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moq-analyzers-research-methodology

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Research methodology for Moq analyzers: evidence bar, adversarial refutation, performance prediction, idea lifecycle.

Software Engineering#developer tools#code analysis#software testing#research methodology#Moq analyzers
Authorrjmurillo
Version1.0.0
Installs0

System Documentation

What problem does it solve?

This Skill provides a comprehensive methodology for researching and developing analyzers within the Moq.Analyzers repository, ensuring the validity and reliability of analyzer implementations.

Core Features & Use Cases

  • Evidence Bar: Ensures mechanisms explain all observed data points, reducing false positives and negatives.
  • Adversarial Refutation: Requires independent validation to prevent blind spots and ensure thorough testing.
  • Performance Prediction: Predicts performance impacts before running tests to assess potential regressions.
  • Idea Lifecycle: Guides the development process from idea to implementation, including retirement of rejected features.
  • Experiment Hygiene: Provides guidelines for managing experiments in a mission-critical environment.

Quick Start

Load this Skill to define and evaluate new analyzer ideas or investigate issues in the Moq.Analyzers repository.

Dependency Matrix

Required Modules

None required

Components

Standard package

💻 Claude Code Installation

Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.

Please help me install this Skill:
Name: moq-analyzers-research-methodology
Download link: https://github.com/rjmurillo/moq.analyzers/archive/main.zip#moq-analyzers-research-methodology

Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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