Top 15 Algorithm Interview Questions

Top 15 Algorithm Interview Questions


When algorithms were first invented, as far back as 2000 B.C.E., the creators probably never imagined they’d be used for driving large, metallic, self-powered chariots known as “cars.” But here we are in the 21st century, using algorithms to run many aspects of our lives, from artificial intelligence to cryptocurrency to logging into basic online services.

So if you’re searching for a job working with algorithms, you’re entering an exciting field with lots of opportunities. But now it’s time to get ready to impress which is why we’ve rounded up 15 algorithm interview questions to help you prepare.

Keep reading to learn the most common algorithm questions, how to answer them, and how to brush up on your skills to get you ready for your interviews.

1. What is an algorithm?

While basic, if you happen to be asked this question, it’s important that you answer confidently and simply. An algorithm is a series of computational steps that takes in an input or multiple inputs and converts it into an output. There are several formats an algorithm can be written in which includes in plain English or as pseudocode.

Once you’ve given a concise answer like this, if you’d like to go deeper, you can do so using an example.

2. What is Quicksort?

This question is meant to test your ability to apply algorithms at least at a very basic level. A Quicksort algorithm sorts queries or lists quickly. It uses what’s referred to as a “divide and conquer” technique, partition exchange, which divides the list of items into three different parts:

  • A pivot element selected from the array
  • Elements less than the pivot element are placed to the left of the pivot to form a left subarray
  • Elements greater than the pivot element are placed to the right of the pivot to form a right subarray

Within the subarrays a pivot element is selected and the remaining values are sorted to the left or right of the pivot. The process is repeated until there only remains a single element in the subarrays.

Time Complexities:

  • Best Case: O(nlogn) This occurs when the pivot element value is close to the middle
  • Worst Case: O(n2) This occurs when the pivot element value is either the largest or smallest value
  • Average Case: O(nlogn)

3. What is the function of a Pivot element?

This is another shallow dive into the basics of algorithms. You can answer by explaining that a pivot element is an element chosen from the array or matrix being worked on to serve as the first element selected by the algorithm to perform calculations.

There are many ways to pick a pivot element. For arrays, pivots can be the last or first element, chosen from the middle, or even randomly selected.  Depending on the algorithm, the way in which the pivot is selected may yield better results.

4. What is meant by the time complexity of an algorithm?

This is another basic element of algorithms, so your answer should begin with a brief definition. The time complexity element of an algorithm refers to the amount of iterations needed for it to be run to completion based on the input size.

5. Explain the different notations used when it comes to time complexity.

When answering this question and any follow-ups, you’re demonstrating your knowledge of how algorithms work, as well as the different ways you can alter them to achieve the desired result.

Using notations helps predict the efficiency of the algorithm. The notations you use for time complexity include:

  • Big Omega: This signifies “more than or same as” iterations. It is the tight lower-bound of the growth of the algorithm’s running time. This would be the best case time complexity.
  • Big-O: This signifies “fewer than or the same as” iterations. It is the tight upper-bound of the growth of the algorithm’s running time. This would be the worst case time complexity.
  • Big Theta: This signifies “the same as” iterations. It ​​is both a tight upper-bound and tight lower-bound on the growth of the algorithm’s running time.
  • Little-O: This signifies “fewer than” iterations. It is ​​an upper-bound that is not asymptotically tight.
  • Little Omega: This signifies “more than” iterations. It is the lower-bound that is not asymptotically tight.

6. How does binary search work?

Binary search is used to find an element within a sorted array. The item in the middle of the array is looked at first. If the element to look for matches the middle item then the search is complete. Otherwise, if the target element is greater than the middle element then the search is repeated on the upper half of the array (all the larger values after the middle). If it is lower than the middle element then the search is done on the lower half of the array (all the smaller values).

