9 Algorithm Interview Questions and Answers for Programmers

Updated 31 March 2023

A programmer writes code or computer instructions to create software programs, websites and other similar applications. They use algorithms to solve problems in a systematic and logical way by following step-by-step instructions for tasks such as sorting data, searching for specific items or calculating mathematical equations.

Knowing what algorithm interview questions an employer might ask you can help you obtain a job in the programming field. In this article, we list nine algorithm questions for programming interviews and provide sample responses to help you ace them.

Find programmer jobs

9 algorithm interview questions with sample answers

If you're applying for a job as programmer, these are some algorithm questions an employer may ask. Also here are the reasons behind asking these questions and sample answers to help you craft your own:

1. What's the relationship between data structures and algorithms?

An employer might ask a programmer this question since these two concepts are fundamental to software engineering. It enables them to gauge a potential employee's programming skills and ability to solve difficult computing problems. In your answer, provide a detailed overview of how each function to create effective coding.

Example: 'Data structures are complex arrangements of items which allow for efficient organisation, retrieval and manipulation of data. Meanwhile, algorithms are a set of instructions that perform operations on the data. Algorithms rely on data structures to store, access, modify and delete information. Together, they form a powerful combination for efficient problem-solving since algorithms can process data according to the structure of the data'.

2. What's a binary search?

An employer may ask this question to measure your ability to efficiently search for data. In your response, explain how a binary search works and why it's more efficient than other methods.

Example: 'A binary search is an algorithm that programmers can use to locate a data item in an array. An array is a collection of items stored in a specific order. A binary search can locate a data item by dividing the number of elements in half with each iteration, thus reducing the amount of time necessary to find an element.

Instead of looping through every item in the array to check for a match, it only checks items that are likely to contain the desired result. This makes it much more efficient than a linear search, which searches for an element in a list by sequentially going through the list one element at a time'.

3. What's a bucket sort algorithm and how do you implement it?

This question tests your knowledge of sorting algorithms and your ability to write efficient code. This helps employers assess your programming skills. Explain how a bucket sort algorithm works and provide an overview of its implementation.

Example: 'Bucket sort is an efficient sorting algorithm that sorts elements into buckets, namely smaller groups of data. It then organises these buckets individually using another sorting algorithm such as insertion sort, the result being that all the elements are collectively in order at the end. To implement, I first divide the range of values into n buckets then traverse the array and assign each element to its respective bucket. Next, I use a suitable sorting algorithm to sort each bucket independently. Finally, I can combine them together to achieve a fully sorted array'.

4. Explain what a cryptographic algorithm is and list three types.

Employers ask this question to assess your understanding of cryptography. When answering, define the term and outline three various types. Be sure to explain each type in some detail so that the interviewer can get a better understanding of the level of your knowledge.

Example: 'A cryptographic algorithm is a type of mathematical equation that can encrypt data so that only someone who has the correct key can read it. Symmetric-key algorithms, such as Data Encryption Standard (DES) and Advanced Encryption Standard (AES), use the same key for both encryption and decryption. Public-key algorithms, such as RSA, require two different keys, namely one for encryption and one for decryption. Hash functions, like SHA-256, generate a unique output, known as a digest, when inputted with data or text. Stream ciphers encrypt data in bits or bytes one at a time'.

5. For what types of problems can you use divide and conquer algorithms?

With this question, the interviewer is determining your knowledge of this approach and evaluating your problem-solving skills. In your answer, describe how divide-and-conquer algorithms work, giving examples of problems they can solve. If possible, you can also include a personal example of when you used a divide-and-conquer algorithm to solve a problem at work.

Example: 'Divide and conquer algorithms are a type of problem-solving technique in which the problem divides into smaller subproblems that I can then solve more easily. These algorithms are useful because they can solve difficult problems, such as sorting and searching, by dividing the problem into multiple parts. Examples of problems include binary search, sorting algorithms and the optimisation of convex functions. For instance, I implemented a binary search algorithm to quickly find an element in a large array using its position'.

6. What's dynamic programming and when do you use it?

Employers ask this question to evaluate your ability to solve optimisation problems. When replying, define the term, explain when you use it and describe why it's effective.

Example: 'Dynamic programming is an algorithm design technique I can use to solve optimisation problems. It works by finding the solutions to smaller, intermediate subproblems. This method is useful for optimising problems with overlapping subproblems, such as travelling salesman or knapsack problems. It's effective because it avoids solving the same problem repeatedly by caching solutions to subproblems. I have experience using dynamic programming to solve the travelling salesperson problem, which involved finding a set of paths that span all cities with the lowest cost'.

7. How does the Fibonacci heap relate to the Dijkstra and Prim algorithms?

This question tests your understanding of the Fibonacci heap and its relationship to two classic algorithms, Dijkstra's and Prim's. When replying, define all of the relevant terms and explain how the Fibonacci heap can improve the performance of both algorithms.

Example: 'The Fibonacci heap is a data structure I can use to improve the performance of both Dijkstra's and Prim's algorithms. Dijkstra's algorithm can find the shortest paths between nodes in a graph, whereas Prim's algorithm can find a minimum spanning tree in a weighted graph. You can usually find both in network routing protocols, computer graphics and AI applications like game theory and natural language processing. They relate to the Fibonacci heap because the data structure can reduce the complexity of these algorithms. This means I can find the shortest paths and minimum spanning trees more quickly as it supports deletion and extraction of minimum element in constant time'.

8. How do you implement a binary search tree?

Employers ask this question because the ability to implement a binary search tree is an indicator that a programmer is familiar with basic computer science principles, can think algorithmically and can use logic and mathematical operations. It also reveals their understanding of the time complexity involved in searching a large set of data, which is important for developing efficient software solutions. In your answer, clearly explain the problem-solving process by discussing why you use this type of tree over other data structures and describing how to implement it.

Example: 'To insert nodes into the binary tree, start at the root node and compare it to the value of the node you wish to insert. There are three techniques for traversing through a binary search tree, namely pre-order, in-order and post-order. Implementing a binary search tree includes creating an empty root node, inserting new nodes into the tree and traversing through the tree. I use this type of tree over other data structures because it can quickly search large sets of data. I can find the required information more quickly because it allows me to access data in logarithmic time'.

9. What's Big O notation?

Big O notation is a numerical system used to measure the complexity of an algorithm. It's important to employers because it provides an indication of how scalable and efficient a programmer's code may be. In particular, it can help them understand the time complexity of an algorithm and whether it's suitable for the required task. When responding, explain how Big O notation works and provide examples of the different types of notations.

Example: 'Big O notation measures the complexity of an algorithm. It's a numerical system which helps me determine the time, space or memory required by an algorithm to complete a task. An example of Big O notation is O(n), which means the running time of my algorithm is directly proportional to the input size. The bigger my data set, the longer it takes for my algorithm to finish running. Other notations include O(1), which indicates that the algorithm runs in constant time regardless of the input size, and O(n2), meaning my algorithm scales quadratically with the size of the input'.