property-based-testing

name	property-based-testing
description	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. For Go code, uses pgregory.net/rapid as the primary PBT framework.

Property-Based Testing Guide

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

Go / rapid (Primary for Go Code)

For Go code, always use pgregory.net/rapid as the property-based testing library. Do NOT use testing/quick -- it is limited, lacks proper shrinking, and has poor generator support.

Why rapid over testing/quick

• Automatic shrinking of failing cases to minimal counterexamples.
• Rich generator combinators: IntRange, SliceOf, Map, Custom, OneOf, Ptr, SampledFrom.
• Stateful testing via rapid.StateMachine for testing stateful systems.
• Integrates with standard *testing.T via rapid.Check.
• Actively maintained with good documentation.

rapid Core Pattern

func TestRoundtrip(t *testing.T) {
    rapid.Check(t, func(t *rapid.T) {
        msg := genMessage().Draw(t, "msg")
        encoded := Encode(msg)
        decoded, err := Decode(encoded)
        if err != nil {
            t.Fatal(err)
        }
        if !reflect.DeepEqual(msg, decoded) {
            t.Fatalf("roundtrip failed: got %v, want %v", decoded, msg)
        }
    })
}

rapid Generators

Generator	Description	Example
rapid.Int()	Any int	rapid.Int().Draw(t, "n")
rapid.IntRange(lo, hi)	Bounded int	rapid.IntRange(0, 100).Draw(t, "n")
rapid.Int64()	Any int64	rapid.Int64().Draw(t, "n")
rapid.Uint64()	Any uint64	rapid.Uint64().Draw(t, "n")
rapid.Float64()	Any float64	rapid.Float64().Draw(t, "f")
rapid.Bool()	true or false	rapid.Bool().Draw(t, "b")
rapid.String()	Any string	rapid.String().Draw(t, "s")
rapid.StringN(minLen, maxLen, maxRunes)	Bounded string	rapid.StringN(1, 50, -1).Draw(t, "s")
rapid.Byte()	Single byte	rapid.Byte().Draw(t, "b")
rapid.SliceOf(gen)	Slice of elements	rapid.SliceOf(rapid.Int()).Draw(t, "xs")
rapid.SliceOfN(gen, min, max)	Bounded slice	rapid.SliceOfN(rapid.Int(), 1, 10).Draw(t, "xs")
rapid.MapOf(keyGen, valGen)	Map	rapid.MapOf(rapid.String(), rapid.Int()).Draw(t, "m")
rapid.SampledFrom(slice)	One of values	rapid.SampledFrom([]string{"a","b"}).Draw(t, "s")
rapid.OneOf(gens...)	One of generators	rapid.OneOf(rapid.Int(), rapid.Int()).Draw(t, "n")
rapid.Just(val)	Constant value	rapid.Just(42).Draw(t, "n")

Custom Generators

func genMessage() *rapid.Generator[Message] {
    return rapid.Custom(func(t *rapid.T) Message {
        return Message{
            ID:       rapid.IntRange(1, 10000).Draw(t, "id"),
            Content:  rapid.StringN(0, 1000, -1).Draw(t, "content"),
            Priority: rapid.IntRange(1, 10).Draw(t, "priority"),
            Tags:     rapid.SliceOfN(rapid.StringN(1, 50, -1), 0, 20).Draw(t, "tags"),
        }
    })
}

Stateful Testing with rapid.StateMachine

For testing stateful systems (data structures, databases, protocol state machines):

type queueMachine struct {
    queue Queue           // System under test.
    model []int           // Reference model.
}

func (m *queueMachine) Init(t *rapid.T) {
    m.queue = NewQueue()
    m.model = nil
}

func (m *queueMachine) Push(t *rapid.T) {
    v := rapid.Int().Draw(t, "v")
    m.queue.Push(v)
    m.model = append(m.model, v)
}

func (m *queueMachine) Pop(t *rapid.T) {
    if len(m.model) == 0 {
        t.Skip("empty queue")
    }
    got := m.queue.Pop()
    want := m.model[0]
    m.model = m.model[1:]
    if got != want {
        t.Fatalf("got %d, want %d", got, want)
    }
}

