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🎯 Exercise Script: Code Quality

Step-by-Step Guide for Students

📝 Instructions: Execute each command in order, one by one. Wait for each command to complete before running the next one.

📋 PHASE 1: SETUP

Step 1: Verify Installation

make help

Step 2: Install Dependencies

make install

Step 3: Check Project Structure

ls -la

🔍 PHASE 2: INITIAL ANALYSIS

Step 4: Record Initial Benchmark

make benchmark-initial

Step 5: See Generated Files

ls -la *report*.txt issues_to_fix*.txt benchmark_results.json

Step 6: View Fixable Issues (MOST IMPORTANT)

cat issues_to_fix_*.txt

Step 7: View Benchmark Data

python tools/benchmark_code_quality.py --report

⚡ PHASE 3: AUTO-FIXER

Step 8: Fix All Issues Automatically

make fix

Step 9: See What Files Were Modified

git status

Step 10: Verify Code Still Works

make test

📊 PHASE 4: COMPARISON

Step 11: Record Post-Fix Benchmark

make benchmark-post-autofix

Step 12: Compare Results

make benchmark-compare

Step 13: Generate Detailed Report

make benchmark-report

🤖 PHASE 5: AI AGENT

Step 14: See Remaining Errors

cat issues_to_fix_*.txt

Step 15: Use AI Agent

💬 Copy and paste this prompt in your AI agent:

Analyze the files in this project and fix the remaining code quality issues 
that automated tools cannot fix. Focus on:
1. Type errors (MyPy issues)
2. Logic improvements
3. Performance optimizations
4. Code structure improvements

Explain each change you make and why it improves the code.

Step 16: Test After AI Changes

make test

📈 PHASE 6: FINAL ANALYSIS

Step 17: Record Final Benchmark

make benchmark-post-ai

Step 18: Final Comparison

make benchmark-compare

Step 19: Final Report

make benchmark-report

Step 20: Reflection

🤔 Answer these questions:

  1. What percentage of errors were fixed automatically?

    • Answer: ___ (check benchmark report)

  2. What types of errors were most difficult to fix?

    • Answer: ___

  3. Which tool did you find most useful?

    • Answer: ___

  4. How would you change your development process after this?

    • Answer: ___

🆘 TROUBLESHOOTING

If a command fails:

# Check if dependencies are installed
pip list | grep -E "(black|ruff|mypy|bandit)"

# Reinstall if needed
make install

If tests fail:

# See specific errors
make test-verbose

# Verify code works
python main.py

If you get confused:

  • Go back to the previous step and make sure it completed successfully
  • Check the output of each command for error messages
  • Ask for help if you're stuck

🏆 SUCCESS CRITERIA

✅ Exercise Completed Successfully if:

  • Reduced at least 70% of initial errors
  • Understand what each tool does
  • Can explain the difference between auto-fixer and AI
  • Applied at least 3 changes suggested by AI
  • Code still works after all changes

🎯 Learning Objectives Achieved:

  • Know code quality tools
  • Can automate repetitive tasks
  • Know when to use AI vs automated tools
  • Have a workflow to improve code

Congratulations on completing the exercise! 🎉

Remember: Code quality is a continuous process, not a destination.