During a code review, what do you look for to ensure high-quality code and adherence to best practices?

Sample answer to the question

During a code review, I mainly look for any bugs that might be lurking in the code. I try to make sure the code is clean, follows the naming conventions we've set as a team, and that it's efficient in terms of performance. I like to ensure that the algorithms implemented are the best fit for the problem being solved and that they're as optimized as they can be. I also watch out for any redundancy or repeated code that could be simplified or refactored.

A more solid answer

When reviewing code, I prioritize ensuring that the algorithms are not only correctly implemented but also chosen wisely based on the problem's complexity. I dive into whether the code follows our best practices - such as DRY (Don't Repeat Yourself) principles and meaningful naming conventions. Additionally, I stay vigilant about potential security vulnerabilities and performance bottlenecks. For instance, in a recent project where we implemented a search feature, I suggested replacing a brute force search with a binary search algorithm which significantly improved performance. I also value collaboration, so I ensure to provide constructive feedback to foster a learning environment and better teamwork.

Why this is a more solid answer:

This solid answer covers a systematic approach to code review, offering a glimpse into the candidate's attention to algorithm choice, best practices, security concerns, and performance optimization. It emphasizes teamwork and the importance of constructive feedback, which aligns with the job description's focus on collaboration, teamwork, and effective communication. The specific example of improving performance by changing algorithms demonstrates analytical and critical thinking. However, the answer can still be enriched by detailing how new technologies and continuous learning are incorporated into the code review process.

An exceptional answer

In my code reviews, I'm meticulous about the details, diving deep into the logic of the algorithm to ensure it's not only the best choice for the task regarding complexity and efficiency but also elegantly implemented. For instance, on a past project dealing with large data sets, I noticed we could switch from a quadratic complexity sorting algorithm to a linearithmic one, streamlining the processing time. I watch out for any code smells which indicate deeper design issues and address them immediately. I advocate for comprehensive commenting and clear documentation, which echoes our responsibility to contribute to maintaining high-quality code repositories. Moreover, I systematically check for opportunities to refactor code, simultaneously keeping an eye open for adaptability, ensuring that the code remains flexible enough to integrate with impending technologies. During the entire process, I balance correction with encouragement, strengthening our collaborative and positive team culture.

Why this is an exceptional answer:

The exceptional answer goes beyond the fundamentals, demonstrating a high level of detail orientation and a strategic approach to code review. This candidate shows awareness of algorithmic complexities and the impact on performance, reinforces the value of maintaining clean code, and advocates for documentation—all crucial for an Algorithm Developer. The story from past experience effectively demonstrates critical thinking and ability to optimize. This answer also indicates that the candidate is aligned with the growth and adaptability aspect of the job, pointing out the balance between maintaining code quality and preparing for future technologies. Finally, it underscores the significance of a supportive team environment, which is vital given the collaborative nature of the role.

How to prepare for this question

Research the company's code standards and best practice expectations. Formulate examples where you've improved code during reviews in past projects, particularly focusing on algorithm optimization.
Practice articulating your thought process during code reviews, including how you handle potential disagreements or suggestions for improvements while maintaining a positive team dynamic.
Prepare to discuss instances where you've had to adapt to new technologies and how you've incorporated them into code reviews. Reflect on how you stay current with algorithmic techniques and advances in your field, as this shows a commitment to continuous learning.
Elaborate on examples that show your attention to detail, such as catching subtle bugs or potential performance issues, and how you communicated those in a constructive way in past code reviews.

What interviewers are evaluating

Algorithm design and analysis
Programming and software development
Collaboration and teamwork
Attention to detail