Scaling your test automation initiatives can be daunting. In a recent webinar, Test Automation at Scale: Lessons from Top Performing Distributed Teams, panelists from Accenture, Bayer, and Eversana shared their insights for overcoming common challenges. Here are their top recommendations.

Establish clear processes for collaboration.
Daily standups, sprint planning, and retrospectives are essential for enabling communication across distributed teams. “The only way that you can build a quality product that actually satisfies the business requirements is [through] that environment where you’ve got the different teams coming together,” said Ariola Qeleposhi, Test Automation Lead at Accenture.

Choose tools that meet current and future needs.
Consider how tools will integrate and the skills required to use them. While a “one-size-fits-all” approach may seem appealing, it may not suit every team’s needs. Think beyond individual products to the overall solution, advised Anand Bagmar, Senior Solution Architect at Applitools. Each product team should have a test pyramid, and tests should run at multiple levels to get real value from your automation.

Start small and build a proof of concept.
Demonstrate how automation reduces manual effort and finds defects faster to gain leadership buy-in. “Proof of concepts will really help to provide a form of evidence in a way to say that, okay, this is our product, this is how we automate or can potentially automate, and what we actually save from that,” said Qeleposhi.

Consider a “quality strategy” not just a “test strategy.”
Involve all roles like business, product, dev, test, and DevOps. “When you think about it as quality, then the role does not matter,” said Bagmar.

Leverage AI and automation as “seatbelts,” not silver bullets.
They enhance human judgment rather than replace it. “Automation is a lot, at least in this instance, it’s like a seatbelt. You don’t think you’ll need it, but when you need it you better have it,” said Kyle Penniston, Senior Software Developer at Bayer.

Build, buy, and reuse.
Don’t reinvent the wheel. Use open-source tools and existing frameworks. “There will be great resources that you can use. Open-source resources, for example, frameworks that might be there that you can use to quickly get started and build on top of that,” said Bagmar.

Provide learning resources for new team members.
For example, Applitools offers Test Automation University with resources for developing automation skills.

Measure and track metrics to ensure value.
Look at reduced manual testing, faster defect finding, test coverage, and other KPIs. “You need to get some metrics really, and then you need to use that from an automation side of things,” said Qeleposhi.

The key to building a solid foundation for scaling test automation is taking an iterative, collaborative approach focused on delivering value and enhancing quality. With the right strategies and tools in place, teams can overcome common challenges and achieve automation success. Watch the full recording.

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Test automation is crucial for any software engineering team to ensure high-quality releases and a smooth software development lifecycle. However, test automation efforts can often be tedious, time-consuming, and require specialized skills. New AI tools are emerging that can help accelerate test automation, handle flaky tests, increase test coverage, and improve productivity.

In a recent webinar, Rizel Scarlett and Anand Bagmar discussed how to leverage AI-powered tools like GitHub Copilot and Applitools to boost your test automation strategy.

GitHub Copilot can generate automated tests.

By providing code suggestions based on comments and prompts, Copilot can help quickly write test cases and accelerate test automation development. For example, a comment like “validate phone number” can generate a full regular expression in seconds. Copilot also excels at writing unit tests, which many teams struggle to incorporate efficiently.

Applitools Execution Cloud provides self-healing test capabilities.

The Execution Cloud allows you to run tests in the cloud or on your local machine. With self-healing functionality, tests can continue running successfully even when there are changes to web elements or locators. This helps reduce flaky tests and maintenance time. Although skeptical about self-healing at first, the experts found Applitools to handle updates properly without clicking incorrect elements.

Together, tools like Copilot and Applitools can transform your test automation.

Copilot generates the initial test cases and Applitools provides a self-healing cloud environment to run them. This combination leads to improved productivity, reduced flaky tests, and increased coverage.

Applitools Eyes and Execution Cloud offer innovative AI solutions for automated visual testing. By leveraging new technologies like these, teams can achieve test automation at scale and ship high-quality software with confidence. To see these AI tools in action and learn how they can benefit your team, watch the full webinar recording.

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