Master Generative AI for Software Testing: Manual to Auto

Leverage AI prompts to generate and validate test cases for a contact us page, explore prompt design, and create test plans for manual testing tasks.

Harness no-code AI tools and local models with GPT-for-all to generate test cases for the contact us page, including input validation and success or error messages, offline and online.

Learn why python excels in testing and AI, thanks to simplicity, cross-platform support, and powerful libraries like playwright, requests, transformers, beehive, and OpenAI's API for automated UI and API tests.

Explore a simple Python login program that uses variables, a function, and if-else logic to validate credentials against a JSON-backed list of test cases, illustrating basic testing concepts.

Install and configure Visual Studio Code as a Python-friendly IDE, install essential Microsoft extensions for debugging, code execution, formatting, and icons, and tailor themes and extensions for automated testing.

Explore Python basics: declare variables of strings, integers, floats, booleans, and none, and print data with f-strings. Practice lists, dictionaries, and sets, including unique values and accessing keys.

Learn to write reusable Python functions that organize code using def, parameters, and return. Validate emails and calculate areas with simple function examples and print statements.

Explore robust testing through exception handling using a simple divide function that demonstrates try and catch for division by zero and invalid input types, with custom error messages.

Leverage Openai's API to generate test cases from requirements and enhance test automation frameworks with python, playwright, and ci integration, boosting coverage and reducing manual effort.

Set up OpenAI's API for test automation by creating an account, adding credits (minimum $5) and using the free trial, then review usage and generate a secret API key.

Build a Python client to generate test cases with OpenAI API, configuring a secret key, defining a prompt as messages, and producing test cases for WebDriver University's contact us page.

Explore generating and refining gherkin and cucumber scenarios with open ai, configure prompts and avoid overwrites, then review, format, and download the feature file for the contact us page.

Implement setup and teardown with behave by using environment.py in the features folder, and before all and before scenario hooks to configure Playwright, launch the browser, and open maximized pages.

Learn to write first step definitions with Behave and Playwright in a behavior-driven framework, using dynamic selectors, a custom context, and actions like navigate and fill.

Apply the dry principle by creating a custom context in utils/types.py to centralize page, browser, and Playwright, then refactor environment and steps for reuse.

Finalize the first scenario by using analyze steps to generate code for unimplemented steps, leveraging OpenAI's API, and implementing selectors for first name, last name, email, and message with submit.

Finalize the remaining test scenarios for the contact us form by uncommenting steps, validating errors with empty and invalid inputs, and using AI-assisted step analysis and dynamic selectors.

Explore how the background keyword reduces code duplication in feature files by listing common steps that execute prior to any scenario, improving readability and maintainability.

Learn how the background keyword enforces preconditions before each scenario in behave, guiding navigation to the contact us form, reusing steps, and applying the dry principle.

Generate API test scenarios with ai by building a simple GET request to the status endpoint using Postman and an OpenAI-driven generator, integrating into an automation framework.

Learn to test api responses by building and validating requests, asserting status codes like 200, and checking response text, with beehive-generated steps and context-based url handling.

Optimize the testing framework by refactoring API and UI test flows with behave hooks and context flags to avoid browser launches for API tests and enable UI screenshot capture.

Create and configure an advanced Jenkins job to run automated test suites with a custom workspace and a Python beehive command using regression tags, monitor logs, and preserve build history.

Learn to generate Allure reports in Jenkins by installing the Allure plugin, configuring post-build actions, preserving reports for targeted regression and API tests, and attaching failure images for debugging.