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Rodeo Chatbot Testing Strategy

This document outlines the testing strategy for the Rodeo Chatbot project. It covers the types of tests we use, how to run them, and best practices for maintaining and expanding our test suite.

Table of Contents

  1. Overview
  2. Types of Tests
  3. Test Files
  4. Running Tests
  5. Writing New Tests
  6. Continuous Integration
  7. Best Practices

Overview

Our testing strategy aims to ensure the reliability, functionality, and maintainability of the Rodeo Chatbot. We employ a combination of unit tests, integration tests, and end-to-end tests to cover various aspects of the system.

Types of Tests

Unit Tests

Unit tests focus on testing individual components or functions in isolation. They are located in the tests/ directory and typically have a one-to-one correspondence with the modules in the src/rodeo/ directory.

Key areas covered by unit tests:

  • CLI argument parsing
  • Chat class methods
  • Utility functions

Example: tests/test_cli.py

Integration Tests

Integration tests verify that different parts of the system work together correctly. They are primarily located in tests/test_integration.py.

Key areas covered by integration tests:

  • CLI and Chat class interaction
  • Session persistence
  • Command processing pipeline

Example: tests/test_integration.py

End-to-End Tests

End-to-end tests simulate real-world usage of the chatbot. They interact with the system as a user would, typically through the CLI interface.

Key areas covered by end-to-end tests:

  • Full conversation flows
  • CLI input/output
  • Error handling and edge cases

Example: tests/test_e2e.py (if implemented)

Test Files

  • tests/test_cli.py: Unit tests for CLI functionality
  • tests/test_chat.py: Unit tests for the Chat class
  • tests/test_integration.py: Integration tests
  • tests/test_e2e.py: End-to-end tests (if implemented)

Running Tests

To run all tests:

pytest tests/

To run a specific test file:

pytest tests/test_file_name.py

To run a specific test function:

pytest tests/test_file_name.py::test_function_name

Writing New Tests

When adding new features or modifying existing ones:

  1. Start by writing unit tests for the new/modified components.
  2. Update or add integration tests to cover the interaction of the new/modified components with the rest of the system.
  3. If the change affects the overall user experience, consider adding or updating end-to-end tests.

Use descriptive test names and include docstrings explaining the purpose of each test.

Continuous Integration

(Note: Implement this section when CI is set up)

We use [CI Tool Name] for continuous integration. All tests are automatically run on each push to the repository. PRs cannot be merged unless all tests pass.

Best Practices

  1. Maintain test independence: Each test should be able to run independently of others.
  2. Use mocking judiciously: Mock external dependencies, but be cautious not to over-mock, which can lead to tests that don't reflect real-world behavior.
  3. Keep tests fast: Optimize tests to run quickly to encourage frequent running.
  4. Test edge cases: Include tests for boundary conditions and error scenarios.
  5. Maintain test coverage: Aim for high test coverage, but prioritize critical paths and complex logic.
  6. Refactor tests: Keep tests clean and maintainable. Refactor as needed when the main code changes.
  7. Use parametrized tests: For similar tests with different inputs, use pytest's parametrize feature.

Remember, tests are a critical part of our development process. They help catch bugs early, document expected behavior, and make it easier to refactor and improve our code with confidence.