systematic-debugging（系统调试）

Systematic Debugging

Overview

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

Core principle: Root cause investigation must precede any fix attempt. Symptom fixes represent process failure.

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

The Iron Law

NO FIXES WITHOUT ROOT CAUSE INVESTIGATION FIRST

Fixes cannot be proposed without completing Phase 1.

When to Apply

Systematic debugging applies to ANY technical issue:

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

Especially valuable when:

• Time pressure creates temptation to guess
• "Quick fix" seems obvious
• Multiple fixes have already been attempted
• Previous fixes failed
• Issue is not fully understood

Process should not be skipped even when:

• Issue appears simple (simple bugs have root causes too)
• Time is tight (systematic approach is faster than thrashing)
• Urgency exists (investigation is faster than rework)

The Four Phases

Each phase must be completed before proceeding to the next.

Phase 1: Root Cause Investigation

Before attempting any fix:

1. Read Error Messages Carefully

- Error messages and warnings often contain solutions - Read stack traces completely - Note line numbers, file paths, error codes

1. Reproduce Consistently

- Determine if the issue triggers reliably - Identify exact steps - Confirm reproducibility - If not reproducible, gather more data instead of guessing

1. Check Recent Changes

- Git diff and recent commits - New dependencies, config changes - Environmental differences

1. Gather Evidence in Multi-Component Systems For systems with multiple components (CI -> build -> signing, API -> service -> database): Diagnostic instrumentation should be added before proposing fixes: 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 Multi-layer system example: # 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.
2. Trace Data Flow When error is deep in call stack: See ./references/root-cause-tracing.md for the complete backward tracing technique. Quick approach:

- Identify where bad value originates - Determine what called this with bad value - Continue tracing up until source is found - Fix at source, not at symptom

Phase 2: Pattern Analysis

Pattern identification should precede any fix:

1. Find Working Examples

- Locate similar working code in same codebase - Identify working code similar to what's broken

1. Compare Against References

- If implementing a pattern, read reference implementation completely - Read every line, do not skim - Understand pattern fully before applying

1. Identify Differences

- List every difference between working and broken code - Do not dismiss small differences as irrelevant

1. Understand Dependencies

- Other components required by this operation - Settings, config, environment needed - Assumptions made by the pattern

Phase 3: Hypothesis and Testing

Scientific method application:

1. Form Single Hypothesis

- State clearly: "X is the root cause because Y" - Be specific, not vague

1. Test Minimally

- Make smallest possible change to test hypothesis - One variable at a time - Do not fix multiple things simultaneously

1. Verify Before Continuing

- If hypothesis confirmed: proceed to Phase 4 - If not confirmed: form new hypothesis - Do not add more fixes on top

1. When Understanding is Missing

- Acknowledge lack of understanding - 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 - Test must exist before fixing

1. Implement Single Fix

- Address the identified root cause - One change at a time - No "while I'm here" improvements - No bundled refactoring

1. Verify Fix

- Test now passes? - No other tests broken? - Issue actually resolved?

1. If Fix Doesn't Work

- Stop - Count attempted fixes - If < 3: Return to Phase 1, re-analyze with new information - If >= 3: Question architecture

1. Architecture Questioning After 3+ Failed Fixes Patterns indicating architectural problem: Stop and question fundamentals: Discuss with human partner before attempting more fixes This is not a failed hypothesis - this is wrong architecture.

- Each fix reveals new shared state/coupling/problem in different place - Fixes require "massive refactoring" - Each fix creates new symptoms elsewhere - Is pattern fundamentally sound? - Is approach continuing through inertia? - Should architecture be refactored vs. fixing symptoms?

Complex Bugs and Planning

For complex bugs, planning must precede any code changes:

When Bug is Complex

A bug requires EnterPlanMode before making changes when ANY of these apply:

• Multi-component involvement - Issue spans multiple files, modules, or subsystems
• Architecture implications - Fix may affect system design, contracts, or interfaces
• Multiple potential approaches - Several valid implementation paths exist
• Side-effect risk - Change could impact unrelated functionality
• Requires refactoring - Fix needs structural changes beyond minimal patch
• Not fully understood - After Phase 1 investigation, root cause is still unclear

Planning Process

1. Complete Phase 1 (Root Cause Investigation)

- Must understand WHAT is broken and WHY before planning - Gather all evidence first

1. Use EnterPlanMode

- This signals to user you need approval before proceeding - Allows user to review approach before implementation

1. Write implementation plan covering:

- Root cause summary (from Phase 1) - Proposed fix strategy - Files that will be modified - Tests to be created/modified - Potential risks and mitigation - Alternative approaches considered

1. Wait for user approval

- User may suggest different approach - User may provide additional context - User may approve as-is

Why Planning for Complex Bugs

• Prevents expensive rework from wrong architectural choices
• Ensures alignment with user preferences and constraints
• Catches overlooked dependencies early
• Provides visibility into proposed changes before execution

For simple bugs: Continue with Phase 2-4 directly without planning.

Red Flags

These mental patterns indicate process violation and require returning to Phase 1:

• "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"
• Proposing solutions before tracing data flow
• "One more fix attempt" (when already tried 2+)
• Each fix reveals new problem in different place

If 3+ fixes failed: Question the architecture.

Human Partner Signals

Watch for these redirections:

• "Is that not happening?" - Indicates assumption without verification
• "Will it show us...?" - Indicates missing evidence gathering
• "Stop guessing" - Indicates proposing fixes without understanding
• "Ultrathink this" - Indicates need to question fundamentals, not just symptoms
• "We're stuck?" (frustrated) - Indicates current approach isn't working

When encountering these signals: Return to Phase 1.

Common Rationalizations

Quick Reference

When Process Reveals No Root Cause

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

1. Process has been completed
2. Document what was investigated
3. Implement appropriate handling (retry, timeout, error message)
4. Add monitoring/logging for future investigation

Note: 95% of "no root cause" cases represent incomplete investigation.

Supporting Techniques

These techniques are part of systematic debugging:

• ./references/root-cause-tracing.md - Trace bugs backward through call stack to find original trigger
• ./references/defense-in-depth.md - Add validation at multiple layers after finding root cause
• ./references/condition-based-waiting.md - Replace arbitrary timeouts with condition polling
• ./references/condition-based-waiting-example.ts - Example implementation of condition-based waiting
• ./find-polluter.sh - Bisect test suite to identify which test pollutes shared state

Related skills:

• superpowers:behavior-driven-development - BDD principles including Gherkin scenarios for test design

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