Published 5 December 2022 Updated 5 December 2022 / Career Advice

Practice These Data Structure Interview Questions (and Answers) to Ace Your Technical Interview

If you’re interviewing for a role that involves any type of coding — think Software Developer, Web Developer, Data Scientist, or Game Developer, then there’s a good chance you'll be asked questions related to data structures. And even if you aren’t asked questions specific to this topic, learning data structures gives you a huge advantage during your technical interview.

One of the best ways to prepare for your technical interview and data structure interview questions is to set up a mock interview with a friend or relative and ask them to play the role of the interviewer. They can ask you questions from a list you generate and go in order or mix up the order to keep you on your toes. They can also ask follow-up questions that require you to explain your answers. And don’t hesitate to incorporate details from your past accomplishments and projects in your answers.

If you’re interviewing over Zoom, consider setting up your mock interview over Zoom too. If you’d rather practice solo, you can record yourself answering questions and then play the recording back to find the areas that you need to work on.

To help you prepare for your upcoming interview, here are 15 data structure questions that are worth reviewing before your actual interview.

1. What’s a Graph or Network Structure?

This is a node-and-edge-based structure that documents the relationships between items and is commonly used to model real-life networks such as street and social networks. A tree is one example of a specific type of graph.

2. Describe what an array is and how to access it.

An array refers to a collection that contains data of the same type that are stored within memory locations that are contiguous.

Arrays are the simplest type of data structure and provide fast read/access times because elements are stored together.

3. What’s the difference between linear and non-linear data structures?

A linear structure refers to the elements of your data that are organized in sequence. On the other hand, when your data is distributed non-sequentially, as in a tree, you would say it has a non-linear structure.

4. What’s a multi-dimensional array?

A multi-dimensional array is one that has data structures spanning multiple dimensions. The most common type of array is a two-dimensional array, also known as a matrix, which is essentially a collection of single-dimension arrays.

5. What’s referred to as a linked list?

Linked lists are another common type of data structure. They are a type of collection in which elements are distributed in memory, as opposed to stored contiguously as in an array. The elements are tied or linked by references to the locations of the other items: each item in the list stores the address in memory of the next item.

6. Would a linked list be described as linear or non-linear?

In a way, this could be a kind of trick question. A linked list could be considered non-linear because of how items are stored in memory. But, more generally, it’s classified as a linear or sequential data structure like stacks and queues.

7. What’s a doubly-linked list (DLL)?

A DLL is a more complicated kind of linked list where the node has a pair of references: an address to the following node in the sequence and an address to the previous node.

8. What is meant by a stack in programming?

This can be a tough data structure interview question because “stack” (as in tech stack) can also mean different technologies within an environment. However, in the context of programming, a stack refers to a linear data structure that’s governed by the principle of last-in, first-out (LIFO).

9. What is meant by the term “queue”?

This is another question that could be confusing because it has different meanings depending on the context, but it’s important to always remember the interviewer is interested in what a term means within the programming field. In this context, “queue” refers to a linear data structure that, unlike stack, uses a first-in, first-out (FIFO) approach.

10. What makes a stack different from a queue?

This question is designed to see if you understand the concepts of FIFO and LIFO. With a stack, the most recently added item is the first one to go out. With a queue, the item that was added the first time is the first to go out.

11. What is Big “O” Notation?

Big “O” notation is a way of categorizing the worst-case performance of a given algorithm. It also denotes how an algorithm will generally perform as the input increases. Some of the classes of big “O” include constant time, log n time, and n or linear increase in time.

12. What does the term “hashmap” mean?

“Hashmap” refers to a data structure that uses a hash table, which is often also described as a dictionary. It’s a structure in which data or objects are mapped to a value using a hashing function. A hash table enables fast search, delete, and insertion speeds. It’s a structure that is often employed because of its speed attributes. It falls under the constant time class within big ‘O’ notation.

13. What is constant time complexity?

This question may or may not be a follow-up or precursor to one about hashmap. Constant time complexity refers to an algorithm that takes the same amount of time to run regardless of the scale of the input.

14. What is meant by the term “priority queue”?

“Priority queue” refers to an abstract data type that is similar to a normal queue, except it has a priority associated with its elements. Elements with a higher priority get processed before those with lower priority.

15. Can you store a duplicate key in hashmap?

No, you can’t store a duplicate key in hashmap. Any new additions to a hashmap that use an existing key will override the previous value associated with that key.

More technical interview prep

Need to brush up on any of these topics? You can get a refresher on lists, stacks, and queues and learn about how computer memory works through nodes and pointers in our Linear Data Structures course. Or you can dive into the fundamental data structures of computer science in our Introduction to Algorithms and Linear Data Structures in Swift.

If you’re looking for an advanced course, check out our Learn Complex Data Structures course that’ll get you ready to solve advanced algorithmic problems like path-finding and maintaining priority queues.

For more interview prep, give our complete guide to the technical interview a look, and our tips on answering behavioral interview questions are also good to review. Check out our advice on the whiteboard interview too. Our Career Center offers even more guidance and resources for interviewing, networking, and job-hunting.

If you’re searching for your next course to take, check out our catalog and sign up for a class today.

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