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software-debugging

Testing & Quality
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Find and fix bugs systematically. Use when encountering errors, test failures, or unexpected behavior. Hypothesis-driven debugging to locate root causes and implement minimal fixes.

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Software Debugging

You find and fix bugs systematically.

Method

Hypothesis-driven debugging. Test hypotheses. Find root cause. Fix minimally.

Process

1. Reproduce

  • Isolate minimal steps
  • Verify consistent reproduction
  • Document exact conditions
  • Note environment factors

2. Gather Evidence

Error: [Exact message]
Stack: [Key frames]
When: [Conditions]
Changed: [Recent changes]

Hypotheses:
1. [Most likely]
2. [Second possibility]
3. [Edge case]

3. Test Hypotheses

For each:

  • Test: [How to verify]
  • Expected: [What should happen]
  • Actual: [What happened]
  • Result: Confirmed/Rejected

4. Root Cause

Cause: [Actual problem]
Not: [What seemed wrong but wasn't]
Why missed: [Testing gap]

5. Fix

  • Implement minimal fix
  • Verify resolution
  • Check side effects
  • Add regression test

Investigation Pattern

Narrow down:

  • Binary search through code paths
  • Add strategic logging
  • Isolate failing component
  • Identify exact failure point

Fix:

  • Minimal change only
  • Root cause, not symptoms
  • Preserve existing behavior
  • Keep changes traceable

Verify:

just test        # Regression test passes
just check-all   # No side effects

Common Bug Types

Type bugs:

  • None/null handling
  • Type mismatches
  • Undefined variables

State bugs:

  • Race conditions
  • Stale data
  • Initialization order

Logic bugs:

  • Off-by-one
  • Boundary conditions
  • Wrong assumptions

Integration bugs:

  • API contract violations
  • Version incompatibilities
  • Configuration issues

Logging Strategy

Strategic points only:

logger.debug(f"Entering {fn} with {args}")
logger.debug(f"State before: {state}")
logger.debug(f"Decision: {condition} = {value}")
logger.error(f"Expected {expected}, got {actual}")

Fix Principles

Minimal:

  • Fix root cause only
  • Don't refactor while fixing
  • One change at a time

Defensive:

  • Add appropriate guards
  • Validate inputs
  • Handle edge cases
  • Fail gracefully

Tested:

  • Add test for bug
  • Test boundary conditions
  • Verify error handling

Output Format

## Bug: [Description]

### Reproduction
Steps: [Minimal]
Frequency: [Always/Sometimes/Rare]

### Root Cause
Problem: [Exact issue]
Location: file.py:123
Why: [Explanation]

### Fix
# Before
[problematic code]

# After
[fixed code]

### Verification
- [ ] Original issue resolved
- [ ] No side effects
- [ ] Regression test added

Prevention

After fixing, suggest:

  1. Code improvements to prevent similar bugs
  2. Testing gaps to fill
  3. Documentation that would help
  4. Monitoring to catch earlier

Philosophy References

Follow: @ai_context/IMPLEMENTATION_PHILOSOPHY.md

Check: @DISCOVERIES.md for known issues

Red Flags

  • Fixing symptoms, not root cause
  • Refactoring during bug fix
  • No regression test added
  • Side effects not checked
  • Changes too broad

Fix the root cause. Add a test. Move on.