testing▌

Modern unit testing with MSTest 3.x/4.x using current APIs and best practices. \n \n Covers test class structure, lifecycle management, and the AAA (Arrange-Act-Assert) pattern with sealed classes and constructor-based initialization \n Provides comprehensive assertion APIs including equality, null checks, exception testing (Throws/ThrowsExactly), collections, strings, comparisons, and type assertions \n Supports data-driven tests via DataRow and DynamicData with ValueTuple and TestDataRow for t

End-to-end testing patterns with Playwright for full-stack Python/React applications. \n \n Covers test structure, page object model, selector strategy (data-testid > role > label), and wait strategies for reliable cross-browser testing \n Includes auth state reuse to avoid repeated logins, test data management via API helpers, and debugging techniques for flaky tests \n Provides CI integration examples, fixture setup for authentication, and naming conventions for tests, pages, and locators \n S

Custom Playwright scripts for any browser automation task, with auto-detected dev servers and visible browser execution. \n \n Auto-detects running localhost dev servers; writes test scripts to /tmp to avoid project clutter \n Supports responsive design testing, login flows, form filling, link validation, and screenshot capture across multiple viewports \n Includes helper utilities for safe clicks, typed input, cookie banner handling, and table data extraction \n Configurable custom HTTP headers

Robust backtesting systems that avoid look-ahead bias, survivorship bias, and overfitting. \n \n Event-driven and vectorized backtester implementations with realistic transaction cost modeling, slippage, and commission handling \n Walk-forward optimization and Monte Carlo simulation for strategy robustness testing across multiple time windows \n Comprehensive performance metrics including Sharpe, Sortino, Calmar ratios, drawdown analysis, and win-rate calculations \n Point-in-time data handling,

Browser automation with Playwright MCP for web navigation, form interaction, and data extraction. \n \n Supports navigation, element interaction (click, type, select), screenshots, and accessibility snapshots that return element references for precise targeting \n Includes JavaScript execution via browser_evaluate and multi-step atomic operations through browser_run_code for complex workflows \n Requires --shared-browser-context flag to maintain browser state across sequential commands; server r

Guidance for property-based testing across languages and smart contracts. \n \n Detects high-value PBT patterns automatically: serialization pairs, parsers, validators, normalization, data structures, algorithms, and smart contract state invariants \n Provides a property catalog with 10 core patterns (roundtrip, idempotence, invariant, commutativity, associativity, identity, inverse, oracle, easy-to-verify, no exception) ranked by strength \n Includes decision tree routing to language-specific r

Test-Driven Development (TDD):

Unit testing Jakarta Bean Validation constraints and custom validators without Spring context. \n \n Covers testing built-in constraints ( @NotNull , @Email , @Min , @Max , @Size ) and custom @Constraint implementations with violation assertion patterns \n Includes cross-field validation, validation groups for conditional rules, and parameterized test scenarios for multiple inputs \n Provides setup patterns using Validation.buildDefaultValidatorFactory().getValidator() and assertion helpers to e

Playwright E2E testing patterns with Page Object Model, configuration, CI/CD setup, and flaky test strategies. \n \n Provides Page Object Model structure for maintainable test organization, with reusable page classes that encapsulate locators and navigation logic \n Covers multi-browser testing across Chromium, Firefox, WebKit, and mobile devices with configurable retries, parallelization, and artifact capture (screenshots, videos, traces) \n Includes flaky test identification and remediation pa

Expert guidance for designing statistically valid A/B tests and experiments. \n \n Provides a structured hypothesis framework, sample size calculations, and metrics selection (primary, secondary, guardrail) to ensure rigorous test design \n Covers test types (A/B, A/B/n, MVT, split URL), traffic allocation strategies, and implementation approaches (client-side vs. server-side) \n Includes pre-launch checklists, guidance on avoiding common pitfalls like early peeking, and frameworks for analyzing