Checklist: What Makes for a Realistic Coding Assessment?

Great assessments focus on real-world skills.

Use realistic scenarios that reflect the job and the industry you’re hiring for. Keep questions adaptive and unpredictable. Choose engaging formats that test problem-solving and creativity, not memorization. The right design minimizes the opportunity—and temptation—for cheating.

Below you’ll find a handy checklist to help you craft more realistic, job-relevant tech interview tasks and asynchronous coding tests.

1. Tools and environment

✅ Primary tools: Does the interview process allow candidates to use industry-standard tools (e.g., IDEs like VS Code)?

✅ Secondary tools: Are relevant secondary tools and resources provided (e.g., packages, libraries, Google/StackOverflow search, AI assistants like Copilot)?

✅ Contextual setup: Are candidates able to work in a setup that mirrors the environment they would encounter in the role (e.g., development tools, code repositories—but also communication and collaboration tools, etc.)?

2. Content realism

✅ Job relevance: Do the questions reflect tasks that are common in the role or industry?

✅ Real-world scenarios: Are the tasks presented in a way that resembles a real-world scenario (e.g., does a coding problem reflect a real product, bug or feature)? 

✅ Problem complexity: Is the problem complex enough to simulate real-world challenges, but not so difficult that it’s unrealistic to solve in the time allotted?

3. Open-endedness

✅ Multiple approaches: Does the question allow for multiple valid solutions?

✅ Room for creativity: Can candidates think critically and innovate in their approach, showcasing their problem-solving abilities?

4. Collaboration potential

✅ Collaborative coding: Can the interview foster back-and-forth collaboration, like in a pair programming session or in a team discussion? Can the interviewer and candidate interact, ask questions, and iterate on solutions?

✅ Communication skills: Does the interview allow candidates to demonstrate how they communicate complex ideas and solutions, just as they would in a collaborative work setting?

5. Time and space

✅ Appropriate time limits: Are the time limits realistic for the task at hand?

✅ Room to think: Does the format give candidates time to think and solve the problem without the pressure of a watching or controlling figure, simulating a normal work environment (e.g., can you leverage a “focus time” feature, to give candidates screen privacy for part of the interview, and time to collect their thoughts)?

6. Industry & role alignment

✅ Specific to role: Does the question relate to the specific team or role within the company?

✅ Connection to business: Does the question relate to the company’s business and its goals (e.g., tasks like update releases for gaming companies or stock pricing for finance firms)?

7. Clarity and specifications

✅ Clear instructions: Are the instructions clear and structured like real job specifications (e.g., Jira/Asana-style tasks)?

✅ Imprecise requirements: Is there room to ask clarifying questions, mimicking the ambiguity often present in real-life work situations?

8. Realistic scenarios and problem types

✅ Legacy context: Does the problem account for legacy code, infrastructure, or systems that candidates may need to work with, especially for senior roles?

✅ Freedom of choice: Does the interview allow the candidate to make technical choices (e.g., libraries, frameworks) and justify their decisions, simulating real job conditions?

9. Feedback mechanism

✅ Iterative review: Can the candidate receive feedback as the interview progresses, similar to how work is reviewed and refined in professional environments?

✅ Learning opportunity: Does the candidate have the opportunity to explain their reasoning or pivot based on feedback, showing how they would adapt to ongoing projects at work?