Test Automation: Finding the right balance between Shift-Left and Shift-Right
Test automation improves reliability and speeds up development. In theory. In practice, not everything can be automated. Some tests cost more to maintain than to run manually. Others become obsolete with the slightest change.
The goal isn’t to automate everything at all costs, but to do it wisely. Testing early to prevent errors, monitoring in production to adjust continuously. It’s the balance between shift-left and shift-right that makes automation truly effective.
Which tests should be automated? Where should the limit be set? How can you avoid unnecessary complexity? That’s what we’ll explore.
1. Automating, but Not at Any Cost
Test automation has its advantages, but it also comes with a cost. Automating everything isn’t practical or necessary. Some tests are too volatile, others require human intervention, and poorly designed automation can distort the assessment of software quality.
Some tests change too frequently. Keeping them updated takes more effort than running them manually. Automating a test that needs to be modified every sprint? That’s a waste of time and resources.
Others are too sensitive to environmental variations. Tests relying on unstable data, fluctuating network delays, or constantly evolving interfaces are prone to false failures that don’t indicate real issues.
A script can check if a button works, but not if it’s well-placed or draws attention. UX tests, exploratory testing, and user emotion analysis cannot be automated. They require intuition, analysis, and adaptability—qualities no program can replicate.
A poorly designed test may flag non-existent issues or, worse, miss critical errors. The more automation is used without strategy, the harder these biases become to detect.
Overloading a system with automated tests also increases technical debt. The more tests there are, the harder they become to maintain and validate. Instead of saving time, you end up wasting it.
Automation should be a strategic decision, not a reflex. A well-thought-out approach avoids these pitfalls. Which tests should be prioritized? What structure should be adopted? Let’s dive in.
2. Building an effective strategy
Automating without a clear method leads to an accumulation of unusable tests. To make automation an asset rather than a burden, it’s essential to choose the right tests and structure the process properly.
Not all tests provide the same value. Critical, repetitive, and stable tests benefit the most from automation:
Conversely, UX tests, exploratory testing, and highly specific scenarios should remain manual.
A well-balanced automation strategy relies on three levels of testing:
The earlier a bug is detected, the less costly it is to fix.
Effective automation doesn’t stop at pre-production testing. It must be integrated throughout the entire development cycle:
Testing early prevents issues, while testing in production ensures long-term stability. This balance makes automation truly effective and sustainable.
3. The right tools and best practices for effective test automation
Test automation is more than just running scripts. Without a clear framework, it quickly becomes a burden. Choosing the right tools and applying solid best practices are essential to ensure reliable and maintainable automated tests.
A testing tool must align with the project’s technology, ecosystem, and the team’s expertise. Poor tool selection leads to complex maintenance and reduced efficiency.
Effective automation isn’t about using more tools, it’s about integrating them seamlessly into the development cycle.
Automation is only as effective as the strategy behind it. Without a structured approach, even the most advanced tests become obsolete.
Waiting until the end of a project to automate tests is inefficient. The later a bug is detected, the more expensive it is to fix. The shift-left approach, which involves testing early in the design phase, helps identify issues sooner and improve code stability.
This methodology requires writing tests before coding. It forces developers to design testable and robust functions, reducing the risk of production failures.
By using tools like Cucumber or SpecFlow, this approach enhances collaboration between developers, testers, and business teams through human-readable test scenarios.
Automating tests doesn’t mean running them in bulk without strategy. Tests must be integrated into deployment pipelines to provide quick feedback without slowing down development cycles. Balancing local execution and CI/CD testing improves overall efficiency.
Automated tests should be isolated and reproducible. Relying on dynamic databases, unstable network conditions, or changing environments introduces false failures and complicates debugging.
Automated tests aren’t static. They must evolve with the product. Structured failure reports and regular test analysis help prevent an accumulation of false positives and ensure long-term reliability.
Automation isn’t a silver bullet. Without a well-planned strategy and thoughtful integration, it can become more of a burden than a benefit.
Conclusion
Automating tests doesn’t mean running as many as possible as often as possible. Poorly planned automation can slow down development, distort results, and increase technical debt. On the other hand, a well-structured strategy helps reduce errors, speed up releases, and ensure better stability.
Efficiency comes from balancing shift-left and shift-right. Testing early catches errors before they spread. Monitoring in production enables quick responses to issues that traditional tests might miss. One doesn’t replace the other—their combination is what makes automation truly effective.
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