debugging

Overview

A systematic approach to finding and fixing bugs. Avoids random changes and ensures issues are truly fixed, not just hidden.

When to Use

• Something isn't working as expected
• Tests are failing
• Users report bugs
• Unexpected behavior in production

Steps

1. Reproduce the issue

   • Get exact steps to reproduce
   • Understand expected vs actual behavior
   • Create minimal reproduction if possible

2. Gather information

   • Error messages and stack traces
   • Logs around the time of the issue
   • Recent changes that might be related
   • Environment details

3. Form hypothesis

   • Based on evidence, what might be wrong?
   • What's the simplest explanation?

4. Test hypothesis

   • Add logging/debugging to verify
   • Use debugger to step through
   • Check assumptions

5. Fix the root cause

   • Don't just fix symptoms
   • Consider why the bug was possible
   • Prevent similar bugs in future

6. Verify the fix

   • Confirm original issue is resolved
   • Check for regressions
   • Add test to prevent recurrence

Debugging Techniques

Print/Log Debugging

print(f"DEBUG: variable={variable}, type={type(variable)}")
logger.debug("Reached checkpoint X with state: %s", state)

Binary Search

• Narrow down the problem location by half
• Comment out sections, add early returns
• Git bisect for regression hunting

Rubber Duck

• Explain the problem out loud
• Often reveals assumptions

Sleep On It

• Fresh eyes catch what tired eyes miss

Watch Out For

• Fixing symptoms instead of root cause
• Making multiple changes at once
• Not testing the fix properly
• Assuming you know the cause without evidence
• Ignoring the obvious (typos, wrong file, etc.)

Common Bug Patterns

• Off-by-one errors
• Null/None reference
• Race conditions
• Type mismatches
• Wrong variable scope
• Cached/stale data
• Environment differences