Cheating prevention and detection in Interview

To reduce instances of cheating during live interviews—and to keep the process fair, transparent, and reflective of real-world work—we recommend combining preventive controls, thoughtful interview design, and active interviewer engagement using the following CoderPad features and best practices.

1. Use multi-file projects

Always use a multi-file project template instead of a single-file pad.

Large language models perform significantly worse when they must reason across multiple interdependent files, navigate structure, and maintain context—closely mirroring real production work. Multi-file setups also make it easier to assess a candidate’s ability to understand unfamiliar code and reason holistically.

2. Design questions and sessions for reasoning, not recall

Structure interviews to surface thinking, trade-offs, and adaptability rather than polished final answers.

Best practices include:

• Multi-part or progressive problems that evolve over time
• Asking candidates to explain their approach verbally as they code
• Introducing follow-up changes mid-solution to test flexibility

Helpful probing questions include:

• “Why did you choose this data structure?”
• “What are the trade-offs of this approach?”
• “If performance became an issue, how would you optimize this?”
• “What would happen if we changed X to Y?”

Skilled developers can reason about complexity, edge cases, and constraints. AI-generated answers often struggle under these follow-ups or rely on vague, textbook-style explanations.

3. Enable video and audio

Enable video and audio for live interviews to confirm the candidate is the one coding and to monitor engagement.

• Video helps establish presence and accountability
• CoderPad’s video feature does not allow backgrounds or background filters
• Video and audio can be toggled in the pad settings when launching the session

These signals help interviewers correlate on-screen activity with verbal reasoning in real time.

4. Leverage environment awareness and respond in the moment

CoderPad alerts interviewers when a candidate:

• Pastes code from an external source
• Leaves the IDE (e.g., tab-switching)

These alerts help surface potentially unmonitored activity, but they are most effective when paired with active interviewer response.

Best practices:

• Ask the candidate why they pasted code or left the IDE when alerts appear
• Treat alerts as prompts for clarification, not immediate disqualification
• Watch for patterns such as:
  • Perfect code pasted after long silence
  • Long pauses before answering follow-up questions
  • A mismatch between verbal fluency and technical depth

For higher-security interviews, you may also ask the candidate to share their screen if off-pad activity is suspected.

If you have Interview Summary and Outline enabled, notes and transcripts are automatically generated so you can stay focused on the candidate rather than documentation.

5. Use playback and post-interview verification

Every pad records a complete timeline of the session, including:

• Code edits
• Runs
• Cursor movements
• Copy/paste events
• IDE exit notifications

After the interview:

• Review playback to verify behavior and pacing
• Look for bursts of activity inconsistent with normal typing
• Use AI-generated summaries and transcripts to support consistent, fair post-interview review

Playback provides objective context and helps reduce bias in hiring decisions.

6. Enable and frame in-app AI usage transparently

If AI is part of your developers’ real-world workflow, interviews should reflect that reality.

• Enable AI Assist for candidates so all AI usage is visible within the platform
• Clearly communicate expectations:
  • Any AI usage should remain within the AI Assist tab
  • Candidates should be prepared to explain, critique, and adapt AI-generated output

This allows interviewers to evaluate how candidates use AI, not just whether they use it.

7. Use collaborative and pair-programming techniques

Consider interview formats that emphasize collaboration and real-time problem solving:

• Pair programming or guided live coding
• Debugging exercises
• Verbal reasoning prompts during implementation

Features like name-tagged cursors and “Follow Candidate” mode make it easier to observe how candidates think, communicate, and respond to feedback—skills that are difficult to fake with AI assistance.

8. Control access with the candidate waiting room

Use the candidate waiting room to prevent candidates from entering the pad before you are ready.

This ensures candidates cannot:

• Pre-read instructions
• Explore the file structure early
• Prepare offline solutions before the interview officially begins

When you admit the candidate, you control exactly when the interview environment becomes visible.

9. End interviews to lock the session

Use the “End Interview” action to immediately revoke editing access once the session is complete.

Ending the interview:

• Prevents post-session edits or overwrites
• Finalizes the session timeline
• Ensures playback remains fully reliable for review

Final note

Effective cheating prevention is not just about restrictions—it’s about designing interviews that reward reasoning, transparency, and real-world skills, while giving interviewers the tools and confidence to respond thoughtfully in the moment.