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debug

Debug a bug or unexpected behavior systematically. Use when the user says "there's a bug", "this isn't working", "I'm getting an error", "help me debug", "why is this failing", "unexpected behavior", "test is failing", "something is broken", or describes behavior that doesn't match expectations - even if they don't say "debug".

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

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Overview

Based on "The Pragmatic Programmer" by Andrew Hunt & David Thomas. Hunt & Thomas's debugging philosophy: debugging is a puzzle to be solved with evidence, not a crisis to be panicked through. The key discipline is don't guess. Form a hypothesis, predict what you'll see if the hypothesis is correct, test it, and observe. Repeat.

Their rubber duck principle: before asking for help, explain the problem out loud (to a rubber duck or anyone). The act of articulating often reveals the answer.

Workflow

Step 1: Reproduce the bug reliably

You cannot debug what you cannot reproduce.

  • What exact steps produce the bug? Document them.
  • Is it 100% reproducible or intermittent?
  • On which environments? (dev only, staging, prod?)
  • Since when? (what changed recently?)

If you can't reproduce it reliably, make that the first problem to solve.

Step 2: Understand the expected vs actual behavior

State explicitly:

  • Expected: what should happen?
  • Actual: what is happening?
  • Evidence: logs, error messages, screenshots

Do not skip this. Vague bug descriptions lead to fixing the wrong thing.

Step 3: Form a hypothesis

What is your best theory for why the actual differs from expected? Write it down. Debugging without a hypothesis is random exploration.

Step 4: Predict the evidence

If your hypothesis is correct, what will you see when you look at [specific thing]? Make a prediction before you look. This keeps you honest.

Step 5: Test the hypothesis

  • Add targeted logging or use a debugger to observe the predicted evidence
  • Change one thing at a time - not multiple
  • If the evidence matches: hypothesis confirmed, move to Step 6
  • If the evidence doesn't match: your hypothesis is wrong, go back to Step 3

Step 6: Fix the root cause (not the symptom)

Hunt & Thomas: fix the problem, not the symptom.

  • Symptom fix: catching an exception that shouldn't be thrown
  • Root cause fix: understanding why the exception is thrown and preventing it

Ask "why" five times before writing the fix.

Step 7: Verify the fix

  • Does the original reproduction case pass?
  • Do existing tests still pass?
  • Write a test that would have caught this bug originally

Step 8: Document the learning

What was the root cause? What made it hard to find? How could it be caught earlier next time?

Anti-Patterns

1. Guessing instead of hypothesizing Bad: Randomly changing things until it works. Good: Form a hypothesis. Predict evidence. Test. Observe. Either confirm or refute.

2. Fixing the symptom Bad: Adding a null check to stop the crash. Good: Understanding why null is reaching that point and preventing it at the source.

3. Changing multiple things at once Bad: "Let me try these 5 changes together." Good: One change at a time. Otherwise you don't know which change fixed it.

4. Not writing a regression test Bad: Fix the bug, move on. Good: Write a test that reproduces the bug before fixing it. The test passes after the fix. It lives in the suite forever.

Quality Checklist

  • Bug is reproducible with documented steps
  • Expected vs actual behavior stated explicitly
  • Hypothesis written down before testing
  • Evidence predicted before looking
  • One change at a time during investigation
  • Root cause identified (not just symptom)
  • Fix verified against original reproduction case
  • Regression test written

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