Validate or Verify: What Should Your Tests Actually Be Doing?

An overlooked challenge in updating your software testing strategy is simply understanding how effective existing testing is, making it hard to troubleshoot gaps or outdated practices. Understanding the distinctions between testing for validation and testing for verification can help your team build confidence and optimize software testing.

Validation and Verification: A Quick Intro 

Developers commonly divide software testing philosophies into a couple of major areas. Yes, there are more than just two families in the taxonomy of software testing strategies, but these essential classifications offer a tried-and-true starting point. 

Verification testing gauges whether you've built a product properly: Does the software perform as expected? Will an underlying algorithm produce the correct output when tested against a rigorous method or model?

Validation testing evaluates whether the product is the correct solution for the task: Does the software meet the user's demands? Does it satisfy any written deliverable or SLA (service level agreement) requirements, like working seamlessly in all target environments?

Validation and verification can overlap, which makes the difference a bit more confusing. For instance, an SLA that describes a project or problem in broad terms may also feature fine-grained specifications you need to meet. In some cases, an end user's goal or compliance standard might necessitate a rigorous verification test on top of your validation efforts. Even more confoundingly, the two types of testing commonly occur in tandem – making it inherently tricky to unravel the threads. 

How can you cut to the heart of the mess? As with most meaningful tasks, breaking the problem down goes quite a long way. Automated functional testing is one of the most impactful divide-and-conquer DevOps tactics. 

The Fundamentals of Functional Testing Automation

Functional testing entails evaluating distinct functionalities of an app or piece of software – not the whole product or the discrete parts that power said functionalities. For instance, if you built a shopping app to a client's specifications, you might have a QA tester confirm that they could take major actions like logging in, saving their cart, or opening a support ticket. 

Remember that functional testing is not the same as verification methods like unit testing. Unit testing involves evaluating individual functions or methods in your codebase without tying them to some broader purpose.

What Makes Functional Testing Strategies Worthwhile?

By testing functionalities independently, you make it far easier to debug problems faster. When something goes sideways, you don't have to spend (waste) as much time hunting for the answer. The very structure of your testing framework acts as a roadmap highlighting which aspects of the product aren't up to par. 

Another way to think about functional testing is as a validation black box. You give your software a broad stimulus, like a new login session, and you confirm it outputs the right results – without delving into the particulars of how the job actually unfolds. 

How Automation Comes Into Play

Automation is the obvious next step for those seeking ultimate manageability: when you're dealing with lots of moving parts, it's easy for things to get lost along the way, particularly when high-volume development cycles come into play. Setting up pipelines that do as much as possible grants you more breathing room.

Effective test automation takes the tedium out of tasks like running tests in response to myriad development lifecycle events. It can take apps through real user journeys and generate new version releases to confirm they build the proper artifacts. Automated software testing eliminates repetitive, time-consuming work to make your testing practices more efficient and rewarding. 

Taking an automated, big-picture approach goes beyond optimizing time spent – or giving your stressed-out dev team some much-needed relief. It has proven ROI benefits, including earlier error detection, enhanced user satisfaction, and reduced testing expense. 

As we've said before, testing is a continuous process that never truly ends as long as your software has active users. It only makes sense to streamline the task by delegating as much legwork as possible.

Putting Intelligent Test Automation to Work 

Functional testing automation isn't always easy, particularly when you try to implement it like you'd tackle manual testing. Although this would seem to defeat the purpose, it's a pretty common blunder: well-meaning enterprises routinely set up functional testing frameworks that are only automated in name, requiring significant human intervention to start cycles, confirm results, and debug problems.

While you'll never truly eradicate all human touchpoints from your continuous testing lifecycle, there are definitely steps you can take to offload the heavy lifting. Here are five to get you moving:

Architect your validation practices around an end-to-end testing philosophy: End-to-end testing confirms your software works from start to finish, whether that entails following a user journey to its logical conclusion or confirming that the app interfaces with third-party tools correctly. Designing tests with a comprehensive outlook fosters a more fluid overall experience and a more cohesive finished product. It also clues you in on how automation might benefit you most by making it easier to observe bottlenecks in your testing process. 

• Use autohealing testing frameworks: Your applications will evolve – It's a fact of life. Your tests, however, shouldn't become obsolete as a result. Machine learning makes it possible to create tests that remain relevant even as UI elements, layouts, design systems, and entire reactive frameworks change. Why spend all that time rewriting tests every time you need to tweak something?
• Automate your regression testing: Although this applies to non-functional as well as functional testing, it's an essential corollary to the previous rule. It's hard to overstate the value of ensuring things still work following changes – or the very real risks of forgetting to rerun tests manually after pushing new code. If you'd rather catch errors before they make it to production and spark off user complaints, then you'll use a CI pipeline that's smart enough to know when tests need rerunning without repeatedly being told.
• Stop writing more test code than actual code: We get it, you love coding, but you can only do so much as a mere mortal. Find a tool that automates your browser, mobile web, API, and UX tests from a single dashboard so that you can devote more of your finger-bending effort to solving real client problems.
• Unify your software testing practices: You shouldn't have to redesign your tests for each end-user platform you want to target. Cross-browser testing lets you create a test and run it anywhere, resulting in more consistent behaviors and more actionable feedback.

Intelligent software testing is about ensuring you've built the infrastructure to test systems and functionalities accurately under diverse circumstances and exacting time constraints. Adopting a holistic approach that lets you plan, refine, and automate your tests from one central focal point can make you a more insightful developer – and empower your team to create better-received software.