32 件 ・ 関連度順
概要と使いどころ
Property-based testing with fast-check (TypeScript/JavaScript) and Hypothesis (Python). Generate test cases automatically, find edge cases, and test mathematical properties. Use when user mentions property-based testing, fast-check, Hypothesis, generating test data, QuickCheck-style testing, or finding edge cases automatically.
日本語の概要は準備中です。原文の説明を表示しています。
Rustの単体・結合・非同期テストを、テストを先に書く流れで整えます。多様な入力の検証、依存先の置き換え、性能測定やカバレッジ確認も扱います。
Writes, reviews, and debugs property-based tests — Hypothesis, fast-check, proptest, jqwik, rapid, and Echidna or Medusa for Solidity invariants. Use whenever tests should cover a whole input domain instead of a hand-picked list of examples: encode/decode and serialize/deserialize pairs, parsers, canonicalizers and normalizers, validators, numeric and Decimal types, comparators and sort order, data structures, and smart-contract state invariants. Also use when adding cases to an existing @given, fast-check, or proptest suite, when judging whether existing property tests assert anything real, and when a generator has shrunk a counterexample and you need to tell a wrong property from a genuine bug. Not for coverage-guided binary fuzzing (libFuzzer, AFL), mutation-testing campaigns, static analysis, benchmarking, or end-to-end UI tests.
日本語の概要は準備中です。原文の説明を表示しています。
Property-based testing with Hypothesis for discovering edge cases and validating invariants. Use when implementing comprehensive test coverage, testing complex logic with many inputs, or validating mathematical properties and invariants across input domains. Triggered by: hypothesis, property-based testing, @given, strategies, generative testing.
日本語の概要は準備中です。原文の説明を表示しています。
Property-based testing strategies, mutation testing, shrinking, and combined PBT+mutation workflow for test quality validation
日本語の概要は準備中です。原文の説明を表示しています。
Property-based testing (PBT) patterns with fast-check (JS/TS), Hypothesis (Python), and gopter (Go). Generate random inputs, define invariants, shrink failures to minimal cases. Adapted from Trail of Bits. Use when testing pure functions, parsers, serializers, state machines, or any code where example-based tests miss edge cases.
日本語の概要は準備中です。原文の説明を表示しています。
Expert guide for property-based testing (fast-check, Hypothesis) and mutation testing (Stryker, mutmut) — AI-generated test properties, invariant discovery, mutation score optimization, and test suite quality verification / Panduan ahli property-based testing (fast-check, Hypothesis) dan mutation testing (Stryker, mutmut) — properti tes yang dihasilkan AI, penemuan invarian, optimasi skor mutasi, dan verifikasi kualitas suite tes.
日本語の概要は準備中です。原文の説明を表示しています。
Pytest testing patterns for Python — fixtures, behavioral naming, behavior/risk-driven coverage, property-based testing with Hypothesis when useful, and mutation testing when justified. Use when writing tests, designing fixtures, configuring coverage, or applying parametrize, async testing, or property-based strategies.
日本語の概要は準備中です。原文の説明を表示しています。
fast-check patterns for JS/TS — 6 canonical property categories with worked examples targeting agent-studio utilities (path normalization, safe-json, glob-to-regex, routing logic)
日本語の概要は準備中です。原文の説明を表示しています。
Guidelines and strategies for constructing meaningful test suites, property-based tests, metamorphic relations, and fuzzing harnesses. Trigger when: - Designing verification bounds, writing tests, creating test invariants, or implementing validation gates. - Prompt contains: testing, test design, property-based testing, PBT, metamorphic testing, fuzzing, integration tests, E2E.
日本語の概要は準備中です。原文の説明を表示しています。
Kotlinのテストを先に書き、KotestとMockKで動作や依存先を検証し、非同期処理のテストからKoverによる網羅率の確認まで進めるスキル。
F#の単体テストや結合テストを作成し、入力を自動生成する検証も取り入れるスキル。結果の確認方法、依存先の置き換え、テストの整理と実行を支援します。
Pre-deployment security audit of Solidity smart contracts in a Foundry project. Combines static analysis (Slither, Aderyn), symbolic execution (Mythril), and property-based testing (forge fuzz + invariant tests with handlers) to catch reentrancy, access-control, oracle/price manipulation, and arithmetic bugs BEFORE deploying to an EVM chain. Also enforces key hygiene (no plaintext private keys, encrypted cast keystore) and a secure deploy workflow. Use when writing, reviewing, testing, or deploying Solidity/Foundry contracts, building a dApp, or working with forge/cast/anvil, MetaMask, or Web3/DeFi code.
