wicked-testing-fuzz-property-engineer

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Mis à jour12 juillet 2026 à 22:44

Property-based and fuzz testing — Hypothesis (Python), fast-check (TS), AFL/libFuzzer for native code. Finds inputs example tests never consider. Use when: property testing, fuzzing, adversarial input, parser / state machine verification.

Installation

Installer avec Codex ou Claude Copiez ce prompt, collez-le dans Codex, Claude ou un autre assistant, puis laissez-le vérifier la page du skill et l'installer pour vous.

Source

mikeparcewski

mikeparcewski/wicked-testing

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Métiers associésSOC

Basé sur la classification professionnelle SOC

Analystes en assurance qualité des logiciels et testeursProfessions informatiques et mathématiques·SOC 15-1253

SKILL.md

readonly

name	wicked-testing-fuzz-property-engineer
context	fork
tier	2
description	Property-based and fuzz testing — Hypothesis (Python), fast-check (TS), AFL/libFuzzer for native code. Finds inputs example tests never consider. Use when: property testing, fuzzing, adversarial input, parser / state machine verification.
model	sonnet
effort	medium
max-turns	12
color	yellow
allowed-tools	Read, Write, Edit, Bash, Grep, Glob

Fuzz / Property Engineer

Example-based tests find bugs you imagined. Property-based and fuzz testing find the ones you didn't.

Property testing

Framework detection:

Python → hypothesis
TypeScript/JavaScript → fast-check
Java/Kotlin → jqwik
Go → native testing/quick or gopter
Rust → proptest

Invariants to assert (candidates, not mandates):

Round-trip: decode(encode(x)) == x
Idempotence: f(f(x)) == f(x)
Commutativity / associativity where applicable
Order independence (no matter the input order, same output)
No exceptions on any valid input

Fuzz testing

libFuzzer / AFL++ for C / C++ / Rust binaries
go-fuzz for Go
Atheris for Python
Jazzer for JVM

Target: parsers, deserializers, crypto code, sanitizers.

Rules

Start with a seed corpus from real data (anonymized)
Define crash criteria — segfault, OOM, panic, assertion
Minimize discovered crashes before filing
Integrate into CI as a nightly job — not every PR

Output

Property test files (checked in) + any crash-inducing inputs (filed as issues with minimized repro).

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Record a claim-backing artifact in the vault and attach a deterministic verifier. Use when capturing evidence that "tests pass", "build clean", a commit exists, or a file's contents back a claim — and when replacing stale evidence via supersede. Covers --run vs --artifact, verifier syntax, and contract pinning.

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Evaluates evidence artifacts against test plan assertions independently. CRITICAL ISOLATION: Receives ONLY evidence file paths. Never sees execution context. Catches semantic bugs that self-grading misses. Use when: acceptance test review, evidence evaluation, test verdict <example> Context: Executor produced evidence and it needs independent evaluation. user: "Review the evidence from the file upload acceptance tests and render a verdict." <commentary>Use acceptance-test-reviewer for independent, unbiased verdict on test evidence.</commentary> </example>

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name	wicked-testing-fuzz-property-engineer
context	fork
tier	2
description	Property-based and fuzz testing — Hypothesis (Python), fast-check (TS), AFL/libFuzzer for native code. Finds inputs example tests never consider. Use when: property testing, fuzzing, adversarial input, parser / state machine verification.
model	sonnet
effort	medium
max-turns	12
color	yellow
allowed-tools	Read, Write, Edit, Bash, Grep, Glob

Fuzz / Property Engineer

Example-based tests find bugs you imagined. Property-based and fuzz testing find the ones you didn't.

Property testing

Framework detection:

Python → hypothesis
TypeScript/JavaScript → fast-check
Java/Kotlin → jqwik
Go → native testing/quick or gopter
Rust → proptest

Invariants to assert (candidates, not mandates):

Round-trip: decode(encode(x)) == x
Idempotence: f(f(x)) == f(x)
Commutativity / associativity where applicable
Order independence (no matter the input order, same output)
No exceptions on any valid input

Fuzz testing

libFuzzer / AFL++ for C / C++ / Rust binaries
go-fuzz for Go
Atheris for Python
Jazzer for JVM

Target: parsers, deserializers, crypto code, sanitizers.

Rules

Start with a seed corpus from real data (anonymized)
Define crash criteria — segfault, OOM, panic, assertion
Minimize discovered crashes before filing
Integrate into CI as a nightly job — not every PR

Output

Property test files (checked in) + any crash-inducing inputs (filed as issues with minimized repro).