test-guided-debloating

Test-Guided Debloating

Remove unnecessary code from a repository while preserving exactly the behavior exercised by a given test suite.

Workflow

1. Understand Requirements

Inputs needed:

• Target repository path
• Test command to run the test suite
• Programming language/framework

Clarify scope:

• Which tests define required behavior (all tests, specific test files, integration tests only)?
• Should test files themselves be preserved (yes, never modify tests)?
• Are there any files that must be kept regardless of coverage (configuration, documentation)?

2. Run Coverage Analysis

Generate test coverage data to identify exercised code. See [coverage_tools.md](references/coverage_tools.md) for language-specific commands.

Python example:

pytest --cov=. --cov-report=json --cov-report=html

JavaScript example:

npm test -- --coverage --coverageReporters=json --coverageReporters=html

Java example:

mvn clean test jacoco:report

Verify:

• Coverage report generated successfully
• All tests pass
• Coverage data includes all source files

3. Analyze Coverage Data

Use scripts/analyze_coverage.py to identify removal candidates:

python scripts/analyze_coverage.py coverage.json --output analysis.json

The script identifies:

• Uncovered files (0% coverage) - safest to remove
• Partially covered files - require manual review
• Uncovered lines - potential dead code within files

Manual review checklist:

• Are uncovered files truly unused (check imports)?
• Do uncovered functions have side effects?
• Are there dynamic imports or reflection?
• Is this a library with public API requirements?

4. Incremental Removal

Remove code incrementally, validating after each step. See [debloating_strategy.md](references/debloating_strategy.md) for detailed strategy.

Removal order (safest to riskiest):

1. Unused imports

``python # Remove unused import statements # Run tests after removal ``

1. Uncovered files (0% coverage, not imported)

``bash # Remove file rm path/to/unused_file.py # Run tests pytest ``

1. Uncovered functions/methods

``python # Remove function definition # Run tests ``

1. Dead branches

```python # Before: if condition that's always true if always_true_condition: do_something() else: never_executed() # Remove this branch

# After: do_something() ```

1. Unused classes

``python # Remove class definition if never instantiated # Run tests ``

After each removal:

# Run full test suite
<test_command>

# Verify all tests pass
# Check for import errors
# Verify build succeeds

5. Validate Preservation of Behavior

Final validation:

• [ ] All tests pass
• [ ] Build succeeds without errors
• [ ] No import/module errors
• [ ] No runtime errors during test execution
• [ ] Test coverage of remaining code unchanged
• [ ] No modifications to test files

Run tests multiple times to catch flaky tests or timing issues.

6. Document Changes

Generate removal report:

DEBLOATING SUMMARY
==================

Removed Elements:
- 15 unused files
- 42 unused functions
- 8 unused classes
- 156 unused imports
- 23 dead branches

Total lines removed: 3,847
Tests passing: 156/156

Preservation Justification:
All test-defined behavior is preserved because:
1. All test-covered code remains intact
2. All transitive dependencies of test-covered code remain
3. No side effects required by tests were removed
4. Build succeeds and all 156 tests pass

Key Principles

Test-Defined Behavior: The test suite is the single source of truth for required functionality.

Conservative Removal: When in doubt, keep the code. Only remove code you're confident is unused.

Incremental Validation: Remove code in small batches and run tests after each change.

Never Modify Tests: Test files define the required behavior and must not be changed.

Preserve Side Effects: Be cautious with code that has side effects (logging, initialization, registration).

Common Pitfalls

Avoid removing:

• Code with side effects (module-level initialization, decorators, metaclasses)
• Code used via reflection or dynamic imports
• Public API methods (if building a library)
• Configuration files
• Error handling needed in production (even if untested)

Watch for:

• Dynamic behavior (eval, exec, importlib, reflection)
• Transitive dependencies (code called by covered code)
• Module-level code execution
• Static initializers
• Decorator/annotation side effects

Helper Script

The analyze_coverage.py script automates coverage analysis:

# Analyze Python coverage
python scripts/analyze_coverage.py coverage.json

# Analyze JavaScript coverage
python scripts/analyze_coverage.py coverage-final.json --format javascript

# Save detailed analysis
python scripts/analyze_coverage.py coverage.json --output analysis.json

Output includes:

• List of uncovered files (safe to remove)
• Partially covered files (review needed)
• Uncovered line ranges
• Safety ratings for removal candidates