Formed in 2009, the Archive Team (not to be confused with the archive.org Archive-It Team) is a rogue archivist collective dedicated to saving copies of rapidly dying or deleted websites for the sake of history and digital heritage. The group is 100% composed of volunteers and interested parties, and has expanded into a large amount of related projects for saving online and digital history.
The DevOps world has quietly turned its focus to solving an essential challenge: enabling software teams to innovate quickly while meeting high customer expectations for quality. In other words, to build useful things faster with fewer mistakes. This tension has been growing for years, but 2020 added the challenges of remote work and accelerated digital transformation to the continued disruption brought about by cloud, SaaS and DevOps. In 2021, we need a road map for taking test automation to the next level with quality engineering, a discipline that incorporates best practices and data-driven testing into the end-to-end customer experience and drives organizational growth.
Rethinking the Quality Process for the DevOps Era
Quality engineering (QE) has traditionally lacked the tools needed to keep pace with digital transformation. Many QE teams struggle with complex, brittle automation frameworks and slow manual testing which create serious bottlenecks to DevOps adoption. While development accelerates, QE is left with disparate or outdated workflows and toolsets.
Rising to the challenges and opportunities presented by DevOps and digital transformation will require innovation in our approach to quality. More than ever, we need to shift our focus away from quality assurance as a task that you perform late in the software development life cycle (SDLC) in favor of quality engineering practices throughout the entire life cycle. It starts with broad, effective test coverage – beginning when your developer is working on a local branch and continuing until a high-quality customer experience is confirmed in production across the entire surface area of the application – web, API, mobile, email, PDF or otherwise. It also goes deep; you evaluate all aspects of quality, ensuring that you satisfy requirements related to functional correctness, accessibility, performance, user experience and more.
Low-Code Test Automation Unlocks a Culture of Quality
With low-code, genuinely effective testing is at the fingertips of every role, from manual testers to developers, automation engineers, product owners and customer support. Requiring all of these roles to develop specialized programming skills is impractical, so low-code tools serve to democratize quality engineering by enabling everyone to participate in authoring tests, updating tests, and gaining insight from test results.
Low-code testing brings several advantages to quality engineering, particularly in the transition from manual testing to automated testing. While traditionally this process would create major disruptions, low-code platforms are smoothing the way. In their IT Automation predictions for 2021, Gartner expects that by 2024, improvements in automation capabilities will refocus 30% of IT operations efforts from support to continuous engineering. For manual testing teams, that shift would likely trigger talent changes and a long process of pilot projects, retraining, and gradual rollouts. Low-code is key to managing this shift, upskilling workers and ensuring quality throughout.
Modern Automation Solutions Embrace Rapid Change
A key challenge with traditional test automation tools is that they were designed for applications that didn’t change frequently and were intended only to validate code. They relied on static selectors to identify page elements. If the selector (say, an ID) changed or objects (the XPath) moved on your webpage, then your tests failed. As more enterprises accelerated development via DevOps, Agile and CI/CD, the burden of test maintenance resulted in the same bottlenecks as manual testing.
2020 was a breakout year for low-code test automation. New, easy-to-use solutions surpassed the capabilities of legacy frameworks that have dominated the sector. These solutions incorporate machine learning, data analytics and other advanced technologies to greatly reduce the burden of test maintenance and overcome the test rigidity challenges of legacy frameworks.
With AI and machine learning, test automation solutions are trained by a tester simply navigating their product. As the tester moves through common customer journeys, the solution builds an understanding of each element and its context so that if an element moves or a property changes, tests containing that element are updated without human intervention. This drastically reduces the amount of maintenance required to ensure your tests are current. When tests do need to be updated, low-code models make it easy for anyone to jump in and make the updates. Looking ahead, auto-healing and low-code editing are crucial to supporting quality engineering in high-velocity teams.
Testing the Entire Customer Experience
Traditional pass/fail validation stops short of offering real insight into the user journey, a critical step effective quality engineering. The next generation of test automation platforms expands focus from validating code to validating the entire user experience. This starts with broadening testing to cover non-functional requirements, such as application performance, accessibility, and user experience. For example, identifying trends in load time for key pages and monitoring visual changes are done autonomously and essential to managing the customer experience. From there, you can prioritize quality efforts toward the components of your application that are most heavily used or highest risk. This enables you to make data-driven decisions about test coverage — focusing your testing efforts on high-priority pages like the checkout page for an e-commerce site, or high-risk pages such as those with multiple interactive elements that are linked from other pages, such as signup forms.
But even a fully data-driven testing strategy that only focuses on the app or website UI is unlikely to cover the full end-to-end user journey, resulting in test coverage gaps and potential pain points for customers. For example, a common user journey may include opening an email, clicking on a link, checking a web site, and downloading a PDF. Whereas the limitations of legacy tools relegates testing to the web portion of that journey, modern solutions allow you to validate the entire user or customer experience (CX): receiving and opening an email, clicking on the link, logging into the web site, downloading the PDF and verifying its content. It’s even possible to confirm values in the backend via API – all without writing a line of code. Developing the tools to seamlessly monitor, repair, and manage the expanded CX is central to our innovation and to our customers’ success.
Quality Engineering as User-Centric as You
Quality is no longer an afterthought or just a box to check before deployment; it’s an essential part of the user experience, and therefore an essential part of maintaining a competitive advantage in every industry that uses software to serve customers. Test automation is critical for high-velocity teams racing to innovate faster, shift to DevOps, and build quality products while working remotely. Thankfully, a growing number of quality assurance teams are getting a seat at the table as DevOps is implemented, elevating the profile of quality as a strategy and growing demand for test automation solutions that can keep pace with the demands of DevOps.
In response to this demand, a new generation of intelligent test automation solutions is enabling teams to rise to the challenge by embracing low-code and machine learning to maintain quality. To build a culture of quality engineering in this environment, your team needs test automation solutions that are as user-centric as you are: solutions that provide coverage across the entire user journey. Solutions that not only verify functional correctness, but provide rich insight into all aspects of quality and enable continuous improvement. Perhaps most importantly, you need solutions that enable everyone on the team to participate in quality. This ensures that the entire SDLC actively participates in building user-friendly products that continue to set the standard for quality at the speed of DevOps.
