Results for “a-b-testing”

Guides writing Rust tests with TDD, covering unit, integration, async, property-based, mocking, and coverage patterns.

Provides best practices, patterns, and solutions for testing Vue.js applications, covering Vitest, Vue Test Utils, component testing, mocking, and Playwright for E2E testing.

Runs API, performance, load, stress, and HTTP tests using the basjoofan CLI with configurable concurrency, duration, and statistics output.

Write reliable, maintainable Kotlin tests using Kotest, MockK, coroutine testing, property-based testing, and Kover coverage following TDD methodology.

Validates observable behavior of apps, CLIs, APIs, and generated artifacts against a prewritten contract without inspecting source code.

Kotlin testing patterns with Kotest, MockK, coroutine testing, property-based testing, and Kover coverage. Follows TDD methodology with idiomatic Kotlin practices.

Write reliable Kotlin tests using Kotest, MockK, coroutine testing, property-based testing, and Kover coverage, following a TDD workflow.

Kotlin testing patterns with Kotest, MockK, coroutine testing, property-based testing, and Kover coverage. Follows TDD methodology with idiomatic Kotlin practices.

Kotlin testing patterns with Kotest, MockK, coroutine testing, property-based testing, and Kover coverage. Follows TDD methodology with idiomatic Kotlin practices.

Provides Vue.js testing best practices, patterns, and solutions for common pitfalls using Vitest, Vue Test Utils, and Playwright.

Design and evaluate A/B tests with power, sample size, and robust metric interpretation. Use when: (1) planning controlled experiments, (2) reading p-values/effects, (3) sequential testing safeguards. NOT for: dark-pattern optimization.

Analyze A/B test results with statistical significance, sample size validation, confidence intervals, and ship/extend/stop recommendations. Use when evaluating experiment results, checking if a test reached significance, interpreting split test data, or deciding whether to ship a variant.

A/B and multivariate testing methodology. Design experiments, calculate sample sizes, determine statistical significance, avoid common pitfalls, and interpret results. Platform-agnostic framework applicable to landing pages, emails, ads, pricing, and product features. Use when the user asks about A/B testing, split testing, experiment design, statistical significance, or conversion experiments.

Design rigorous A/B tests with clear hypotheses, controlled variants, appropriate metrics, and sample size calculations.

Automates visual testing and UI interaction verification using browser automation after deploying features.

Provides F# testing patterns using xUnit, FsUnit, Unquote, FsCheck, and integration testing with Testcontainers and WebApplicationFactory, including test organization and anti-patterns.

A B Testing Based Design Skill

Designs an A/B test or experiment with clear hypothesis, variants, success metrics, sample size, and duration. Use when planning experiments to validate product changes or test hypotheses.

A/B test design and experiment planning for paid advertising. Structured hypothesis framework, statistical significance calculator, test duration estimator, sample size calculator, and platform-specific experiment setup guides (Meta Experiments, Google Experiments, LinkedIn A/B). Use when user says A/B test, split test, experiment design, test hypothesis, statistical significance, sample size, or test duration.

Designs A/B tests with sample size calculation, statistical significance testing, and result interpretation

Algebra Based Testing Skill

Design, prioritize, and evaluate product experiments with clear hypotheses and defensible decisions, including A/B testing, sample size estimation, and statistical interpretation.

Analyze A/B test results for statistical significance with ship, extend, or kill recommendations

Applied Botany Testing Skill

Transforms A/B test and product experiment data into actionable readouts with hypothesis, metrics, interpretation, and decision.

Analyzes test suites to measure assertion diversity, detect shallow or trivial assertions, and identify tests that lack meaningful verification.

Prevents AI-introduced regressions with sandbox-mode API testing, automated bug-check workflows, and patterns that catch blind spots where the same model writes and reviews code.

Applied Logic Testing Skill

Write effective unit tests with best practices for any project. Use when writing tests, creating test cases, improving test coverage, increasing confidence before release, or when the user mentions testing. Mutation score / assertion theater → test-mutation.

AL App/Test project layout diagnosis for Business Central. Use when the main app compiles test sources, AL0297 appears on test object IDs, Library Assert or Library - Sales is missing, test/app.json is not recognized, or a multi-root workspace with app and test projects needs diagnosis.