Time Complexities:

  • Best Case: O(1) This occurs if the value matches the middle item to begin with.
  • Worst Case: O(logn) Occurs if the value is at one of the end steps or is not in the array at all.
  • Average Case: O(logn)

7. What is meant by a heap sort?

A heap sort involves comparing items using a sorting algorithm. The input is divided between a sorted and unsorted region. What’s shifted to the sorted region is dependent on whether working on a max-heap or min-heap. A max-heap has the element with the maximum value at the root while a min-heap has the minimum value at the root. When using heap sort on a max-heap, the unsorted region shrinks as the largest item is shifted to the sorted region. For min-heap, the smallest item is shifted to the sorted region.

In a max-heap, the parent node’s value is always greater than their children. To sort the elements of a max-heap using heap sort, the following steps are to be followed:

  • Replace the last element of the heap with the root node
  • Remove the newly placed last element from the heap
  • Convert the now binary heap back into a max-heap
  • Repeat the process until there is no more elements

Time Complexities:

  • Best Case: O(nlogn)
  • Worst Case: O(nlogn)
  • Average Case: O(nlogn)

8. What is a skip list used for?

A skip list is used for the data structuring process. It is based on linked-lists and uses probability to build layers of new links on an original linked-list. It can be thought of as looking at a chain of bus routes. There are buses that stop at every stop but there are also buses that make only express stops. The express buses have fewer stops than that of the regular buses. Making new layers in the skip list can be thought of like the express routes. Being able to get to the most-frequented nodes more efficiently can make other tasks like inserting or deleting nodes much easier and faster than some other algorithms.

9. What are some of the most common cryptographic algorithms?

This may feel like a tough question because it sounds like you have to commit a bunch of stuff to memory, but if you miss a couple, they won’t blame you. Also, there are tons of algorithms out there. Here are some:

  • IDEA
  • Blowfish
  • CAST
  • LOKI
  • DES
  • GOST
  • 3-way

10. What is a hash algorithm and how is it used?

You will want to get comfortable answering this question because hash algorithms are popular now due to their use in cryptography. A hash algorithm refers to a hash function, which takes a string and converts it to a fixed length regardless of how long it was to begin with. You can use it for a wide range of applications, from cryptocurrency to passwords and a range of other validation tools.

11. What role do algorithms play in cryptocurrency?

If you’re interviewing for a job related to cryptocurrency, this could be a challenging question, especially if you get lost in the weeds while answering it. One way to answer this question is to mention just how heavily blockchain-based cryptocurrencies rely on cryptography. The blocks or records that make up the blockchain are secured using cryptographic methods like hash algorithms. There are also algorithms used to generate public-private keys and for “mining” cryptocurrencies.

12. How does an encryption algorithm work?

These kinds of algorithm interview questions get closer to the heart of some of the solutions you may be hired to work with. An encryption algorithm converts plain text into a code known as ciphertext. The algorithm uses keys to do this. Longer keys give you more potential options for making your ciphertext.

13. What is a radix sort algorithm?

Radix sort can come in handy with databases, and if your position may involve them, you should be ready to answer this question. Radix Sort is a sorting algorithm that avoids making comparisons by distributing elements into buckets based on their radix instead.  If there are elements with more than one significant digit, then the bucket distribution is repeated for each digit.

14. What is a recursive algorithm?

A recursive algorithm refers to a way of solving a complex problem by segmenting it into smaller sub-problems. You do this again and again until you get a problem that’s small enough that it’s easy to solve. Binary search is one example of an algorithm that can be implemented to be recursive.

15. What are the three laws that govern a recursive algorithm?

These kinds of algorithm interview questions may come as follow-ups for the “What is a recursive algorithm?” question. A recursive algorithm needs to follow these laws:

  • It has to have a base case.
  • It has to call itself.
  • It needs to change its state and shift towards the base case.

Get ready to ace your interviews

Need a refresher on any of these concepts? Not only do we give you the knowledge you need to land a great tech job, but we also provide you with courses and Skill Paths that make it easier to knock your interviews out of the park. These include interview practice with popular coding languages like Java, Javascript, Python, and more.

If you’re ready to position yourself for a great tech job — whether you’re ready to interview or just want to start learning — you can get started with our catalog of courses today.


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