When a test fails without any visible reason, even though the code runs flawlessly, it’s enough to make any developer sigh in frustration. These so-called “flaky tests” have long plagued the world of software development. Over the years of working with various American technology companies — including projects in healthcare, real estate, and corporate training — Anatolii Husakovskyi, an outstanding Senior QA Automation Engineer, has gained extensive experience addressing the persistent issue of flaky automated tests.
His systematic approach enabled him, in one of his previous projects, to reduce false test failures by 95%, significantly improving productivity and software quality. This remarkable achievement is just one example of how his expertise sets him apart in the field of quality assurance.
Engineering Roots in Aerospace
This story doesn’t start in tech — it begins in an industry where mistakes can cost lives.
Anatolii’s journey to revolutionizing QA is rooted in an unusual combination of academic backgrounds: two master’s degrees in aerospace engineering and software development. His education at the National Aerospace University instilled in him the disciplined approach and precision that are hallmarks of the aviation industry.
“In aerospace, even a microscopic error can have catastrophic consequences,” Husakovskyi explains. “I brought that same mindset into software testing, where precision is just as vital.”
Transitioning from aerospace to IT wasn’t a pivot away from engineering — it was a continuation. After an internship at an international IT services provider and early work in test automation at healthcare technology projects, Anatolii began applying his analytical mindset to the software world.
Diagnosing the Problem
In one of the enterprise-scale U.S. software projects Anatolii joined in 2023, the test suite was crumbling under the weight of inconsistent failures.
“I noticed the team was spending up to 40% of their time triaging false negatives and rerunning tests,” he recalls. “That’s a massive productivity drain.”
Through in-depth analysis, he identified several systemic weaknesses:
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Poor handling of asynchronous operations — tests either waited too long or not long enough.
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Fragile selectors — easily broken by minor UI changes.
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Lack of test data isolation — resulting in unpredictable side effects.
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No unified retry strategy — causing redundant test reruns.
“The tests were being written independently, without a cohesive architecture,” says Husakovskyi. “I mapped the interdependencies and saw how they compounded into a snowball effect.”
The business impact was severe: delayed releases, eroded trust in test results, and unreliable quality signals. Regression testing was taking 40% longer than necessary, forcing the company into an impossible trade-off between speed and confidence.
A Strategic, Incremental Transformation
Instead of scrapping everything and starting over, Anatolii chose a measured, iterative roadmap.
“Revolutions are great, but the business can’t pause while you rebuild,” he notes. “Every phase had to deliver tangible improvements.”
His strategy was grounded in clean code principles, rarely enforced as strictly in test code as in production code. Core initiatives included:
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Building robust abstractions for common operations
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Structuring tests into isolated tiers based on execution frequency
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Addressing the reversed testing pyramid: reducing resource-heavy E2E tests while increasing integration and unit test coverage
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Introducing metrics-driven progress tracking
“The hardest part was shifting the team’s mindset,” he admits. “People treated test code as second-class. I pushed the idea that it needs to be just as clean and maintainable as the app itself.”
His architectural overhaul centered around a modified Page Object Model, tailored for complexity.
“The standard POM works fine for simple apps,” he says. “But I introduced extra layers of abstraction to shield tests from UI volatility.”
For asynchronous behavior, he designed an adaptive waiting system that adjusted to real-world execution patterns rather than relying on hardcoded timeouts.
“My background in modeling complex systems helped here,” he explains. “We created an algorithm that learns from historical test runs and adapts in real time.”
A major breakthrough came in the form of test data isolation.
“Good tests are like scientific experiments — they need controlled, isolated conditions,” says Husakovskyi. “Each test now uses its own sandboxed dataset.”
Measurable Impact on Productivity and Quality
Tight CI/CD integration was key. Tests ran on every commit and during nightly extended suites.
The results were transformative:
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1200 regression tests that previously ran for 90 minutes now finished in 50–55 minutes — even with 40 additional tests added.
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A detailed dashboard tracked execution time, retry rates, and component stability.
“You can’t improve what you don’t measure,” Husakovskyi asserts.
Perhaps the most profound shift was cultural.
“I spent time explaining to developers that flaky tests are a shared responsibility,” he says. “Eventually, engineers began adding test-friendly selectors right in the development phase.”
Concrete results speak volumes:
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Flaky test rate down 95% (from 20–25 failures/day to just 1–2/week)
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Regression test time cut by 30–40%
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Test coverage up 25% with no increase in total execution time
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60% less time spent debugging false positives; 40% more on feature development
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Release cycles shortened from two weeks to 8–10 days
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Production bugs down 35%
“What I’m most proud of is how the team now sees automated testing — not as a chore, but as a strategic advantage,” he says.
Industry Lessons and Broader Impact
Anatolii’s success was built on years of iteration.
“I first truly understood flaky tests at health-focused tech company,” he recalls. “Working on medical apps, where reliability is non-negotiable, shaped my approach. Then I refined it further at Global French quality control and compliance services provider, perfected it at a Canada-based learning technology company, and now continue to implement these practices at a leading US real estate platform.”
“In every project, I saw similar issues — just with different symptoms. That helped me identify the underlying patterns.”
His methods have wide applicability.
“This problem is universal,” he says. “I estimate that flaky tests cost our industry billions in delayed releases and wasted effort.”
“Most teams choose between writing tests fast or making them stable. I believe you can — and should — achieve both.”
Final Thoughts
Anatolii Husakovskyi’s work transcends a single company. He proved that flaky tests are solvable — with a systemic, engineering-driven approach rooted in both rigor and empathy for real-world development workflows.
“I believe the future of test automation lies in integrating AI,” he says. “Smart systems that analyze test patterns and predict instability before it even happens — that’s where we’re headed.”
His results across multiple U.S. projects — from healthcare to real estate — offer a blueprint for QA excellence. By combining aerospace discipline with software ingenuity, Anatolii has shown that even the industry’s most persistent pain points can be overcome — with the right mindset and a refusal to compromise.
