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runesleo-systematic-debugging

v3.0.0

Four-phase debugging framework that ensures root cause investigation before attempting fixes. Never jump to solutions.

Sourced from ClawHub, Authored by runesleo

Installation

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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
NO INVESTIGATION WITHOUT CONTEXT RECALL FIRST

If you haven't completed Phase 0, you cannot proceed to Phase 1. 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 Five Phases

You MUST complete each phase before proceeding to the next.

Phase 0: Context Recall (MANDATORY FIRST STEP)

BEFORE doing ANYTHING else:

  1. Extract Keywords from Error
  2. What's the error type? (OOM, timeout, connection, type error...)
  3. What component? (server, browser, API, database...)
  4. What area of the codebase?

  5. Search for Prior Knowledge

  6. Check project docs, MEMORY files, or past conversations
  7. Search codebase for similar error patterns: grep -r "ErrorType" .
  8. Check git log for related recent changes: git log --oneline -20

  9. Review Results

  10. Found relevant experience? -> Apply directly, skip to Phase 4
  11. Found partial match? -> Use as starting point for Phase 1
  12. Nothing found? -> Proceed to Phase 1, remember to record solution later

  13. Output Format ``` Context Recall:

  14. Query: "xxx"
  15. Found: [description of related knowledge]
  16. Action: [apply experience / continue investigation / no match] ```

VIOLATION: Proceeding to Phase 1 without Context Recall output = process failure.


Phase 1: Root Cause Investigation

BEFORE attempting ANY fix:

  1. Read Error Messages Carefully
  2. Don't skip past errors or warnings
  3. They often contain the exact solution
  4. Read stack traces completely
  5. Note line numbers, file paths, error codes

  6. Reproduce Consistently

  7. Can you trigger it reliably?
  8. What are the exact steps?
  9. Does it happen every time?
  10. If not reproducible -> gather more data, don't guess

  11. Check Recent Changes

  12. What changed that could cause this?
  13. Git diff, recent commits
  14. New dependencies, config changes
  15. Environmental differences

  16. 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 ```

  1. Trace Data Flow
  2. Where does bad value originate?
  3. What called this with bad value?
  4. Keep tracing up until you find the source
  5. Fix at source, not at symptom

Phase 2: Pattern Analysis

Find the pattern before fixing:

  1. Find Working Examples
  2. Locate similar working code in same codebase
  3. What works that's similar to what's broken?

  4. Compare Against References

  5. If implementing pattern, read reference implementation COMPLETELY
  6. Don't skim - read every line
  7. Understand the pattern fully before applying

  8. Identify Differences

  9. What's different between working and broken?
  10. List every difference, however small
  11. Don't assume "that can't matter"

  12. Understand Dependencies

  13. What other components does this need?
  14. What settings, config, environment?
  15. What assumptions does it make?

Phase 3: Hypothesis and Testing

Scientific method:

  1. Form Single Hypothesis
  2. State clearly: "I think X is the root cause because Y"
  3. Write it down
  4. Be specific, not vague

  5. Test Minimally

  6. Make the SMALLEST possible change to test hypothesis
  7. One variable at a time
  8. Don't fix multiple things at once

  9. Verify Before Continuing

  10. Did it work? Yes -> Phase 4
  11. Didn't work? Form NEW hypothesis
  12. DON'T add more fixes on top

  13. When You Don't Know

  14. Say "I don't understand X"
  15. Don't pretend to know
  16. Ask for help
  17. Research more

Phase 4: Implementation

Fix the root cause, not the symptom:

  1. Create Failing Test Case
  2. Simplest possible reproduction
  3. Automated test if possible
  4. One-off test script if no framework
  5. MUST have before fixing

  6. Implement Single Fix

  7. Address the root cause identified
  8. ONE change at a time
  9. No "while I'm here" improvements
  10. No bundled refactoring

  11. Verify Fix

  12. Test passes now?
  13. No other tests broken?
  14. Issue actually resolved?

  15. If Fix Doesn't Work

  16. STOP
  17. Count: How many fixes have you tried?
  18. If < 3: Return to Phase 1, re-analyze with new information
  19. If >= 3: STOP and question the architecture (step 5 below)
  20. DON'T attempt Fix #4 without architectural discussion

  21. 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 the user before attempting more fixes.

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)

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
0. Context Recall Extract keywords, search prior knowledge Output recall summary
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

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