Effective Work Sample Exercises for Hiring Top Software Engineers

Software engineering roles are critical to the success of technology-driven organizations. The right software engineer can accelerate product development, improve code quality, and drive innovation. However, traditional interview methods often fail to accurately assess a candidate's true capabilities and potential fit within your engineering team.

Practical work samples provide a window into how candidates approach real-world engineering challenges. Unlike theoretical questions or whiteboard exercises that test memorization, well-designed work samples reveal problem-solving approaches, coding practices, and technical decision-making skills in context. They also demonstrate how candidates handle feedback and iterate on their solutions—a crucial skill for any engineer.

The best engineering teams use targeted work samples to evaluate specific competencies required for success in their environment. These exercises should mirror the actual work your engineers do daily, from writing clean, maintainable code to debugging complex systems and collaborating on technical designs.

By implementing the following work samples in your interview process, you'll gain deeper insights into each candidate's technical abilities, problem-solving approach, and collaboration style. This leads to more informed hiring decisions and better team fits, ultimately reducing costly hiring mistakes and accelerating your engineering team's productivity.

Activity #1: Code Implementation Challenge

This exercise evaluates a candidate's ability to write clean, functional code that meets requirements. It assesses coding proficiency, attention to detail, and how well they implement solutions to defined problems—core skills for any software engineer.

Directions for the Company:

• Provide a clearly defined coding problem that can be completed in 45-60 minutes.
• The problem should be relevant to your tech stack but not require specialized domain knowledge.
• Create a GitHub repository template with starter code, tests, and a README with clear instructions.
• Allow candidates to use their preferred IDE and development environment.
• Ensure the problem has multiple valid approaches with different trade-offs to reveal the candidate's thinking.

Directions for the Candidate:

• Clone the provided repository and read the README instructions carefully.
• Implement a solution that meets all the requirements specified in the problem statement.
• Write clean, well-documented code with appropriate comments.
• Include unit tests to verify your solution works as expected.
• Be prepared to explain your approach, any trade-offs you considered, and how you might extend the solution given more time.

Feedback Mechanism:

• After reviewing the code, provide specific feedback on one aspect the candidate did well (e.g., "Your solution efficiently handles edge cases") and one area for improvement (e.g., "The error handling could be more robust").
• Give the candidate 10-15 minutes to refactor their code based on the improvement feedback.
• Observe how receptive they are to feedback and their ability to quickly iterate on their solution.

Activity #2: System Design Discussion

This exercise evaluates a candidate's ability to think about architecture, scalability, and technical trade-offs—essential skills for building maintainable software systems that can evolve with changing requirements.

Directions for the Company:

• Prepare a system design scenario relevant to your business (e.g., "Design a service that processes user uploads and generates thumbnails").
• Create a document with the scenario, constraints, and expected deliverables.
• Provide whiteboarding tools (physical or digital) for the candidate to sketch their design.
• Assign an experienced engineer to lead the discussion who can ask probing questions about scalability, fault tolerance, and trade-offs.

Directions for the Candidate:

• Review the system design scenario provided 30 minutes before the discussion.
• Prepare to explain your approach to designing a solution that meets the requirements.
• Be ready to sketch architecture diagrams showing components, data flows, and interfaces.
• Consider scalability, reliability, security, and maintainability in your design.
• Be prepared to discuss alternative approaches and their trade-offs.

Feedback Mechanism:

• Provide feedback on a strength in their design approach (e.g., "Your consideration of caching strategies was thorough").
• Offer one significant area for improvement (e.g., "The database schema might create performance bottlenecks").
• Ask the candidate to revise a specific portion of their design based on this feedback.
• Evaluate their ability to incorporate feedback and adapt their thinking.

Activity #3: Debugging Exercise

This exercise assesses a candidate's troubleshooting skills and ability to navigate unfamiliar code—critical capabilities for maintaining and improving existing systems, which is often a significant part of a software engineer's role.

Directions for the Company:

• Prepare a small, self-contained application with intentionally introduced bugs.
• The bugs should represent common issues (e.g., race conditions, memory leaks, incorrect API usage).
• Include a README with the expected behavior and symptoms of the issues.
• Provide access to necessary debugging tools and documentation.
• Ensure the codebase is small enough to be understood in 15-20 minutes.