func (m *queueMachine) Check(t *rapid.T) {
    if m.queue.Len() != len(m.model) {
        t.Fatalf("length mismatch: got %d, want %d", m.queue.Len(), len(m.model))
    }
}

func TestQueue(t *testing.T) {
    rapid.Check(t, rapid.Run[*queueMachine]())
}

Go Property Test Patterns

Roundtrip (encode/decode):

func TestCodecRoundtrip(t *testing.T) {
    rapid.Check(t, func(t *rapid.T) {
        original := genMessage().Draw(t, "msg")
        encoded, err := Encode(original)
        if err != nil {
            t.Fatal(err)
        }
        decoded, err := Decode(encoded)
        if err != nil {
            t.Fatal(err)
        }
        if !reflect.DeepEqual(original, decoded) {
            t.Fatalf("roundtrip failed: %v != %v", original, decoded)
        }
    })
}

Idempotence (normalization):

func TestNormalizeIdempotent(t *testing.T) {
    rapid.Check(t, func(t *rapid.T) {
        s := rapid.String().Draw(t, "s")
        once := Normalize(s)
        twice := Normalize(once)
        if once != twice {
            t.Fatalf("not idempotent: Normalize(%q) = %q, Normalize(%q) = %q",
                s, once, once, twice)
        }
    })
}

Sorting properties:

func TestSort(t *testing.T) {
    rapid.Check(t, func(t *rapid.T) {
        xs := rapid.SliceOf(rapid.Int()).Draw(t, "xs")
        result := MySort(xs)

        // Length preserved.
        if len(result) != len(xs) {
            t.Fatalf("length changed: %d -> %d", len(xs), len(result))
        }

        // Ordered.
        for i := 1; i < len(result); i++ {
            if result[i-1] > result[i] {
                t.Fatalf("not sorted at index %d: %d > %d", i, result[i-1], result[i])
            }
        }

        // Idempotent.
        result2 := MySort(result)
        if !reflect.DeepEqual(result, result2) {
            t.Fatal("sort not idempotent")
        }
    })
}

Oracle (reference implementation):

func TestOptimizedMatchesReference(t *testing.T) {
    rapid.Check(t, func(t *rapid.T) {
        input := rapid.SliceOf(rapid.Int()).Draw(t, "input")
        got := OptimizedImpl(input)
        want := ReferenceImpl(input)
        if !reflect.DeepEqual(got, want) {
            t.Fatalf("mismatch: optimized=%v, reference=%v", got, want)
        }
    })
}

When to Invoke (Automatic Detection)

Invoke this skill when you detect:

• Serialization pairs: encode/decode, serialize/deserialize, toJSON/fromJSON, pack/unpack, Marshal/Unmarshal
• 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
• State machines: Protocol state, connection lifecycle, workflow transitions (use rapid.StateMachine)

Priority by pattern:

Pattern	Property	Priority
encode/decode pair	Roundtrip	HIGH
Pure function	Multiple	HIGH
State machine	Invariants via StateMachine	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	f(x, identity) == x	Operations with neutral element
Inverse	f(g(x)) == x	encrypt/decrypt, compress/decompress
Oracle	new_impl(x) == reference(x)	Optimization, refactoring
Easy to Verify	is_sorted(sort(x))	Complex algorithms
No Exception	No crash on valid input	Baseline property

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/Decode is a serialization pair. Property-based testing with a roundtrip property using rapid.Check would provide stronger coverage than example tests. Want me to use that approach?"

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

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

If Go codebase uses testing/quick, suggest migration:

"I see this codebase uses testing/quick. The rapid library (pgregory.net/rapid) provides better shrinking, richer generators, and stateful testing support. Want me to use rapid for the new tests?"

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" - rapid has excellent built-in generators and rapid.Custom makes custom ones trivial
• "The test failed, so it's a bug" - Failures require validation; see {baseDir}/references/interpreting-failures.md
• "No crash means it works" - "No exception" is the weakest property; always push for stronger guarantees
• "testing/quick is good enough" - It lacks proper shrinking, has limited generators, and is effectively unmaintained; use rapid instead