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Top Sorting Interview Questions and Problems

Last Updated : 21 Mar, 2024
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Here is the collection of the Top 50 list of frequently asked interview questions on Sorting. Problems in this article are divided into three Levels so that readers can practice according to the difficulty level step by step. 

Top-50-Sorting-Coding-Problems-for-Interviews-copy

Top 50 Sorting Coding Problems for Interviews

Sorting Interview Question and Answers:

Question 1: What is a sorting algorithm?

Answer: A sorting algorithm is a method used to arrange elements in a specific order, often from smallest to largest or vice versa, making data easier to manage and search.

Question 2: What are the different types of sorting algorithms?

Answer: There are two types of Sorting algorithms: Comparison based sorting algorithms and non-comparison-based sorting algorithms. Comparison based sorting algorithms include Bubble SortSelection SortInsertion SortMerge SortQuick SortHeap Sort, etc. and non-comparison-based sorting algorithms include Radix SortCounting Sort and Bucket Sort.

Question 3: Why Sorting algorithms are important?

Answer: The effectiveness of other algorithms (like search and merge algorithms) that depend on input data being in sorted lists is enhanced by efficient sorting. Sorting is also frequently helpful for generating output that is readable by humans. Sorting is directly used in divide-and-conquer strategies, database algorithms, data structure algorithms, and many other applications.

Question 4: What is the difference between comparison-based and non-comparison-based sorting algorithms?

Answer: Comparison-based sorting algorithms compare elements to determine their order, while non-comparison-based algorithms use other techniques, like counting or bucketing, to sort elements without direct comparisons.

Question 5: Explain what is ideal Sorting Algorithm?

Answer: The Ideal Sorting Algorithm would have the following properties:

  • Stable: Equal keys are not reordered.
  • Operates in place: Requires O(1) extra space.
  • Worst-case O(n log n) key comparisons: Guaranteed to perform no more than O(n log n) key comparisons in the worst case.
  • Adaptive: Speeds up to O(n) when the data is nearly sorted or when there are few unique keys.

The choice of sorting algorithm depends on the specific requirements of the application. Some algorithms prioritize stability, while others prioritize speed or space efficiency.

Question 6: What is meant by “Sort in Place”?

Answer: In-place algorithms prioritize space efficiency by utilizing the same memory space for both input and output. This eliminates the need for additional storage, thereby reducing memory requirements. Selection Sort, Bubble Sort, Insertion Sort, Heap Sort and Quicksort are in-place sorting algorithms.

Question 7: Which sort algorithm works best on mostly sorted data?

Answer: For mostly sorted data, Insertion Sort typically works best. It’s efficient when elements are mostly in order because it only needs to make small adjustments to place each element in its correct position, making it faster than other sorting algorithms like Quick Sort or Merge Sort.

Question 8: Why is Merge sort preferred over Quick Sort for sorting linked lists?

Answer: Merge Sort is preferred for sorting linked lists because its divide-and-conquer approach easily divides the list into halves and merges them efficiently without requiring random access, which is difficult in linked lists. Quick Sort’s reliance on random access and potential worst-case time complexity makes it less suitable for linked lists.

Question 9: What is Stability in sorting algorithm and why it is important?

Answer: Stability in sorting algorithms means that the relative order of equal elements remains unchanged after sorting. Stable sorting algorithms ensure that equal elements maintain their original positions in the sorted sequence. Some of the stable sorting algorithms are: Bubble Sort, Insertion Sort, Merge Sort and Counting Sort.

Question 10: What is the best sorting algorithm for large datasets?

Answer: For large datasets, efficient sorting algorithms like Merge Sort, Quick Sort, or Heap Sort are commonly used due to their average time complexity of O(n log n), which performs well even with large amounts of data.

Question 11: How does Quick Sort work?

Answer: Quick Sort is a Divide and Conquer sorting algorithm. It chooses a pivot element and rearrange the array so that elements smaller than the pivot are on the left, and elements greater are on the right. Then, recursively apply the partitioning process to the left and right subarrays. Subarrays of size one or zero are considered sorted.

Question 12: What is the worst-case time complexity of Quick Sort?

Answer: In the worst case, Quick Sort may take O(N^2) time to sort the array.  The worst case will occur when everytime the problem of size N, gets divided into 2 subproblems of size 1 and N – 1.

Sorting Interview Problems:

Easy Problems on Sorting:

Problems

Solve

Check if a given array contains duplicate elements within k distance from each other

Solve

Check whether two Strings are anagrams of each other

Solve

Maximum Perimeter Triangle from array

Solve

Maximize array sum after K negations using Sorting

Solve

Sum of minimum absolute difference of each array element

Solve

Sort an array in waveform

Solve

Chocolate Distribution Problem

Solve

Floor in a Sorted Array

Solve

Floor in a Sorted Array

Solve

Find a pair with the given difference

Solve

Medium Problems on Sorting:

Problems

Solve

Triplet Sum in Array (3sum)

Solve

Find a triplet in an array whose sum is closest to a given number

Solve

Find K most occurring elements in the given Array

Solve

Merge Overlapping Intervals

Solve

Arrange given numbers to form the biggest number | Set 1

Solve

Sort an array of 0s, 1s and 2s | Dutch National Flag problem

Solve

K’th Smallest/Largest Element in Unsorted Array

Solve

Inversion count in Array using Merge Sort

Solve

Minimum Number of Platforms Required for a Railway/Bus Station

Solve

Check if two arrays are equal or not

Solve

Find all triplets with zero sum

Solve

Find maximum meetings in one room

Solve

Case-specific Sorting of Strings

Solve

Union of Two Linked Lists

Solve

Sort elements by frequency using STL

Solve

Minimum Increment operations to make Array unique

Solve

Find the maximum number of intersections lines

Solve

Find the point where maximum intervals overlap

Solve

Check if two arrays are equal or not

Solve

Rearrange an array to minimize sum of product of consecutive pair elements

Solve

Position of an element after stable sort

Solve

Merge Sort for Doubly Linked List

Solve

Radix Sort

Solve

Segregate 0s and 1s in an array

Solve

Sort all even numbers in ascending order and then sort all odd numbers in descending order

Solve

Minimum product of k integers in an array of positive Integers

Solve

Permute two arrays such that sum of every pair is greater or equal to K

Solve

Count pairs from two sorted arrays whose sum is equal to a given value x

Solve

Alternative Sorting

Solve

Choose k array elements such that difference of maximum and minimum is minimized

Solve

Hard Problems on Sorting:

Problems

Solve

Alien Dictionary

Solve

Merge two sorted arrays with O(1) extra space

Solve

Count smaller elements on Right side

Solve

Find the smallest positive integer value that cannot be represented as sum of any subset of a given array

Solve

Count of Subarrays of given Array with median at least X

Solve

Merge K sorted linked lists | Set 1

Solve

Smallest Difference Triplet from Three arrays

Solve

Sort n numbers in range from 0 to n^2 – 1 in linear time

Solve

Sort a 2D vector diagonally

Solve

Print Binary Tree levels in sorted order

Solve

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