4 Test Automation Limitations to Overcome

The DevOps concept sparked a revolution in software engineering, and for good reason. Faster releases, improved collaboration and better knowledge sharing — what’s not to love?

Ask a tester. With more devices, customer channels, personas and markets come more areas to test. Test automation can work at speed, but not breadth, as it is limited to the reliable data you have on hand and the stability of your automated script repository. The resources and effort required to stand up test automation, let alone maintain it over the long haul, leave blind spots at best and poor coverage at worst. In some ways, test automation is even antithetical to DevOps; while it promotes speed, it often leads to knowledge gaps, technical debt and less human collaboration and ingenuity from the tester perspective.

Let’s explain the limitations of test automation in DevOps organizations, and how it can leave some problematic — and costly — digital quality blind spots. We’ll also get into the importance of prioritizing both speed and quality without sacrificing one for the other, which happens all too often, as well as the often cumbersome costs associated with test automation.

Test automation isn’t enough

Many DevOps proponents are pro-test automation. Their thinking promotes the panacea that automation and engineering combined equal quality. It’s not this simple, as much as we’d like to believe it is. While test automation certainly has its uses, the modern approach is undermined by its limitations.

Let’s put DevOps within the lens of test automation, which must establish these three objectives to work in the real world:

• Establish a robust and scalable automation framework
• Foster communication between engineering, QA and product teams
• Implement automation within the sprint cycle for timely testing and feedback.

The goal is to automatically execute tests as you design the software in a fast and cohesive way. The notion of DevOps is to ease both engineering and delivery through improved collaboration and removing barriers.

The logic makes sense, but the practical strains of software engineering, strategic differences between departments and limitations of test automation itself begin to manifest in several problematic ways. Here are four common challenges for test automation in DevOps — and how crowdsourced testing likely offers a better solution.

1. Communication starts to degrade. Collaboration is one of the key pieces to test automation success mentioned above. On the surface, it seems easy enough, but the best of intentions and a fancy AI-enabled tool can’t always overcome the significant cultural, strategic and expertise differences between dev, QA and product teams.

The communication piece is the first of the three key test automation characteristics to degrade in DevOps organizations. It’s difficult enough to establish an internal dialogue that internal teams all find useful, but then throw offshore teams into the equation, and it’s often a recipe for confusion that can lead to flaky test scripts, which might work once but never again.

2. Speed creates friction for quality (and vice versa). When it comes time to accelerate, manual testing is seen as an impediment to speed, even if it’s known to be a highly valuable characteristic for quality. Here’s where we begin to see the friction between speed and quality, and automation emerge as an option to address it.

Applications might also lack certain details that can aid testers in their work, such as incomplete requirements, poorly written user stories or lack of access to certain environments. Ensuring the team has proper access to these resources also requires time and open communication — as we’ve established, these can sometimes be in short supply. Lack of code knowledge or any other automation skill gaps on the QA side also introduces friction between speed and quality. It’s not uncommon to see siloed knowledge as it pertains to test automation, which creates bottlenecks in the thing that is supposed to alleviate them.

3. Automation environments paint a partial picture. Teams execute in-sprint automated test cases through open source tools like Cucumber against the dev and QA environments in isolation, which can’t fully account for how the product will work in the hands of real users. So tests might achieve reliable results on these environments, but ultimately fail in real-world settings, establishing a false sense of confidence in the release.

This problem extends to production environments too. The team might turn to costly emulators and device farms to run their apps, but these offer several shortcomings. First, a large number of devices is great, but it’s only as good as the amount of data you can throw at it — if you have five logins, you can only run five tests in parallel. Second, even the best device farm providers are limited in what they can provide to a given customer at a given time, and not all of those devices will be able to support automation.

4. Lack of data exerts pressure. Test engineers write automation scripts based on existing data sets. Over time, the application changes, the features change and the requirements change, but the scripts stay the same, relying on the same old data. While these scripts will still validate the basic functionality, they fail to go beyond the happy path — and the happy path grows narrower over time as the automation fails to account for additional edge cases as the product matures. Remember, the chaos of diversity in a product being used in real-world scenarios, including different devices, browsers, OSes, geographies, networks and more, creates hundreds of thousands of different user scenarios. That’s a lot of room for things to go wrong at the edge.

