AI in Testing, Magic Quadrant, Tylor Swift is Back and More TGNS88

How do you integrate AI with software testing? Want to know one of the better BDD frameworks and what tool just ranked highest on the Gartner Magic Quadrant for application performance monitoring and observability? Find out in this episode of the Test Guild News show for the week of July 16th. So grab your favorite cup of coffee or tea and let's do this. Before we get into it, are you looking to take your automation project to the next level? Look no further than Applitools and the Visual AI validation testing. Trust me, it is a game changer. Plus you could try it for yourself by creating a free account. Now by clicking the special link in the first comment down below and see the difference for yourself. First article comes your way via Sabab, who's a software engineer, and he discusses the implementation of a page object model I think is really going to help you with your automation. So this post actually covers implementing the Palm design pattern with an object repository that I thought was interesting. So in the post, Sabbath emphasizes the importance of Palm and enhancing the maintainability and reliability of automation code. He goes on to explain how each web page or user interface UI component is represented by a separate class called a page object, which encapsulates the elements and behaviors of the corresponding web page or UI component. He also demonstrates how to store UI locators in an external JSON file acting as an object repository, and this is used to separate code interactions with UI and locators. It also provides an example of how to add locators for various fields. And this post also serves as a valuable resource for software developers and testers looking to improve their animation codes, maintainability and reusability. Definitely something you should check out and you can find it in the first comment down below. Also, Jason Arbon is back on the show with even more AI automation awesomeness. So in this latest blog post it's called Testing Bolt on AI and it's a really thought provoking discussion on integration of AI and specifically using open APIs. ChatGPT with software testing Also, Jason argues that testers often underutilize AI capabilities, sticking to predictable, concise interactions, and he encourages testers to use their skills to reveal more complex test cases to learn from AI, virtually adding expert testers to their team for free. And Jason also demonstrates this by engaging in a dialogue with ChatGPT about boundary testing and it shows how the AI, when asked to think beyond the typical answers, providing comprehensive and well thought out responses, proving its potential to enhance test coverage. Jason also concludes by arguing that testers give AI the same opportunities to explain, elaborate, and iterate on a topic in conversation, just as they would with a human colleague. Speaking of AI, I have a free webinar you should check out that's going to help you with generative AI. So this is a webinar I'll be hosting next week, and it's with Todd from Reflect, and it's going to be a demonstration how generative AI can revolutionize the way we build test software. This webinar is going to focus on Reflect's integration with Open API's ChatGPT, which allows testers to write tests in plain English and have them automatically executed. And the session is going to cover two key use cases, enabling test teams to practice behavior driven development without the need for underlining automation frameworks or restrictive Gherkin syntax, and avoiding flaky tests by using AI assisted targeting to locate elements on the page. And it's going to happen on July 25th. You can register now using the link down below and I hope to see you all there. All right, speaking of gherkin and cucumber, I actually have an article on a framework I think you should learn more about if you're not using it already. And this is by Enos, who talks about a recently published article on API testing with SpecFlow. And so this article takes a deep dive into using BDD with SpecFlow and particularly in the context of API testing. And despite initial skepticism, Enos found that Gherkenstahl's test with the given when then structure and natural language syntax really turned out to be an incredible useful way, especially for testing APIs. And in this article he takes a deep dive into explaining the behavior driven development with Spec Flow and how do you actually utilize bdd, the process emphasizing collaboration and communication, and also outlines how to create a simple BDD Spec Flow Flow Howard automation testing framework. He also demonstrates how to use SpecFlow's data driven testing capabilities to handle test data, and he concludes by encouraging others to explore Gherking for API testing. Really great article. Definitely check it out and you can find that once again in the first comment down below. So who are the leaders in the Gartner magic quadrant for 2023 for application performance monitoring and observability? Well, I found one of them on LinkedIn and this was posted by larby How New Relic has been recognized as a leader for the 11th consecutive year and this article goes over how the company attributes this recognition to its commitment to data accessibility, actual insights from different data sources and cost effectiveness, and also support for OpenTelemetry and it offers five key points that make a difference. Like the Unified Full Stack Observability platform is able to automatically correlate all telemetry data sources to improve operational efficiency and provide actionable insights in context throughout the DevSecOps cycle, has advanced security vulnerability management capabilities, is the industry's first generative AI assistant and 650 turnkey connectors and also openness of the platform embracing OpenTelemetry integration with Prometheus, Grafana, open source agents, GraphQL API, custom React visualizations, apps and more. So we spoke a lot about AI so far, especially generative AI and ChatGPT. But how about for performance? Well, in a recent blog post I found an article that covers this as well. This post by Mohnish who explores the integration of K6, one of the top testing tools out there for load testing and ChatGPT in the AI language model to streamline performance testing processes. And this article really takes a step by step guide approach on setting up K6 generating automated K6 scripts using Chat GPT, interpreting test results and and how to export results in preferred formats. He also demonstrates how Chat GPT can be used to automate the generation of K6 scripts, saving time and effort, and it also discusses the importance of understanding the interpreting test results to optimize applications performance. And the post concludes with a demonstration of how to export K6 results in different formats for effective analysis and reporting. And this really cool approach to performance testing offers a way to identify and address performance issues early on ensuring high performance applications, which I think more people need to do for sure. And besides performance testing, I think another testing technique more folks need to get into is chaos testing, and so I found a resource for that as well. So this article goes over the concept of Chaos testing, which is a methodology designed to improve system resilience, and the author explains how kiosk testing, which involves injecting controlled failures into a system to identify potential weakness, differs from traditional testing methods. And it includes some of the benefits of this approach like improved system performance, increase end user satisfaction and enhanced architecture design. He also shares Ally Tech's own Chaos Testing framework, which uses cloud resilience hub chaos engineering tools and load testing tools. And the framework combines performance testing and chaos engineering to assess the impact of system failures on user experience. And the article concludes by emphasizing that kiosk testing, just like performance testing, is not a one time activity but a continuous process vital for maintaining resilience and reliable systems. And believe it or not, Taylor Swift is back and Performance News she brought down another ticket sale operation for Ticketmaster, this time in France. And what does it mean for performance engineers and testers? Let's find out. So Taylor Swift's latest tour ticket sales in France has been temporarily halted due to technical glitches in Ticketmaster. What happened is the issue prevented users or fans from logging into the website and which affected sales for Swift's concerts in Paris. And this hiccup kind of recalls the initial sale of Swift's tour in the US which also experienced delays and cancellation. And so they obviously didn't really learn from that first experience they had in the U.S. it really underscores the importance of rigorous stress testing and capacity planning to ensure systems handle peak loads, especially during high demand events. It also highlights the need for effective capacity contingency planning and clear communication with users in the event of disruptions. And by learning from these real world scenarios, developers and testers can better prepare their systems for future challenges and maintain a positive user experience even under demanding conditions. And it also highlights, as we talked about earlier, performance testing, resilience testing is not a one and done activity. It needs to be constantly done to make sure that the user is always getting the best experience of all. Right? For links of everything value we covered in this news episode, head over to the links in the first comment down below. And while you're there, make sure to check out our awesome sponsor applitools free account offer and discover how to take your automation testing to the next level. Leveraging Visual AI so that's it for this episode of the Test Guild News Show. I'm Joe. My mission is to help you succeed in creating end to end full stack pipeline automation awesomeness. As always, test everything and keep the good. Cheers.