34 Common Dynamic Programming Interview Questions With Tips

By Indeed Editorial Team

Published 3 May 2022

The Indeed Editorial Team comprises a diverse and talented team of writers, researchers and subject matter experts equipped with Indeed's data and insights to deliver useful tips to help guide your career journey.

Dynamic programming is a computer programming technique that involves attempting to overcome a complex problem by dividing it into multiple smaller ones. Regardless of your experience and background, knowing some common dynamic programming interview questions and how to answer them can help you prepare for an interview for a job in the field. Learning more about the common questions and preparing for your interview can significantly improve your chances of success. In this article, we discuss different questions that may come up in dynamic programming interviews and provide some general interview tips.

10 general dynamic programming interview questions

While these dynamic programming interview questions are likely to come up during an interview for a related role, they're also common to most types of interviews:

  1. How did you hear about this job opening?

  2. What's your preferred type of working environment?

  3. Can you tell us a little about yourself?

  4. What do you consider your biggest professional quality?

  5. What do you consider your biggest professional flaw?

  6. Where do you see your career in five years?

  7. How would you describe your ideal job?

  8. What's your primary motivation to continuously improve as a professional?

  9. Why do you think you're the right candidate for this job?

  10. What are some of your passions outside work?

Related: How to Write a Cover Letter for an IT Role (With Example)

10 dynamic programming interview questions about experience and background

Recruiters generally ask these questions to assess the candidate's relevant experience in dynamic programming:

  1. How would you describe your experience in using dynamic programming in your work?

  2. What do you consider your most important professional achievement up to this point?

  3. How did you improve your proficiency in dynamic programming over the past year?

  4. Can you describe a major professional challenge you've faced throughout your career and how you overcame it?

  5. How do you usually blend working within a team with getting individual results?

  6. Can you describe a typical day at one of your previous jobs?

  7. What's the biggest mistake you've made while performing dynamic programming, and how did you recover from it?

  8. What feedback can you provide regarding your previous supervisor?

  9. Based on your previous professional experiences, what attracts you the most and the least about this role?

  10. Compared to similar situations in your career, how would you describe our recruitment process up to this point?

Related: What Is Software Development: Definition, Processes and Types

10 in-depth dynamic programming interview questions

These are some specific technical questions that may come up during interviews for roles that require a dynamic programming background:

  1. How can you use dynamic programming to count the number of ways you can measure a distance?

  2. If you have a set of non-negative integers and a value sum, how can you determine whether there's a subset of the given set with the sum equal to the value sum?

  3. Given a sequence of real numbers from A(1) to A(n), how can you determine a contiguous subsequence as A(i)…A(j) with a maximum sum of elements in the subsequence?

  4. How can you count all possible combinations of n-digit numbers on a typical mobile keypad?

  5. Would you say that Dijkstra's algorithm is dynamic programming or a greedy algorithm?

  6. How does dynamic programming differ from memoisation and recursion?

  7. How can you recognise a problem you can solve with dynamic programming?

  8. Can you use dynamic programming to determine the number of times a pattern appears as a subsequence within a given string?

  9. If given a rope of a certain length and a set of rope prices, i, where 1<=i<=n, how can you use dynamic programming to find the most appropriate way to cut the rope into smaller ropes to maximise profit?

  10. What are the main differences between dynamic programming and the divide-and-conquer paradigm?

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4 interview questions about dynamic programming with sample answers

These are some dynamic programming-related questions that may come up during an interview, plus sample answers you can use to help you formulate your own:

1. How would you describe dynamic programming?

Some interviewers prefer to ask a general open question to assess the candidate's knowledge and ability to define dynamic programming. The two approaches you can take when applying this method are top-down and bottom-up approaches, so it's usually important to mention them when describing dynamic programming. It's also helpful to point out the principal goal of dynamic programming, which is to help improve the efficiency of your work by avoiding recalculating the same subproblems multiple times.

Example answer: 'Dynamic programming is a computing technique that can help you avoid computing the same subproblems multiple times. You can achieve this by implementing dynamic programming algorithms with recursion even when the program doesn't require them. It helps you avoid computational repetition by allowing you to store results in a general table and access them whenever resolving an issue. This can help you determine if you already have the issue resolution within your existing data. You can also use existing data to find a solution to a given problem.'

2. How is dynamic programming different from recursion and memoisation?

Interviewers may ask this question to determine your knowledge and understanding of dynamic programming and other processes you may use in your work. You can answer it by defining each separately while mentioning how they relate to each other. Doing so can showcase your overall programming knowledge.

Example answer: 'Memoisation refers to storing a function call's previous results. Recursion is a method of making a function call itself. Neither makes a difference depending on algorithmic complexity. Dynamic programming is the process of solving significant challenges by dividing them into small parts. While you can use recursion to implement dynamic programming algorithms, you can't use memoisation to optimise it because you only solve each sub-problem once.'

3. What are some typical characteristics of dynamic programming?

Recruiters may ask this question to determine your general dynamic programming familiarity and assess your view of it. Instead of simply defining it, you can improve your answer by mentioning some aspects that make it unique. You can also emphasise how you can use it to improve a programmer's effectiveness and efficiency by offering them a way to address complex problems within a project.

Example answer: 'From my perspective, the primary characteristic of dynamic programming is helping programming professionals save time and energy by storing answers for overlapping questions and providing quick access to them. It does so by allowing them to keep the results of subproblems in an accessible table. This characteristic can help programmers resolve complex issues correctly and quickly.'

4. How do you decide between using a top-down or bottom-up approach?

This question can help recruiters assess your practical experience with dynamic programming. By explaining the context when each technique is appropriate, you can show your ability to process a situation, assess its characteristics and choose an effective resolution. Both approaches have distinct advantages and disadvantages, so a balanced answer is typically an appropriate one.

Example answer: 'When deciding between a top-down and bottom-up approach, the two main factors I consider are time and space complexity. While both methods require creating a table for all sub-problems and sub-solutions, the bottom-up approach may help reduce auxiliary space costs by placing them in topological order. The bottom-up approach may also increase the time working with redundant sub-problems, so I would use the top-down approach if time is a priority.'

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Interview tips for candidates specialising in dynamic programming

Consider these interview tips when attending an interview for a role that requires strong dynamic programming knowledge:

  • Practise some of your answers beforehand: Because interview questions about dynamic programming can be highly technical and complex, practising some basic concepts before the interview can help you sound prepared and knowledgeable. You can practise by giving a friend or colleague a set of common questions and rehearsing the entire interview experience with them.

  • Ask relevant questions: Aside from giving good answers to the recruiter's questions, you can also demonstrate your knowledge by asking appropriate questions. Think about what to ask the recruiter regarding the role and the organisation before the interview.

  • Emphasise your soft skills: Although dynamic programming jobs are highly technical, employees with strong soft skills are more likely to be successful at their jobs. During the interview, try to showcase your communication, problem-solving and critical thinking skills.

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