped water for the entire array.

Merge two sorted linked lists into a single sorted linked list.

• Create a dummy node to start the merged list

• Compare nodes from both lists and add the smaller one to the merged list

• Move the pointer of the merged list and the list with the smaller node

• Handle cases where one list is exhausted before the other

• Return the head of the merged list

Implement a program to compress a string by replacing consecutive duplicates with the count of repetitions.

• Iterate through the string and keep track of consecutive characters and their counts.

• Replace consecutive duplicates with the count of repetitions.

• Ensure the count of repetitions is ≤ 9.

• Return the compressed string.

The task is to find the total number of ways to make change for a specified value using given denominations.

• Use dynamic programming to solve this problem efficiently.

• Create a 2D array to store the number of ways to make change for each value up to the specified value.

• Iterate through each denomination and update the array accordingly.

• The final answer will be the value at the last cell of the array.

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)]

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.

Validate if a given binary tree is a Binary Search Tree (BST) or not.

• Check if the left subtree of a node contains only nodes with data less than the node's data.

• Check if the right subtree of a node contains only nodes with data greater than the node's data.

• Recursively check if both the left and right subtrees are also binary search trees.

• Example: For a node with data 4, left subtree nodes (2, 1, 3) are smaller and right subtree node (5) is larger.

Flatten a linked list of sorted child linked lists into a single sorted linked list.

• Traverse the linked list and maintain a priority queue to keep track of the next smallest element.

• Merge the child linked lists into the priority queue while traversing the main linked list.

• Pop elements from the priority queue to create the final flattened linked list.

Convert a Binary Search Tree to a Greater Sum Tree by replacing each node's value with the sum of all node values greater than the current node's value.

• Traverse the BST in reverse inorder (right, root, left) to visit nodes in descending order.

• Keep track of the running sum of visited nodes and update each node's value with this sum.

• Modify the BST in place without creating a new tree.

• Example: Input BST: 4 1 6 0 2 5 7 -1 -1 -1 3 -1 -1 -1 -1. Output Greater Sum Tree: 26 30 21 36 ...read more

Merge two balanced BSTs into a single balanced BST and return the root node of the new balanced BST.

• Create inorder traversals of both BSTs

• Merge the two inorder traversals into a single sorted array

• Build a new balanced BST from the sorted array

Search for integers in a rotated sorted array efficiently.

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

• Based on the pivot point, apply binary search on the appropriate half of the array.

• Return the index of the integer if found, else return -1.

Find the maximum element between two nodes in a Binary Search Tree (BST) path.

• Traverse the BST to find the path between NODE1 and NODE2.

• Keep track of the maximum element encountered in the path.

• Return the maximum element found, or -1 if NODE1 or NODE2 are not in the BST or no elements exist between them.

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.

Calculate the height of a Binary Tree using Inorder and Level Order traversals without constructing the tree.

• Use the properties of Inorder and Level Order traversals to determine the height of the Binary Tree.

• The height of a Binary Tree is the number of edges on the longest path from the root to a leaf node.

• Consider edge cases like a single node tree or empty tree while calculating the height.

Generate a pattern of numbers in rows following a specific sequence based on powers of 2.

• Start with 1 number in the first row, 2 numbers in the second row, 4 numbers in the third row, and so on based on powers of 2.

• Fill the pattern with numbers in increasing sequence from 1 to 9, recycling back to 1 after reaching 9.

• Output the pattern for a given number 'N' of rows.

• Example: For N = 4, the pattern would be 1, 23, 4567, 89123456.

Find pairs of nodes in a BST that sum up to a given value 'S'.

• Traverse the BST in-order to get a sorted list of nodes.

• Use two pointers approach to find pairs with sum 'S'.

• Keep track of visited nodes to avoid using the same node twice in a pair.

Given a matrix of characters, determine if a word can be formed by selecting adjacent characters.

• Parse input to get matrix dimensions, characters, and queries

• For each query, search for the word in the matrix by checking adjacent characters

• Output '1' if word is present, '0' if not

Convert a Binary Search Tree into a Greater Sum Tree by replacing each node's value with the sum of all nodes' values greater than the current node's value.

• Traverse the BST in reverse inorder (right, root, left) to visit nodes in descending order.

• Keep track of the running sum of visited nodes' values and update each node's value with this sum.

• Recursively apply the above steps to all nodes in the BST.

• Example: For input BST [4, 1, 6, 0, 2, 5, 7], the output Greater Sum Tree wil...read more

Find the maximum element in the path from NODE1 to NODE2 in a Binary Search Tree.

• Traverse the BST from NODE1 to NODE2 while keeping track of the maximum element encountered.

• If NODE1 or NODE2 does not exist in the BST, return -1.

• The path does not include the values of NODE1 and NODE2 themselves, except when no intermediary nodes exist.

Validate if a given binary tree is a Binary Search Tree (BST) or not.

• Check if the left subtree of a node contains only nodes with data less than the node's data.

• Check if the right subtree of a node contains only nodes with data greater than the node's data.

• Ensure that both the left and right subtrees are also binary search trees.

• Traverse the tree in an inorder manner and check if the elements are in sorted order.

• Use recursion to validate each node in the tree.

Check if it is feasible to complete all courses with prerequisites.

• Create a graph representing the prerequisites with courses as nodes and edges as prerequisites.

• Perform a topological sort on the graph to check if there is a cycle (if there is, then it's not feasible to complete all courses).

• If there is no cycle, then it is feasible to complete all courses.

Find the length of the longest substring without repeating characters in a given string.

• Use a sliding window approach to keep track of the longest substring without repeating characters.

• Use a hashmap to store the index of each character as it appears in the string.

• Update the start index of the window when a repeating character is found.

• Calculate the maximum length of the window as you iterate through the string.

