「mutation-testing」の検索結果

Use when evaluating test quality on modules containing business logic, calculation utilities, or state machines to determine whether the tests provide genuine defect detection.

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Configures mewt or muton campaigns, analyzes surviving mutants, and investigates bugs exposed by testing gaps. Use when setting up mutation testing, reviewing campaign results, identifying equivalent mutants, or finding bugs from surviving mutations.

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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.

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EXPERIMENTAL — mutation testing with muter to measure whether tests actually assert anything: mutants that survive reveal assertion-free coverage. Advisory report only, never a merge gate. Use on engine/logic targets when coverage numbers look good but bugs still slip through.

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Mutation testing ile test suite kalitesini olc. Stryker, mutmut, go-mutesting destegi.

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Validate test effectiveness with mutation testing using Stryker (TypeScript/JavaScript with Vitest or bun test via @hughescr/stryker-bun-runner) and mutmut (Python). Find weak tests that pass despite code mutations. Use to improve test quality.

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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.

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Turn surviving mutants into better tests, or into bug reports. Use when a mutation run reports escaped mutants, when the MSI gate fails, when asked whether a test suite is actually testing anything, or before proposing to lower a threshold.

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Mutation testing patterns for verifying test effectiveness. Use when analyzing branch code to find weak or missing tests.

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Spec-locked TDD with a mutation-testing gate — refine the intent into an immutable Gherkin contract (SHA-256 frozen), implement under the three laws of TDD, pass a judge audit, and merge only if every mutant dies.

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Refute-before-prove research discipline: automated counterexample sweeps before any formalization, meter-integrity audits for information-bound experiments, mutation-tested model checkers, pre-registered commit-or-cut gates for speculative directions, wrong-turn reporting, and numeric-claim provenance. Use when validating any new theorem, bound, equilibrium, or security claim; when building or trusting a checker, simulator, or experiment; or when deciding whether a speculative research direction lives or dies. NOT for exploratory brainstorming, product prioritization, writing style, or literature review.

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