property-based-testing

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4.9k4302 months ago

Provides guidance for property-based testing across multiple languages and smart contracts. Use when writing tests, reviewing code with serialization/validation/parsing patterns, designing features, or when property-based testing would provide stronger coverage than example-based tests.

Quick Install

npxskills add trailofbits/skills--skill property-based-testing

Instructions

Property-Based Testing Guide

Use this skill proactively during development when you encounter patterns where PBT provides stronger coverage than example-based tests.

When to Invoke (Automatic Detection)

Invoke this skill when you detect:

Serialization pairs: encode/decode, serialize/deserialize, toJSON/fromJSON, pack/unpack
Parsers: URL parsing, config parsing, protocol parsing, string-to-structured-data
Normalization: normalize, sanitize, clean, canonicalize, format
Validators: is_valid, validate, check_* (especially with normalizers)
Data structures: Custom collections with add/remove/get operations
Mathematical/algorithmic: Pure functions, sorting, ordering, comparators
Smart contracts: Solidity/Vyper contracts, token operations, state invariants, access control

Priority by pattern:

Pattern	Property	Priority
encode/decode pair	Roundtrip	HIGH
Pure function	Multiple	HIGH
Validator	Valid after normalize	MEDIUM
Sorting/ordering	Idempotence + ordering	MEDIUM
Normalization	Idempotence	MEDIUM
Builder/factory	Output invariants	LOW
Smart contract	State invariants	HIGH

When NOT to Use

Do NOT use this skill for:

Simple CRUD operations without transformation logic
One-off scripts or throwaway code
Code with side effects that cannot be isolated (network calls, database writes)
Tests where specific example cases are sufficient and edge cases are well-understood
Integration or end-to-end testing (PBT is best for unit/component testing)

Property Catalog (Quick Reference)

Property	Formula	When to Use
Roundtrip	`decode(encode(x)) == x`	Serialization, conversion pairs
Idempotence	`f(f(x)) == f(x)`	Normalization, formatting, sorting
Invariant	Property holds before/after	Any transformation
Commutativity	`f(a, b) == f(b, a)`	Binary/set operations
Associativity	`f(f(a,b), c) == f(a, f(b,c))`	Combining operations
Identity

Strength hierarchy (weakest to strongest): No Exception → Type Preservation → Invariant → Idempotence → Roundtrip

Decision Tree

Based on the current task, read the appropriate section:

TASK: Writing new tests
  → Read [{baseDir}/references/generating.md]({baseDir}/references/generating.md) (test generation patterns and examples)
  → Then [{baseDir}/references/strategies.md]({baseDir}/references/strategies.md) if input generation is complex

TASK: Designing a new feature
  → Read [{baseDir}/references/design.md]({baseDir}/references/design.md) (Property-Driven Development approach)

TASK: Code is difficult to test (mixed I/O, missing inverses)
  → Read [{baseDir}/references/refactoring.md]({baseDir}/references/refactoring.md) (refactoring patterns for testability)

TASK: Reviewing existing PBT tests
  → Read [{baseDir}/references/reviewing.md]({baseDir}/references/reviewing.md) (quality checklist and anti-patterns)

TASK: Test failed, need to interpret
  → Read [{baseDir}/references/interpreting-failures.md]({baseDir}/references/interpreting-failures.md) (failure analysis and bug classification)

TASK: Need library reference
  → Read [{baseDir}/references/libraries.md]({baseDir}/references/libraries.md) (PBT libraries by language, includes smart contract tools)

How to Suggest PBT

When you detect a high-value pattern while writing tests, offer PBT as an option:

"I notice encode_message/decode_message is a serialization pair. Property-based testing with a roundtrip property would provide stronger coverage than example tests. Want me to use that approach?"

If codebase already uses a PBT library (Hypothesis, fast-check, proptest, Echidna), be more direct:

"This codebase uses Hypothesis. I'll write property-based tests for this serialization pair using a roundtrip property."

If user declines, write good example-based tests without further prompting.

When NOT to Use PBT

Simple CRUD without complex validation
UI/presentation logic
Integration tests requiring complex external setup
Prototyping where requirements are fluid
User explicitly requests example-based tests only

Red Flags

Recommending trivial getters/setters
Missing paired operations (encode without decode)
Ignoring type hints (well-typed = easier to test)
Overwhelming user with candidates (limit to top 5-10)
Being pushy after user declines

Rationalizations to Reject

Do not accept these shortcuts:

"Example tests are good enough" - If serialization/parsing/normalization is involved, PBT finds edge cases examples miss
"The function is simple" - Simple functions with complex input domains (strings, floats, nested structures) benefit most from PBT
"We don't have time" - PBT tests are often shorter than comprehensive example suites
"It's too hard to write generators" - Most PBT libraries have excellent built-in strategies; custom generators are rarely needed
"The test failed, so it's a bug" - Failures require validation; see interpreting-failures.md
"No crash means it works" - "No exception" is the weakest property; always push for stronger guarantees

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