TopCoder Feature Articles: The Intersection of Dynamic Programming and Behavioral Interviews

Alessio Frateily

Hatched by Alessio Frateily

Apr 23, 2024

4 min read


TopCoder Feature Articles: The Intersection of Dynamic Programming and Behavioral Interviews


In the world of computer science, there are various techniques and algorithms that programmers use to solve complex problems. One such technique is dynamic programming (DP), which is applicable to many counting and optimization problems. Meanwhile, in the world of job interviews, behavioral questions are commonly asked to assess a candidate's past experiences and problem-solving skills. Surprisingly, there are common points between these two seemingly unrelated topics. In this article, we will explore the intersection of dynamic programming and behavioral interviews and how they can benefit each other.

Understanding Dynamic Programming:

To understand dynamic programming, one must first have a firm grasp on recursion. Recursion is a programming technique where a function calls itself to solve a problem by breaking it down into smaller, more manageable subproblems. However, if the very thought of recursion makes you uncomfortable, then it's crucial to develop a solid understanding of it before diving into dynamic programming.

Dynamic programming comes into play when you encounter problems that involve finding the "how many," "minimum," "maximum," "shortest," or "longest" solutions. These problems often require you to solve subproblems and build upon their solutions to obtain the optimal result. For example, consider the longest common subsequence problem, where you are given two strings and need to find the longest subsequence that appears in both strings. The characters of the subsequence do not have to appear consecutively in the original strings. By applying dynamic programming, you can efficiently solve this problem and find the longest common subsequence.

Applying Behavioral Interview Techniques:

On the other hand, behavioral interviews aim to assess a candidate's past experiences and problem-solving skills by asking specific questions about their previous work situations. These questions typically revolve around times when the candidate faced challenges, disagreements with team members, or had to take initiative on a project. By using the STAR-L framework (Situation, Task, Actions, Result, Learnings), candidates can effectively structure their answers and provide meaningful insights into their problem-solving abilities.

When answering behavioral questions, it is essential to focus on what you personally did rather than using collective pronouns like "we." It's crucial to explain the impact your actions had and the results they achieved. Additionally, preparing 2-3 stories for each project or experience can help you provide diverse and relevant examples during the interview. Remember to highlight the driving factors behind your decisions and be ready to answer technical questions related to your projects as well.

Connecting the Dots:

Now that we have explored the basics of dynamic programming and behavioral interviews, it's time to connect the dots and see how these two topics intersect. Both dynamic programming and behavioral interviews require individuals to break down complex problems into smaller, more manageable parts. In dynamic programming, this is done through recursive relationships, whereas in behavioral interviews, it is done through the STAR-L framework.

Furthermore, both dynamic programming and behavioral interviews emphasize the importance of taking initiative and finding optimal solutions. Dynamic programming encourages programmers to think critically and build upon subproblem solutions to achieve the best outcome. Similarly, in behavioral interviews, candidates are expected to showcase their ability to take initiative and solve problems effectively.

Actionable Advice:

Before wrapping up this article, here are three actionable pieces of advice for anyone preparing for dynamic programming-based interviews or behavioral interviews:

  • 1. Practice recursion: If you struggle with recursion, take the time to practice writing recursive functions and understanding their logic. Recursion is a fundamental concept in dynamic programming and can greatly improve your problem-solving skills.
  • 2. Prepare diverse stories: Before your behavioral interview, prepare 2-3 stories for each project or experience you have. These stories should showcase different aspects of your problem-solving abilities and highlight your impact on the results.
  • 3. Emphasize customer satisfaction: Whether you're solving a dynamic programming problem or answering a behavioral question, always keep the customer's satisfaction in mind. Focus on how your actions and decisions can satisfy the customer's needs and create a positive impact.


In conclusion, the worlds of dynamic programming and behavioral interviews may seem distinct, but they share common points and can benefit from each other. Understanding recursion is essential for grasping dynamic programming, while the STAR-L framework helps structure answers in behavioral interviews. By applying the principles of dynamic programming to behavioral interviews, candidates can showcase their problem-solving abilities effectively. Remember to practice recursion, prepare diverse stories, and prioritize customer satisfaction in both realms. With these insights in mind, you'll be well-prepared to excel in dynamic programming-based interviews and ace your behavioral interviews.

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