Property-Based Testing and Mutation Testing

Deferred to Phase 2.25: Mutation testing runs ONCE per feature as final quality gate at orchestrator Phase 2.25 (after all steps complete). Do NOT run mutation testing during inner TDD loop.

Property-Based Testing (PBT)

Instead of examples ("given X, expect Y"), write properties ("for all valid inputs, condition Z holds"). Framework generates hundreds/thousands of inputs checking property. Dramatically expands test coverage.

Property Patterns

1. Invariants: "for all inputs, condition holds" (sorted list is ordered, balance >= 0)
2. Roundtrip: "encode then decode = original" (serialize/deserialize, compress/decompress)
3. Oracle: "compare against reference implementation" (optimized vs correct-but-slow)
4. Metamorphic: "different operations, same result" (add(a,b)==add(b,a), filter can't increase size)

Shrinking

When property fails, framework auto-finds minimal failing input. Dramatically accelerates debugging. Algorithm: find failing input -> try simpler variants -> if still fails, use as new candidate -> repeat.

PBT Tools by Language

Language	Framework
Python	Hypothesis
JavaScript/TypeScript	fast-check
Haskell	QuickCheck
Rust	quickcheck
Java	jqwik
C#	FsCheck

Adopted by Amazon, Volvo, Stripe, Jane Street (ICSE 2024 study).

When PBT Adds Value

HIGH value: algorithms | data structures | serialization | business rules (validation, calculations) | protocols/state machines. LOW value: simple CRUD | UI logic | external API integrations. PBT complements example-based testing, doesn't replace it.

PBT + TDD Integration

1. Start with example-based TDD for specific cases (drives detailed design)
2. Once basic implementation works, write properties to generalize
3. If property fails: found bug or need refined implementation
4. Refactor freely - properties verify behavior preservation

Properties = higher-level spec that survives refactoring better than examples.

Mutation Testing

Evaluates test suite quality by introducing artificial bugs (mutations) and checking if tests catch them. Mutation score = killed mutants / total mutants. Stronger metric than code coverage.

Mutation Score Targets

Score	Quality
< 60%	Weak suite, significant gaps
60-80%	Moderate, some gaps
> 80%	Strong, few gaps

Target: 75-80% minimum. Not all survivors indicate bad tests (equivalent mutants exist).

Mutation Operators

Change == to != | + to - | remove method call | change constant | modify loop boundary | alter comparison.

Mutation Testing Tools

Language	Tool
Java	PIT
JavaScript/TypeScript/C#	Stryker
Python	mutmut, Cosmic Ray

Computationally expensive. Use incremental: on changed code in PRs, full codebase weekly.

Combined PBT + Mutation Workflow

1. Write example-based tests (TDD) -> cover known scenarios
2. Apply mutation testing -> identify assertion gaps -> write more tests
3. Add PBT for complex logic -> cover input space systematically
4. Mutation testing again -> verify properties are comprehensive

Quality ratchet: each technique exposes gaps others miss. Prioritize critical paths and complex algorithms.

PBT Performance Guidance

• Fast feedback: ~100 examples | CI/CD: ~1000 examples | Nightly builds: ~10000+ examples

Modern frameworks allow configuring example count per context.