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Testing Strategies @ docker/genai-stack

Testing Strategies for GenAI Stack

Overview

The GenAI Stack project utilizes various testing strategies and methodologies to ensure the quality and reliability of its components. In this documentation, we will cover the different testing options and provide examples for each.

What is Testing Strategies?

Testing Strategies refer to the approaches and methodologies used to design, develop, and execute tests for software projects. These strategies help ensure that the software functions correctly, is maintainable, and meets the desired requirements.

Why is Testing Strategies important?

Testing Strategies are crucial for maintaining the quality and reliability of software projects. They help:

  1. Identify and fix bugs early in the development process, reducing the time and cost of fixing issues.
  2. Ensure that new features and changes do not introduce unintended side effects or regressions.
  3. Improve code coverage and test the various aspects of the software.
  4. Increase confidence in the software and reduce the risk of introducing new issues.

Testing Options in GenAI Stack

Unit Tests

Unit tests are tests that focus on individual components or units of code in isolation. They are typically used to test specific functionality, logic, or behavior of a piece of code.

Example

Here’s an example of a unit test for a simple function in Python:

import unittest
      
      def add(x, y):
      return x + y
      
      class TestAdd(unittest.TestCase):
      def test_addition(self):
      self.assertEqual(add(1, 2), 3)
      self.assertEqual(add(-1, 1), 0)
      self.assertEqual(add(0, 0), 0)
      
      if __name__ == '__main__':
      unittest.main()

Source

Unit Testing in Python

Integration Tests

Integration tests are tests that focus on the interactions between different components or systems. They are used to test the integration and communication between different parts of the software.

Example

Here’s an example of an integration test for a simple web application using Selenium:

from selenium import webdriver
      from selenium.webdriver.common.keys import Keys
      
      def test_search(driver):
      driver.get("http://localhost:5000")
      driver.find_element_by_name("q").send_keys("test")
      driver.find_element_by_name("q").send_keys(Keys.RETURN)
      assert driver.find_element_by_tag_name("h1").text == "Search results for: test"
      
      if __name__ == "__main__":
      driver = webdriver.Firefox()
      test_search(driver)
      driver.quit()

Source

Selenium WebDriver

End-to-End Tests

End-to-end tests are tests that simulate the entire user journey, from the user interface to the backend systems. They are used to test the complete flow of the application and ensure that all components are working together correctly.

Example

Here’s an example of an end-to-end test for a simple web application using Cypress:

describe('End-to-End', () => {
      it('visits the root route', () => {
      cy.visit('/')
      cy.url().should('include', '/')
      })
      
      it('performs a search', () => {
      cy.get('#search-input').type('test')
      cy.get('#search-button').click()
      cy.url().should('include', '/search/test')
      })
      })

Source

Cypress Documentation

This documentation provides an overview of the testing strategies and methodologies used in the GenAI Stack project, including unit tests, integration tests, and end-to-end tests. It also provides examples for each testing option using popular testing frameworks such as Python's unittest, Selenium, and Cypress.
      
      Sources:
      
      * [Unit Testing in Python](https://docs.python.org/3/howto/unittest.html)
      * [Selenium WebDriver](https://www.selenium.dev/documentation/)
      * [Cypress Documentation](https://docs.cypress.io/guides/getting-started/writing-tests)

Explanation