Directions for the Candidate:

• Review the provided codebase and understand its intended functionality.
• Identify the bugs causing the application to behave incorrectly.
• Fix the issues and explain your reasoning for each fix.
• Document any additional improvements you would recommend beyond fixing the immediate bugs.
• Be prepared to discuss your debugging approach and how you identified the root causes.

Feedback Mechanism:

• Highlight one effective debugging technique the candidate used (e.g., "Your systematic isolation of the race condition was impressive").
• Suggest one way they could improve their debugging process (e.g., "Using logging strategically might have helped identify the issue faster").
• Ask them to implement this improvement in their approach to finding one remaining bug.
• Observe how they adapt their debugging strategy based on feedback.

Activity #4: Code Review Exercise

This exercise evaluates a candidate's ability to review code critically, identify issues, and communicate feedback constructively—essential skills for maintaining code quality and collaborating effectively in engineering teams.

Directions for the Company:

• Prepare a pull request with 100-200 lines of code that contains various issues:
• Functional bugs
• Performance inefficiencies
• Security vulnerabilities
• Style inconsistencies
• Missing tests
• Include a brief description of what the code is supposed to accomplish.
• Provide context about any relevant coding standards or practices your team follows.

Directions for the Candidate:

• Review the provided pull request as if you were a team member responsible for approving it.
• Identify and document issues you find, categorizing them by severity and type.
• Provide constructive feedback on how to address each issue.
• Highlight any positive aspects of the code that should be preserved.
• Be prepared to discuss how you prioritize different types of issues in code reviews.

Feedback Mechanism:

• Acknowledge one aspect of their review that was particularly thorough or insightful (e.g., "You identified a subtle security vulnerability that many miss").
• Suggest one way they could improve their review approach (e.g., "Consider focusing more on architectural implications").
• Ask them to revise their feedback on one specific issue incorporating this suggestion.
• Evaluate their ability to communicate technical concerns clearly and constructively.

Frequently Asked Questions

How long should each work sample take?

Each exercise should be designed to take 45-60 minutes, including time for feedback and iteration. The entire technical assessment process across multiple interviews should not exceed 4-5 hours of a candidate's time to respect their schedule while still gathering sufficient data for evaluation.

Should we use the same work samples for all levels of software engineers?

While the format can remain consistent, you should adjust the complexity and expectations based on seniority. Junior engineers might focus more on implementation details, while senior candidates should demonstrate stronger system design skills and technical leadership in their approaches.

How do we ensure these exercises don't disadvantage candidates from diverse backgrounds?

Design exercises that focus on fundamental engineering skills rather than specialized knowledge. Provide clear instructions and necessary context. Allow candidates to use familiar tools and environments. Evaluate their problem-solving approach and ability to learn, not just their existing knowledge.

What if a candidate doesn't complete the exercise in the allotted time?

Focus on what they did accomplish and their approach rather than completion. The exercises are designed to be challenging, and how candidates prioritize under time constraints can be informative. Their reasoning about trade-offs and what they would do with more time often reveals more than a rushed complete solution.

How should we weigh these work samples against other interview components?

Work samples should be a significant factor in your evaluation but not the only one. They should be considered alongside behavioral interviews that assess cultural fit, collaboration skills, and growth mindset. The relative weight might vary based on your team's specific needs and values.

Can these exercises be conducted remotely?

Yes, all these exercises can be adapted for remote interviews using collaborative coding platforms, video conferencing with screen sharing, and digital whiteboarding tools. The key is ensuring candidates have access to the necessary tools and clear communication channels.

The hiring process for software engineers should be as thoughtfully engineered as your products. By implementing these work samples, you'll gain deeper insights into candidates' technical abilities and working styles, leading to better hiring decisions and stronger engineering teams.

Yardstick helps companies design and implement effective technical assessments tailored to their specific needs. Our platform provides tools for creating, administering, and evaluating work samples that accurately predict on-the-job performance. Learn more about how we can help improve your technical hiring process by exploring our AI job descriptions, AI interview question generator, and AI interview guide generator.

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