Microsoft Corporation SDE Interview Questions, Process, and Tips

Efficiently check if a number is present in an array where each element differs by 1.

• Use binary search to find the element in the array

• Calculate the difference between the middle element and the first element

• If the difference is equal to the index of the middle element minus the index of the first element, then the left half of the array is consecutive

• If the difference is not equal, then the right half of the array is ...read more

Microsoft Excel

• Add more chart types (p1)

• Improve collaboration features (p2)

• Enhance data analysis tools (p3)

• Integrate with more external data sources (p4)

• Improve error handling and debugging (p5)

Program to rearrange shuffled 16 squares to get original big square

• Create a 4x4 matrix to represent the big square and fill it with shuffled squares

• Loop through the matrix and check if each square is in the correct position

• If a square is not in the correct position, swap it with the square in the correct position

• Repeat until all squares are in the correct position

The first declaration casts i to int pointer and dereferences it, while the second declaration casts the address of i to int pointer and dereferences it.

• The first declaration assumes i is already an int pointer.

• The second declaration takes the address of i and casts it to an int pointer.

• The first declaration may cause a segmentation fault if i is not an int pointer.

• The second declaration may cause unexpected behavior i...read more

Minimum comparisons needed to find median in unsorted array of size n

• For odd n, median is the middle element. For even n, median is the average of middle two elements

• Minimum comparisons needed for odd n is (n-1)/2. For even n, it is n/2

• Various sorting algorithms can be used to find median in an unsorted array

Time complexity to find an element in an alternatively sorted array.

• The time complexity will be O(log n) using binary search.

• Check the middle element and compare with the target element.

• If the middle element is greater than the target, search in the left half of the array.

• If the middle element is smaller than the target, search in the right half of the array.

• Repeat until the target element is found or the array is exha

Find an index in array where sum of elements on left side is equal to sum of elements on right side.

• Loop through array and calculate sum of all elements

• Then loop through array again and check if sum of elements on left side is equal to sum of elements on right side

• Return the index if found, else return -1

Find minimum number of jumps required to reach end of array with max moves in right direction at each index.

• Use dynamic programming approach to solve the problem

• Maintain an array to store minimum number of jumps required to reach each index

• Traverse the array and update the minimum number of jumps for each index

• Return the minimum number of jumps required to reach the end of array

Tournament tree is a binary tree where each node represents a match between two players/teams.

• Tournament tree is used in sports tournaments to determine the winner.

• The leaf nodes represent the players/teams and the internal nodes represent the matches.

• The winner of each match is the node with the higher score.

• Code can be written using a recursive function to traverse the tree and determine the winner.

Find 2 maximum elements in array in O(n+log(n)) comparison

• Use divide and conquer approach

• Divide array into two halves

• Recursively find max elements in each half

• Compare the two max elements to find the overall max elements

Find row with maximum 1s in a sorted 2D array of 0s and 1s.

• Use binary search to find the first occurrence of 1 in each row.

• Calculate the number of 1s in each row using the index found in step 1.

• Keep track of the row with maximum number of 1s.

• Time complexity: O(m log n), where m is the number of rows and n is the number of columns.