The organization can invest in test data management to address this problem, using it to analyze production databases and supplying synthetic data to bolster the automation. But this is a time-consuming and expensive process, as it requires investment in additional staff and resources to maintain it. On top of that, companies in regulated industries, like life sciences or financial services, run the risk of compliance issues when they use synthetic data. Likewise, test automation augmented with synthetic data might run afoul of data protection laws and policies, which vary market to market and change over time.

The power and adaptability of the crowd

Test automation and device farms close some of the holes in the enormous fish net, but leave ample opportunity for defects to leak through, especially when you pan out to consider the unique user experiences that come with accessibility, localization, customer journeys and more. The million-dollar bug could be anywhere. That’s why it’s important to achieve the best test coverage possible on a growing matrix of real-world usage scenarios, not just to move quickly through the easily automatable pathways. The goal is speed and quality, not just speed.

The flexibility and boundless nature of exploratory testing provides more value than automation ever could. Achieving high-quality exploratory testing at DevOps speed and enterprise scale means being deliberate and purposeful with your strategy. For the vast majority of businesses, it’s neither feasible to scale internal testing resources nor possible to recruit, maintain and operate a global base of crowdtesters to achieve the results you need.

This is where Applause comes in. With a global network of more than one million digital experts, we help businesses across a variety of industries, including B2B technology, media and telecommunications, retail and more, to achieve their vast and nuanced digital quality goals. Coordinating strategic crowdtesting efforts in accordance with test automation can help attain the speed and quality enterprise-grade digital products require to thrive in the marketplace.

Here’s how we fill gaps in the areas mentioned above:

Communication. Applause compiles a team for you that includes a delivery manager, test architect, test engineer and test team lead to coordinate testing efforts. All testing results are thoroughly documented, including through images and videos of defects if needed, and uploaded into your preferred bug tracking systems.

Speed. Testers typically start to find defects within the first 24-48 hours, helping uncover defects early in the process to enable fast remediation. Applause fits into your SDLC wherever you need us, whether it’s early testing on a prototype or ongoing testing and feedback on a production application. With our approach, we cut setup time from months to weeks, standing up the infrastructure faster and with no need for internal maintenance. We execute whenever you need us, around the clock, in different time zones, weekends, anytime.

Environments and devices. We don’t fake it. Applause puts your prototypes, products or apps into the hands of real customers in real scenarios all around the world. You determine the demographics and situations for testing, and we source testers for the task. Whether you need testing along a country border, new accounts or specific personas, such as people with disabilities, we’re ready to get started today. And there’s no need to worry about device sprawl because our testers’ device portfolios evolve as new products release to the market.

Data. There’s no need to simulate data or guess whether the data is up to date. Rather than trust automation to execute on potentially iffy data, our customers execute tests in their actual environments. Our solutions, including our User Experience Testing and Accessibility Testing solutions, scale as needed for organizations looking to go the extra mile for their customers.

For DevOps organizations who would prefer to exclusively invest in test automation over manual testing, here’s a dirty secret: many third-party vendors give their automation a manual boost when it breaks anyway. As mentioned above, test automation is dependable when it relies on a robust framework, strong communication and fits within your SDLC for timely feedback. In these ways, test automation augments manual testing efforts — and these are the elements we bring to our own Automated Functional Testing practice, which can spin up with a six-week pilot program. Used properly, test automation is a sound investment, especially when complemented by robust manual testing that covers the gaps and edges.

The difference between test automation vendors and a digital quality partner like Applause is the depth and value we can provide. You’ll hit break even faster, typically in just a few test cycles. In fact, a recent IDC report found that our customers achieve average benefits of $3.79 million yearly per organization, while also accelerating test cycles by 36%.

Tell us about your unique digital quality goals, and let’s discuss how we can help you achieve them with ease, scale and speed.