Unit Test Parameterized

What it does

This skill enables AI agents to generate parameterized unit tests, which are test cases that run the same logic with different input values. It helps ensure code correctness across a wide range of scenarios without writing repetitive test code.

When to use it

• You need to verify a function's behavior against multiple input-output pairs efficiently.
• You're working on a project where test coverage is critical, and manual test creation would be time-consuming.
• You want to automate the generation of unit tests for functions that handle various edge cases or data types.

Key capabilities

• Generates parameterized test cases based on provided inputs and expected outputs.
• Supports multiple testing frameworks (e.g., Jest, pytest).
• Reduces redundancy in test code by using dynamic input parameters.

Example prompts

• "Generate a parameterized unit test for a function that calculates the square of a number with inputs [2, 3, -1] and expected outputs [4, 9, 1]."
• "Create a Jest test suite for a validation function using these input-output pairs: { 'a': true }, { '': false }, { '123': true }."
• "Write parameterized unit tests in pytest format for a function that checks if a string is a palindrome."

Tips & gotchas

• Ensure your input-output pairs are well-defined and cover edge cases to maximize test effectiveness.
• Some testing frameworks may require additional setup or plugins to support parameterized tests.