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Performance Testing and ChatGPT

Performance testing applications requires a set of skill that are build and gathered over many years of studying and using the various techniques and tools that are required to make sure the application you are testing is fit for production. Now we have all heard of Artificial Intelligence (AI) and the many tools and companies that now exist in the AI space.

Based on a quick look on the internet there are around 15,000 AI startups in the United States alone. So surely with all that technology at our disposal we should be able to use these AI tools to define our performance tests meaning that anyone can determine what performance testing should take place regardless of experience and training.

To build, execute and analyse these tests still requires a competent performance tester but the definition of what should be done could be handed over to Artificial Intelligence right? Let’s find out shall we, we will use ChatGPT as this commonly available and probably the one most have heard of.

Performance Testing in a Scrum Framework

Agile development teams generally follow the principles of Scrum where individual teams work together to manage their workload through a set of values, principles, and practises.

From a development perspective this gives a team which comprises a Product Owner, Scrum Master, and Development team the autonomy to work and deliver in an environment that suits their needs and helps them develop change for the organisation in a way that maximises efficiencies.

This blog post is not an overview of the scrum methodology but will require some understanding of the processes that take place, and these will be discussed throughout his post. What we are trying to do is understand how in an Agile delivery framework we can make sure that performance testing is not lost or overlooked. Scrum teams work in short sprints that means that your performance testing must, like the unit testing built by the development teams, be lightweight and, well... agile, for want of a better word.

Maximizing Testing Efficiency: Parameterizing Playwright Scripts

Parameterization in testing is a powerful technique that allows you to run the same test script with different inputs, configurations, or scenarios. In the world of browser automation and testing, Playwright provides various methods to parameterize your scripts, making it easier to validate different use cases and ensure the robustness of your web applications.

In this blog post, we'll explore several approaches to parameterizing Playwright scripts.

Browser Automation Debug with Playwright Trace Viewer

Playwright Trace Viewer is a powerful tool that allows developers and testers to gain deeper insights into the execution of browser automation scripts created with Playwright. It provides a visual representation of script execution, enabling users to diagnose issues, optimize performance, and understand the flow of actions within their automation scripts.

In this blog post, we'll explore how to use Playwright Trace Viewer effectively to enhance your browser automation projects.

Playwright Test Generator

Playwright Test Generator is a powerful tool that simplifies the process of creating and maintaining end-to-end tests for web applications. Whether you're a developer or a QA engineer, Playwright Test Generator can save you time and effort by generating test scripts that ensure the reliability and functionality of your web applications.

In this blog post, we'll walk you through the process of using Playwright Test Generator to create and manage automated tests effectively.

TL;DR head straight to Recording a Script With Playwright Codegen if you already have Playwright for Node.js environment installed and want to record a new script.