Scraping Browser, Netflix App Testing. AI code Reviews and More TGNS154

What are some features of scraping browser that can help your automation test? How does Netflix app test at scale? And are AI code reviews replacing human reviewers? Find out in this episode of the Test Skill News show for the week of April 20th. Grab your favorite cup of coffee or tea and let's do this. Hey, before we get into the news, I want to thank this week's sponsor, Zap Test AI, an AI driven platform that can help you supercharge your automation efforts. It's really cool because their Intelligent Copilot generates optimized code snippets while their Plan studio can help you effortlessly streamline your test case management. And what's even better is you can experience the power of AI in action with their risk free 6 month proof of concept featuring a dedicated Zap expert at no upfront costs unlock unparalleled efficiency and ROI in a testing process. Don't wait. Schedule a demo now and see how it can help you improve your test automation efforts using the link down below so as you probably know, I spooked a lot of people. So last week I I was talking with the folks at Bright Data and they shared a feature with me that could make browser automation significantly easier for developers and testers working with playwright, puppeteer or Selenium. How? Well, first off, they pointed me to this awesome resource from a recent expert panel they did around how you can handle dynamic data, async data and anti bot mechanisms in your scraping or test automation workflows. And they also go over rate limiting and IP blocking strategies, managing brittle locators, simulating user interactions to trigger lazy loaded content, and how to scale your scraping operations using hosted browser infrastructure. And I think a lot of automation testers are missing out on scraping techniques that can really help them with a lot of things that they're not aware of. So ask the folks at Bright Data if they can help all my guild members and they share with me a link where you can test it for yourself with $15 in free credit using the link and down below do you know that only 11% of teams reach what is considered some of the highest QA maturity levels? Well, I found out all about this in a new report by Catalan in the State of Software Quality 2025 report reveals critical challenges and opportunities facing the software testing industry. The report finds a significant gap in QA maturity across organizations, with only 11% of teams reaching fully optimized processes. In most organizations, 82% still rely primarily on testing things in a manual EFF and time constraints remain the biggest obstacle. With 55% of QA professionals and over half of organizations struggle to secure funding for necessary automation tools. So what do you do with all this info? Well, I have a special treat for you. I'm excited to announce I'll be speaking at the Quality Horizon event by Catalan on the future of QA beyond bug hunting to core business drivers, where we'll be going over not only this survey, but also some key insights you could take away to to help you with your QA efforts as well. So we're going to go over what is QA as a driver for customer experience so you can learn how to make quality a key part of your customer strategy. You also learn how to build a culture of quality. We'll also be talking about the future of QA teams as well, and I'm really excited because we'll be joined by an awesome expert panel that also includes Rosie Sherry, who's the founder and CEO of Ministry of Testing. So hope to see you there and hear your questions. You can register using the link down below. So Tyreek King is back again with some more AI insights where he talks about a growing gap in software testing, the ability to evaluate human experience in an AI driven system. And he breaks down that while traditional testing methods focus on functional and performance, Tariq argues that today's AI powered applications require test strategies that prioritize how users feel, not just how the system functions. And Tyreek also points out that as while AI becomes prominent in software, testers are being pushed beyond checking for bugs and failures, they now face a harder challenge evaluating quality like trust, empathy and fairness, which he terms human centered attributes. And he suggests that this shift demands new tools, frameworks and mindsets, and that current test automation strategies are largely unequipped to measure subjective qualities such as user satisfaction or psychological safety. So I think it's a great take and also points out that how AI is not going to replace testers, it's just going to probably help modify what we currently do to do things. Like Tariq pointed out, that's going to be even more critical as we enter more and more AI based code and development. All right, so I always love real world case studies, so I was excited to find this next article about how Netflix does app testing at scale. So in this post it highlights how at Netflix the engineering team manages app test to support frequent releases, multiple device types in diverse regional requirements without compromising on stability or quality. And they describe how they do this by deploying a layered testing strategy which combines unit integration and UI tests. And what I think is really cool is their use of internal tools like Test Orchestration, which allows them to split and paralyze test executions across thousands of Android devices using Firebase Test Lab. And this strategy has drastically reduced execution time while maintaining consistent results and to catch issues early. Netflix integrates testing at every stage of the development cycle. They include pre merge checks on pull requests, nightly runs on physical and virtual devices, and occasional canary releases to a small segment of users before rolling out globally. And the team also maintains device coverage through continuous monitoring and prioritization based on actual user data. Rather than testing on every possible device, they only focus on the ones that reflect real world usage and emerging trends in their viewers base. All right, next up is our webinar of the week. So I'm really excited to have Clinton join us to talk all about the challenges of fintech testing and what organizations face such as ensuring regulatory compliance, preventing fraud, maintaining user trust, and achieving system scalability. So Clint is going to delve into how robust testing practices can help overcome these hurdles, focusing on delivering consistent, high quality user experiences that will help you to mitigate regulatory risk, strengthen fraud prevention systems, and maintain financial and data integrity through advanced testing techniques that he's going to demonstrate on this webinar. You want to miss it? Hope to see you there using the link down below. All right, speaking of real world experiences, I found another really quick blog post that goes over how AI code reviews can help you and if it's going to actually replace human team members. And this is by S. Shadaranga, who examines the growing use of AI driven code reviews. Any details? How tools like Amazon, Codewhisperer, GitHub, Copilot, and Deep Code are becoming increasingly sophisticated as identifying code issues such as code smells, vulnerabilities and style inconsistencies. However, he does emphasize that while AI tools can automate repetitive tasks and surface common coding errors faster, they fall short in areas requiring deep contextual understanding, architectural judgment, or assessing broad system impacts, skills essential for senior engineers and experienced testers. And he also goes over how AI models often lack the ability to fully grasp project specific conventions or nuanced team dynamics. And I think this ties in really well with what Tariq was saying, how we really need to think about how a user is going to feel as well about a feature, and I can't figure that out. So that's why we need both AI and human intelligence together. Definitely. Another must read. Next up is Follow the Money Segment. This is how Bob plon has raised 7.5 million to simplify AI driven infrastructure by offering a serverless platform that allows developers to write data pipelines using familiar languages like Python and SQL. And this approach eliminates the need for managing complex infrastructure such as spot clusters or intricate configuration files. And I never heard of this platform before, so I thought it'd be a great thing for you to check out as well. And last up is how financial teams are bracing Contract as code to control API risk so this article by Matt talks about how API development and testing, finance and compliance teams are beginning to assert more control over over API contracts which are traditionally managed by engineering teams. And according to a report in the New Stack, this move is driven by the growing need for regulatory compliance, data privacy and reliability, and highly scrutinized industries like fintech and banking and the adoption of contract as code. A practice where API contracts are treated like source code which are versioned, tested and reviewed is enabling non developers to participate directly in API governance and how tools are allowing finance and risk professionals to define and validate contracts in a standardized, transparent format. And the collaboration is increasingly finalized through Git based workflows enabling shared ownership between technical and non technical teams. And also goes over how some organizations are also incorporating contract linting, drifting and testing directly into CICD pipelines, pushing quality assurance responsibilities further left into the contract definition stage. All right, for looks of earth and value we covered in this news episode, head on over to the links in the comment down below. So that's it for this episode of the Test Skill News Show. I'm Joe. The missions help you succeed in creating end to end full stack automation awesomeness. As always, test everything and keep the good. Cheers.