If a job is worth doing, it’s worth doing well, unless it’s automation. This seems to be the motto for many software development projects. And why not? After all, it’s only testing. Just get the team to throw up some automated scripts, and that’ll do. It’s better than nothing.
Is it though? Is flaky automation better than no automation at all? Does it help accelerate projects and reduce timelines, or does it end up causing more problems than it solves?
And are the questions moot when, with modern AI-powered tools, there’s no excuse for flaky tests?
What Are Flaky Tests?
Flaky tests are temperamental beasts with minds of their own and a deep fear of conformity. They pass or fail inconsistently—seemingly without any change to the underlying code—if they even make it through a complete execution.
As the kids might say, these tests are easily triggered and are particularly susceptible to slight environmental inconsistencies, minor response time delays, and poorly planned test dependencies.
Generally, they’re caused by poor design, too much internal logic, outdated tools and a lack of adequate planning.
The Problem with Flaky Tests
Testing isn’t a glamorous role, but it’s essential. It’s the Makelele, Rodri, or N’Golo Kante of the SDLC. The rock-solid core that cuts out defects before they become issues. Or at least it should be.
Flaky automated tests undermine the whole premise. You can’t trust the results, you get false positives, ignored failures, and—if there’s no manual backup testing—allow real bugs to slip through.
They wasted time and resources, as teams investigate false failures or rerun tests unnecessarily. This, in turn, affects team morale, slows down delivery, and tarnishes testing’s reputation.
Are Flaky Tests Better Than No Tests?
Rather than being better than no tests, Flaky tests are actually worse. They create noise, waste time, and undermine confidence in automation.
Reliable tests are essential for maintaining software quality and enabling confident go-lives. Without them, what’s the point of testing?
Yes, in rare cases, flaky tests may reveal intermittent bugs, but more often, they obscure rather than clarify.
Why There’s No Excuse for Flaky Tests Today
Here’s the confusing thing about this whole dilemma: there is no longer any excuse for flaky tests.
Modern automation tools make it easy to create and maintain solid, resilient tests. With AI-based object recognition and natural language scripting reducing test creation and maintenance effort, and minimising flakiness.
Plus, you have automated detection and maintenance features that enable teams to quickly identify and fix any problems that AI misses.
How OpenText’s AI-Powered Testing Suite Solves Flakiness
The OpenText Functional Testing solutions—specifically the appropriately named OpenText Functional Testing—provide AI-driven automation that simplifies test creation, boosts coverage, and increases test resiliency.
- This includes natural language processing, which enables easy, codeless test authoring, making tests less prone to errors and easier to maintain.
- The inbuilt AI functionality provided by OpenText DevOps Aviator enables you to generate manual tests from video, then convert them to automated tests.
- There’s also AI object detection and advanced maintenance tools that help ensure tests remain reliable, even as applications evolve.
- Plus, you get access to cross-platform testing capabilities, which further reduce the risk of environmental flakiness.
Conclusion
Flaky automation tests are worse than having no automation at all. They are a liability, not an asset.
However, the current generation of AI-powered tools, such as OpenText Functional Testing, means you don’t have to put up with flakiness. It’s easier than ever to create solid tests that accelerate your projects and reduce business risk!