• Return the maximum length as the result.

Identify missing numbers within the range of smallest and largest elements in an array.

• Find the smallest and largest elements in the array.

• Generate a list of numbers within the range of smallest and largest elements.

• Remove the numbers that are present in the array to get the missing numbers.

• Sort and return the missing numbers.

Given a string, partition it into palindromes and return all possible configurations.

• Use backtracking to generate all possible palindrome partitions

• Check if each substring is a palindrome before adding it to the partition

• Return all valid partitions as an array of strings

BFS traversal of an undirected and disconnected graph starting from vertex 0.

• Start BFS traversal from vertex 0 and visit all connected nodes in sorted order.

• Use a queue to keep track of nodes to visit next.

• Keep a visited array to avoid revisiting nodes.

• Print the BFS traversal path as the nodes are visited.

• Example: For input V=5, E=4 and edges 0-1, 0-2, 1-3, 2-4, the BFS traversal will be [0, 1, 2, 3, 4].

Print the left view of a binary tree given in level order form.

• Traverse the tree level by level and print the first node encountered at each level

• Use a queue to perform level order traversal

• Keep track of the level while traversing the tree

Print all possible paths from top-left to bottom-right in a matrix by moving only right or down.

• Use backtracking to explore all possible paths from top-left to bottom-right in the matrix.

• At each cell, recursively explore moving right and down until reaching the bottom-right corner.

• Keep track of the current path and add it to the result when reaching the destination.

Calculate the sum of proper divisors of a given natural number.

• Iterate from 1 to sqrt(N) and check for divisors

• If a divisor is found, add it to the sum and also add N/divisor if it is not the same as divisor

• Return the sum as the result

Design and implement a class BSTIterator to perform in-order traversal over a Binary Search Tree (BST).

• Implement a parameterized constructor to initialize the iterator with the root of the BST.

• Implement a method 'next()' to return the next smallest element in in-order traversal.

• Implement a method 'hasNext()' to check if there exists a next smallest element in traversal.

• Ensure the output is the in-order traversal of the BST using the iterator.

Identify and return the first non-repeating character in a string, or the first character if all characters repeat.

• Iterate through the string to count the frequency of each character

• Iterate through the string again to find the first character with frequency 1

• If no such character is found, return the first character of the string

Explaining how to handle 'n' in a string during swapping process

• Identify the positions of 'n' in the string

• Exclude those positions from the swapping process

• Use a temporary variable to swap the characters

• Ensure the swapped characters are not 'n'

• Return the modified string

Calculate and print the median after each new integer is added to the stream.

• Use a min heap to store the larger half of the numbers and a max heap to store the smaller half of the numbers.

• Keep the two heaps balanced by ensuring the size difference is at most 1.

• If the total number of elements is odd, the median is the top element of the larger heap. If even, average the tops of both heaps.

• Update the heaps as new elements are added to the stream.

Remove duplicates from a sorted linked list without adjacent duplicates.

• Traverse the linked list while comparing current and next nodes.

• If they are equal, skip the next node by updating the current node's next pointer.

• Repeat until the end of the list is reached.

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

Reverse all the words in a given string

• Split the string into an array of words

• Loop through the array and reverse each word

• Join the reversed words back into a string

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.

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

To find the maximum difference between a node and its descendant in the same path in a binary tree, we can perform a depth-first search while keeping track of the minimum value encountered so far.

• Perform a depth-first search on the binary tree, keeping track of the minimum value encountered so far in the path.

• At each node, calculate the difference between the current node value and the minimum value encountered so far in the path.

• Update the maximum difference found so far if ...read more

Static memory allocation is done at compile time, while dynamic memory allocation is done at runtime.

• Static memory allocation is fixed in size and allocated on the stack, while dynamic memory allocation can change in size and is allocated on the heap.

• Static memory allocation is determined at compile time, while dynamic memory allocation is determined at runtime.

• Static memory allocation is less flexible but faster, while dynamic memory allocation is more flexible but slower.

• Ex...read more

I would rate my basic communication skills as strong and my confidence as high.

• I have experience effectively communicating with team members and stakeholders.

• I am comfortable presenting my ideas and discussing technical concepts.

• I actively seek feedback to improve my communication skills.

• I have successfully led meetings and discussions on project requirements.

ACID properties ensure database transactions are processed reliably. Memory management involves allocating and deallocating memory efficiently.

• ACID properties: Atomicity, Consistency, Isolation, Durability

• Atomicity ensures that either all operations in a transaction are completed successfully or none are

• Consistency ensures that the database remains in a valid state before and after the transaction

• Isolation ensures that transactions are executed independently without interfere...read more

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.

Function to return unique number for each string of at most 5 characters with O(1) space.

• Use a hash function to map each string to a unique number.

• Ensure that the hash function has a constant time complexity.

• Use a fixed-size array to store the hash values for each string.

Kruskal's algorithm finds MST by sorting edges, adding smallest edge that doesn't create a cycle, repeat until all vertices are connected.

• Sort all edges in non-decreasing order of their weights.

• Initialize an empty graph to store the MST.

• Iterate through sorted edges and add the smallest edge that doesn't create a cycle in the MST.

• Repeat until all vertices are connected in the MST.

To make a copy of a linked list with two pointers, iterate through the original list and create a new node for each element.

• Iterate through the original linked list

• Create a new node for each element

• Set the 'next' pointer of each new node

• Set the 'arbitrary' pointer of each new node

The question asks how to feed a 2D matrix with values based on the given binary tree.

• Traverse the binary tree and for each node, update the corresponding row in the matrix

• Use a recursive function to update the matrix values

• Start with the root node and recursively update its descendants

• Set M[i, j] to 1 if node i is an ancestor of node j

• Repeat the process for all nodes in the binary tree

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.