What is PICT (Pairwise Independent Combinatorial Testing)?

PICT is a testing methodology that focuses on testing all possible pairs of parameter values. Research shows that most software bugs are triggered by either a single input parameter or an interaction between two, making pairwise testing a highly efficient alternative to exhaustive testing.

Can I define custom rules and dependencies?

Yes, the skill supports a robust constraint syntax (e.g., IF [OS] = 'Linux' THEN [Browser] <> 'Safari') to ensure that generated test cases represent valid real-world scenarios and business logic.

Is this suitable for testing APIs?

Absolutely. It is ideal for API testing where you need to verify combinations of different HTTP methods, authentication states, payload sizes, and header values efficiently.

How does this skill reduce the number of test cases?

Instead of testing every single possible combination (which can lead to thousands of tests), this skill uses mathematical algorithms to generate a minimal set of cases where every value of every parameter is tested with every value of every other parameter at least once.

PICT Test Designer

Name: PICT Test Designer
Author: ShunmeiCho

byShunmeiCho

0•

Seguridad y Pruebas

Generates optimized pairwise test cases and combinatorial models from software requirements or code.

The PICT Test Designer skill streamlines software quality assurance by applying Pairwise Independent Combinatorial Testing (PICT) to your development workflow. It analyzes requirements to extract parameters, applies equivalence partitioning for value selection, and enforces business constraints to produce a minimal yet comprehensive set of test cases. This tool is perfect for developers and QA engineers looking to achieve high test coverage for complex systems, APIs, and configurations without the overhead of exhaustive manual test design, significantly reducing the total number of test cases while maintaining high defect detection rates.

Características Principales

01Pairwise combinatorial test generation to maximize coverage

02Automated parameter and value extraction from code or requirements

03Support for boundary value analysis and equivalence partitioning

04Business constraint logic implementation for valid test scenarios

050 GitHub stars

06Formatted markdown test matrix generation with expected outcomes

Casos de Uso

01Configuration testing across varied OS, browser, and hardware environments

02Validation of complex web forms with conditional logic and dependencies

03API endpoint testing with multiple interacting parameters and headers

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add shunmeicho/claude-config pict-test-designer

For use in Claude.ai and ChatGPT

Download Skill