日本語の概要は準備中です。原文の説明を表示しています。
Pre-deployment security audit of Solidity smart contracts in a Foundry project. Combines static analysis (Slither, Aderyn), symbolic execution (Mythril), and property-based testing (forge fuzz + invariant tests with handlers) to catch reentrancy, access-control, oracle/price manipulation, and arithmetic bugs BEFORE deploying to an EVM chain. Also enforces key hygiene (no plaintext private keys, encrypted cast keystore) and a secure deploy workflow. Use when writing, reviewing, testing, or deploying Solidity/Foundry contracts, building a dApp, or working with forge/cast/anvil, MetaMask, or Web3/DeFi code.
日本語の概要は準備中です。原文の説明を表示しています。
Testing strategies including contract testing, snapshot testing, mutation testing, property-based testing, and test organization
日本語の概要は準備中です。原文の説明を表示しています。
Write and simplify C# property-based, model-based, and executable specification tests with CsCheck. Use for generators, shrinking, stateful command sequences, Spec guards and rules, implementation conformance, or replaying generated failures.
日本語の概要は準備中です。原文の説明を表示しています。
Port the state-delta + property-based testing paradigm to languages other than Python. DIY recipes per language; canonical Python ref shipped in nwave_ai.state_delta.
日本語の概要は準備中です。原文の説明を表示しています。
Strategic guidance for choosing and implementing testing approaches across the test pyramid. Use when building comprehensive test suites that balance unit, integration, E2E, and contract testing for optimal speed and confidence. Covers multi-language patterns (TypeScript, Python, Go, Rust) and modern best practices including property-based testing, test data management, and CI/CD integration.
日本語の概要は準備中です。原文の説明を表示しています。
Testing strategies, patterns, and tools for robotics software. Use this skill when writing unit tests, integration tests, simulation tests, or hardware-in-the-loop tests for robot systems. Trigger whenever the user mentions testing ROS nodes, pytest with ROS, launch_testing, simulation testing, CI/CD for robotics, test fixtures for sensors, mock hardware, deterministic replay, regression testing for robot behaviors, or validating perception/planning/control pipelines. Also covers property-based testing for kinematics, fuzz testing for message handlers, and golden-file testing for trajectories.
日本語の概要は準備中です。原文の説明を表示しています。
Generates automated test oracles to verify correct software behavior. Creates assertion-based oracles (expected values), property-based oracles (invariants), differential oracles (comparing implementations), and metamorphic oracles (input transformations). Use when you need to generate assertions for test cases, identify invariants that should always hold, compare new vs legacy implementations, create metamorphic test relationships, validate function correctness, or improve test coverage with better verification strategies. Supports Python (pytest, unittest, hypothesis) and Java (JUnit, property testing).
日本語の概要は準備中です。原文の説明を表示しています。
Explain why counterexamples violate specifications by analyzing formal specifications (temporal logic, invariants, pre/postconditions, code contracts), informal requirements (user stories, acceptance criteria), test specifications (assertions, property-based tests), and providing step-by-step traces showing state changes, comparing expected vs actual behavior, identifying root causes, and assessing violation impact. Use when debugging test failures, understanding model checker output, explaining runtime assertion violations, analyzing static analysis warnings, or teaching specification concepts. Produces structured markdown explanations with traces, comparisons, state diagrams, and cause chains. Triggers when users ask why something failed, explain a violation, understand a counterexample, debug a specification, or analyze why a test fails.
日本語の概要は準備中です。原文の説明を表示しています。
Think and work like an expert Formal Methods Researcher. Use when a task calls for Formal Methods Researcher judgment. Reasons from operational semantics and temporal logics through SPIN/TLA+/PRISM, Coq/Lean/Isabelle, Z3/CVC5, refinement and separation logic, vacuity and false-positive diagnosis, and Dafny/F* versus property-based testing boundaries.
日本語の概要は準備中です。原文の説明を表示しています。
Think and work like an expert Computer Scientist. Use when a task calls for Computer Scientist judgment. Reasons from computational models, abstraction contracts, invariants, and measurable complexity through CLRS-grade algorithm analysis, impossibility results (FLP, CAP, NP-hardness), property-based and chaos testing, and formal tools (TLA+, Coq, Z3) while treating partial failure, race conditions, label leakage, and abstraction leaks like GC pauses and clock skew as first-class failure modes.
日本語の概要は準備中です。原文の説明を表示しています。
Reviews Rust test code for unit test patterns, integration test structure, async testing, mocking approaches, and property-based testing. Covers Rust 2024 edition changes including async fn in traits for mocks,
日本語の概要は準備中です。原文の説明を表示しています。