systematic-debugging

Tests & Qualité

Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes

Documentation

Systematic Debugging

Overview

Random fixes waste time and create new bugs. Quick patches mask underlying issues.

Core principle: ALWAYS find root cause before attempting fixes. Symptom fixes are failure.

Violating the letter of this process is violating the spirit of debugging.

The Iron Law

NO FIXES WITHOUT ROOT CAUSE INVESTIGATION FIRST

If you haven't completed Phase 1, you cannot propose fixes.

When to Use

Use for ANY technical issue:

Test failures
Bugs in production
Unexpected behavior
Performance problems
Build failures
Integration issues

Use this ESPECIALLY when:

Under time pressure (emergencies make guessing tempting)
"Just one quick fix" seems obvious
You've already tried multiple fixes
Previous fix didn't work
You don't fully understand the issue

Don't skip when:

Issue seems simple (simple bugs have root causes too)
You're in a hurry (rushing guarantees rework)
Manager wants it fixed NOW (systematic is faster than thrashing)

The Four Phases

You MUST complete each phase before proceeding to the next.

Phase 1: Root Cause Investigation

BEFORE attempting ANY fix:

1.Read Error Messages Carefully
Don't skip past errors or warnings
They often contain the exact solution
Read stack traces completely
Note line numbers, file paths, error codes
2.Reproduce Consistently
Can you trigger it reliably?
What are the exact steps?
Does it happen every time?
If not reproducible → gather more data, don't guess
3.Check Recent Changes
What changed that could cause this?
Git diff, recent commits
New dependencies, config changes
Environmental differences
4.Gather Evidence in Multi-Component Systems

WHEN system has multiple components (CI → build → signing, API → service → database):

BEFORE proposing fixes, add diagnostic instrumentation:

```

For EACH component boundary:

Log what data enters component
Log what data exits component
Verify environment/config propagation
Check state at each layer

Run once to gather evidence showing WHERE it breaks

THEN analyze evidence to identify failing component

THEN investigate that specific component

```

Example (multi-layer system):

```bash

# Layer 1: Workflow

echo "=== Secrets available in workflow: ==="

echo "IDENTITY: ${IDENTITY:+SET}${IDENTITY:-UNSET}"

# Layer 2: Build script

echo "=== Env vars in build script: ==="

env | grep IDENTITY || echo "IDENTITY not in environment"

# Layer 3: Signing script

echo "=== Keychain state: ==="

security list-keychains

security find-identity -v

# Layer 4: Actual signing

codesign --sign "$IDENTITY" --verbose=4 "$APP"

```

This reveals: Which layer fails (secrets → workflow ✓, workflow → build ✗)

5.Trace Data Flow

WHEN error is deep in call stack:

See root-cause-tracing.md in this directory for the complete backward tracing technique.

Quick version:

Where does bad value originate?
What called this with bad value?
Keep tracing up until you find the source
Fix at source, not at symptom

Phase 2: Pattern Analysis

Find the pattern before fixing:

1.Find Working Examples
Locate similar working code in same codebase
What works that's similar to what's broken?
2.Compare Against References
If implementing pattern, read reference implementation COMPLETELY
Don't skim - read every line
Understand the pattern fully before applying
3.Identify Differences
What's different between working and broken?
List every difference, however small
Don't assume "that can't matter"
4.Understand Dependencies
What other components does this need?
What settings, config, environment?
What assumptions does it make?

Phase 3: Hypothesis and Testing

Scientific method:

1.Form Single Hypothesis
State clearly: "I think X is the root cause because Y"
Write it down
Be specific, not vague
2.Test Minimally
Make the SMALLEST possible change to test hypothesis
One variable at a time
Don't fix multiple things at once
3.Verify Before Continuing
Did it work? Yes → Phase 4
Didn't work? Form NEW hypothesis
DON'T add more fixes on top
4.When You Don't Know
Say "I don't understand X"
Don't pretend to know
Ask for help
Research more

Phase 4: Implementation

Fix the root cause, not the symptom:

