32 个 · 按相关度排序
Writes, reviews, and debugs property-based tests, which generate inputs to check general rules. Helps test conversions, parsers, normalization, and state invariants, assess whether existing assertions are meaningful, and distinguish faulty rules from implementation bugs.
中文简介正在准备中。当前显示英语简介。
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.
中文简介正在准备中。当前显示原文说明。
按照先写测试的流程编写Rust单元、集成和异步测试，涵盖生成多样输入、替换依赖、性能基准测试与覆盖率检查，用于验证行为并补充未测试部分。
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.
中文简介正在准备中。当前显示原文说明。
Property-based testing strategies, mutation testing, shrinking, and combined PBT+mutation workflow for test quality validation
中文简介正在准备中。当前显示原文说明。
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.
中文简介正在准备中。当前显示原文说明。
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.
中文简介正在准备中。当前显示原文说明。
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.
中文简介正在准备中。当前显示原文说明。
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)
中文简介正在准备中。当前显示原文说明。
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.
中文简介正在准备中。当前显示原文说明。
为Kotlin代码先编写测试，使用Kotest和MockK验证行为与依赖交互，涵盖异步测试、生成输入的属性测试及Kover覆盖率检查。
帮助编写和组织F#单元测试、异步测试与集成测试，使用自动生成的输入验证性质，替换依赖，并检查测试结果、质量及覆盖情况。
Audit Solidity contracts in Foundry projects before deployment using code analysis, randomized tests, manual review, and private key checks. Produces a JSON report with findings, remediation, test coverage, and a pass or fail deployment decision.
中文简介正在准备中。当前显示英语简介。
Audit Solidity contracts in Foundry projects before deployment using code analysis, randomized tests, manual review, and private key checks. Produces a JSON report with findings, remediation, test coverage, and a pass or fail deployment decision.
中文简介正在准备中。当前显示英语简介。
Testing strategies including contract testing, snapshot testing, mutation testing, property-based testing, and test organization
中文简介正在准备中。当前显示原文说明。
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.
中文简介正在准备中。当前显示原文说明。
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.
中文简介正在准备中。当前显示原文说明。
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.
中文简介正在准备中。当前显示原文说明。
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.
中文简介正在准备中。当前显示原文说明。
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).
中文简介正在准备中。当前显示原文说明。
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.
中文简介正在准备中。当前显示原文说明。
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.
中文简介正在准备中。当前显示原文说明。
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.
中文简介正在准备中。当前显示原文说明。
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,
中文简介正在准备中。当前显示原文说明。