Parasoft(link is external) is showcasing its latest product innovations at embedded world Exhibition, booth 4-318(link is external), including new GenAI integration with Microsoft Visual Studio Code (VS Code) to optimize test automation of safety-critical applications while reducing development time, cost, and risk.
Over the last few years, we've heard increasing buzz about "codeless" platforms to help develop and create websites, enterprise apps and more. Today, we're seeing hosts like WordPress and Wix, marketing software like Salesforce, and e-commerce delivery platforms like Shopify become a staple across the enterprise, making it super simple for your average Joe to whip together a website or blog — no coding required.
Believe it or not, this rise in "codeless" development and delivery is translating over to the DevOps world — even for those who are well-versed in coding and the numerous different languages that come with it. So much so that codeless test automation has become a top priority for testers, as well as the developers who are now also taking on some of those testing responsibilities.
Despite the increased interest, many organizations are struggling with how to best implement codeless test automation for increased output with very little trial-and-error. Now's the perfect time to get up to speed and learn how your organization can go codeless.
Let's start with a basic understand of codeless test automation and its benefits.
Why the sudden uptick in codeless test automation?
Codeless test automation is exactly as it sounds. It's testing that requires zero coding skills throughout the entire testing pipeline. Yet, while many are quick to attribute the growing skills gap throughout the DevOps industry to the increased adoption of — and interest in — codeless test automation, the practice (and its subsequent technologies) weren't created to fill that hole.
Rather, codeless test automation has risen to fame in an effort to take DevOps to the next level. While DevOps has been around for more than a decade, DevOps maturation has slowed over the last few years. Advances in Continuous Delivery (CD), Continuous Integration (CI) and Continuous Testing (CT) have come nearly to a halt, as development teams struggle to find new, innovative ways to speed up the software delivery lifecycle (SDLC) in the face of increased demand. What's more, with more apps, features, iterations, users, and ultimately quality assurance activities, to tend to than ever before teams are under pressure. Codeless test automation relieves development teams of the time-extensive responsibility of coding — giving them their time back to focus on greater advancements for their business and the industry as a whole.
Who benefits from codeless test automation?
At the end of the day, not all testers are programmers — or even know how to code. Business testers and manual testers are often stuck at a standstill due to the variety of testing frameworks based on their lack, or very limited knowledge, of coding and the many languages that are used today.
Even developers who have a coding background are using codeless test automation. According to recent research from the Apps Association, there's a major need for professionals in the DevOps space with nearly a quarter of a million job openings listed within the industry. While organizations remain in high-demand to fill these roles, developers are bearing more of the brunt, taking on more testing and quality assurance (QA) responsibilities that were typically outside their realm of work. Codeless test automation, however, makes it easier for them to execute their tests quickly, freeing their time up.
Which tests should I use codeless test automation for?
It's important to note that codeless test automation will never completely replace all manual testing. There are always going to be some tests that need the "human touch," or to be monitored much more closely. Typically, this includes tests that have third party dependencies and complex prerequisites from a setup perspective.
However, there are several types of tests that can — and should — be operating codeless. For example, manual tests that are either hard to implement or require greater in-house skills should be the first that make the cross-over, in addition to "flaky" tests that continuously lead to inconsistent results (e.g. pass and fail for the same configuration or result in false-negatives). Typically, a lot of these "flaky" tests are those that look at web pop-ups for unconfigured image elements or the effects of mobile behaviors, such as certain devices being blocked by certain applications.
At the end of the day, organizations must recognize that they will have a combination of code and codeless tests that need to work together. The best approach is to exclude the tests that will operate codeless from the actual code itself, apply the codeless test and then bring it back into the sequence.
What do I need to be able to implement codeless test automation?
In terms of skills, codeless testers don't need to know how to code — but they do need a high-level understanding of testing, as well as deep insight into the product they're testing, its business objectives and pain points.
Additionally, businesses should recognize that codeless test automation cannot exist alone. Just as with any code-based testing environment, the test itself requires a scalable, always-on and available quality lab. The platform should also support testing on all of the devices you may need to assess, including different mobile phones, operating systems, web browsers, tablets and more. Beyond the lab, there's also the need for analysis capabilities that can provide a comprehensive overview of the quality as well as risks areas on the spot to help identify and triage issues early-on.
What's next for codeless test automation?
Codeless test automation is still relatively new to the industry and has a lot of maturing to do. With any emerging technology, there is much to be learned from best practices to key pain points and everything in between. When it comes to artificial intelligence (AI), there's a lot of room for growth. At this time, the deep learning that is needed to really give codeless the legs to take over all aspects of the testing process isn't quite there, and likely won't be for the next few years on web devices — and even longer for mobile.
In the meantime, codeless test automation can significantly cut down on the time and resources put into monotonous tests that eat away at developers and testers time. It gives them the opportunity to be much more productive than they are today — and more invested in the DevOps cycle. With codeless test automation, testing teams have a renewed opportunity to shine.
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