feat: Generated API Test Cases using AI #183
Description
Description
Implement an AI-powered system that automatically generates basic test cases for newly created API endpoints. This feature will streamline the testing process, improve coverage, and reduce manual effort when adding or modifying APIs.
The AI system will analyze the API's input parameters, expected outputs, and error conditions to generate positive and negative test cases compatible with the existing testing framework.
Requirements
-
API Input/Output Analysis:
- Extract input parameters and expected outputs from API endpoint definitions.
- Identify required and optional fields, data types, constraints, and error conditions.
-
Test Case Generation:
- Generate unit tests for basic CRUD operations (if applicable).
- Include positive test cases (valid inputs and expected outputs).
- Include negative test cases (invalid inputs, missing fields, and edge cases).
-
Integration with Testing Framework:
- Generated tests should be compatible with the existing testing framework (e.g., Jest, Mocha).
- Place generated test files in the appropriate
testsdirectory structure.
-
Developer Review:
- Allow developers to review and adjust AI-generated test cases if necessary.
-
Documentation:
- Provide clear setup instructions and usage guidelines for the AI-generated test cases.
Acceptance Criteria
- AI tool generates test cases for at least 90% of API endpoints.
- Positive and negative test cases are included for all analyzed endpoints.
- Generated test cases integrate seamlessly into the existing testing workflow.
- Developers can manually review and adjust the test cases.
- Documentation clearly explains the feature and setup.
Potential Tools/Approaches
- AI Integration: OpenAI GPT API or similar LLMs to analyze API definitions.
- API Parsing: Use Swagger/OpenAPI specification or Postman collections to extract API details.
- Framework Compatibility: Jest, Mocha, or other existing testing tools in the boilerplate.