1.Create Failing Test Case
Simplest possible reproduction
Automated test if possible
One-off test script if no framework
MUST have before fixing
Use the superpowers:test-driven-development skill for writing proper failing tests
2.Implement Single Fix
Address the root cause identified
ONE change at a time
No "while I'm here" improvements
No bundled refactoring
3.Verify Fix
Test passes now?
No other tests broken?
Issue actually resolved?
4.If Fix Doesn't Work
STOP
Count: How many fixes have you tried?
If < 3: Return to Phase 1, re-analyze with new information
If ≥ 3: STOP and question the architecture (step 5 below)
DON'T attempt Fix #4 without architectural discussion
5.If 3+ Fixes Failed: Question Architecture

Pattern indicating architectural problem:

Each fix reveals new shared state/coupling/problem in different place
Fixes require "massive refactoring" to implement
Each fix creates new symptoms elsewhere

STOP and question fundamentals:

Is this pattern fundamentally sound?
Are we "sticking with it through sheer inertia"?
Should we refactor architecture vs. continue fixing symptoms?

Discuss with your human partner before attempting more fixes

This is NOT a failed hypothesis - this is a wrong architecture.

Red Flags - STOP and Follow Process

If you catch yourself thinking:

"Quick fix for now, investigate later"
"Just try changing X and see if it works"
"Add multiple changes, run tests"
"Skip the test, I'll manually verify"
"It's probably X, let me fix that"
"I don't fully understand but this might work"
"Pattern says X but I'll adapt it differently"
"Here are the main problems: [lists fixes without investigation]"
Proposing solutions before tracing data flow
"One more fix attempt" (when already tried 2+)
Each fix reveals new problem in different place

ALL of these mean: STOP. Return to Phase 1.

If 3+ fixes failed: Question the architecture (see Phase 4.5)

your human partner's Signals You're Doing It Wrong

Watch for these redirections:

"Is that not happening?" - You assumed without verifying
"Will it show us...?" - You should have added evidence gathering
"Stop guessing" - You're proposing fixes without understanding
"Ultrathink this" - Question fundamentals, not just symptoms
"We're stuck?" (frustrated) - Your approach isn't working

When you see these: STOP. Return to Phase 1.

Common Rationalizations

| Excuse | Reality |

|--------|---------|

| "Issue is simple, don't need process" | Simple issues have root causes too. Process is fast for simple bugs. |

| "Emergency, no time for process" | Systematic debugging is FASTER than guess-and-check thrashing. |

| "Just try this first, then investigate" | First fix sets the pattern. Do it right from the start. |

| "I'll write test after confirming fix works" | Untested fixes don't stick. Test first proves it. |

| "Multiple fixes at once saves time" | Can't isolate what worked. Causes new bugs. |

| "Reference too long, I'll adapt the pattern" | Partial understanding guarantees bugs. Read it completely. |

| "I see the problem, let me fix it" | Seeing symptoms ≠ understanding root cause. |

| "One more fix attempt" (after 2+ failures) | 3+ failures = architectural problem. Question pattern, don't fix again. |

Quick Reference

| Phase | Key Activities | Success Criteria |

|-------|---------------|------------------|

| 1. Root Cause | Read errors, reproduce, check changes, gather evidence | Understand WHAT and WHY |

| 2. Pattern | Find working examples, compare | Identify differences |

| 3. Hypothesis | Form theory, test minimally | Confirmed or new hypothesis |

| 4. Implementation | Create test, fix, verify | Bug resolved, tests pass |

When Process Reveals "No Root Cause"

If systematic investigation reveals issue is truly environmental, timing-dependent, or external:

1.You've completed the process
2.Document what you investigated
3.Implement appropriate handling (retry, timeout, error message)
4.Add monitoring/logging for future investigation

But: 95% of "no root cause" cases are incomplete investigation.

Supporting Techniques

These techniques are part of systematic debugging and available in this directory:

root-cause-tracing.md - Trace bugs backward through call stack to find original trigger
defense-in-depth.md - Add validation at multiple layers after finding root cause
condition-based-waiting.md - Replace arbitrary timeouts with condition polling

Related skills:

superpowers:test-driven-development - For creating failing test case (Phase 4, Step 1)
superpowers:verification-before-completion - Verify fix worked before claiming success

Real-World Impact

From debugging sessions:

Systematic approach: 15-30 minutes to fix
Random fixes approach: 2-3 hours of thrashing
First-time fix rate: 95% vs 40%
New bugs introduced: Near zero vs common
Utiliser l'Agent systematic-debugging - Outil & Compétence IA | Skills Catalogue | Skills Catalogue