'Let It Fail' - Strengthening Software Through Calculated Test Failures

In the ever-evolving landscape of software development, testing remains a key component of success and operational longevity, especially with automation. I am lifting the stone on my personal philosophy, the unconventional yet valuable approach of allowing automated tests to fail, and how such failures can ultimately lead to stronger, more reliable software.

Expanding the Horizon: Lean into Combinatorial Testing and Find Bugs at the Outer Boundaries

Test automation is commonly associated with software stability and reliability, but its true potential lies in combinatorial testing. By pushing the boundaries through repetitive automated scenarios, we can expose hidden issues, ensuring the software not only meets expectations but also withstands adverse conditions. This combinatorial testing, executed through varied arrays and payload configurations, is pivotal in fortifying software resilience. Automation doesn't need to babysit the 'happy path.' Use automation to explore all remotely possible configurations and entry limits, challenging the software under various scenarios. It's as simple as utilizing a broad spectrum of test data to probe every possible configuration and condition. By doing so, we ensure that the software is not just functional but also resilient and capable of handling unexpected and divergent situations.

Finding Strength in Failure: The Unseen Benefits of Test Breakage

Letting automated tests fail may seem antithetical to the aim of testing, we all like to see those green checkmarks. However, never-failing tests may indicate a cushioned environment that is failing to challenge the software sufficiently. A fitting role for automation is to function as a stress test, thoroughly evaluating the software's strength and efficiency at all points of contact, and not shying away from revealing its vulnerabilities. These failures direct our focus towards necessary refinements, ultimately strengthening the software's core. The philosophy of `let it fail` goes beyond just accepting failures; it's about understanding their inherent value. Automated tests that fail due to unexpected design changes, text alterations, bugs in conditional rendering, or unintended API changes provide crucial insights. These failures act as indicators, pointing out areas where the software is not aligned with its intended design or usage expectations. Embracing these failures allows us to adapt quickly to changes and fix issues that might not have been evident initially, thereby enhancing the software's reliability and user experience.

But it Passes... Avoiding the Trap of Over-Stabilized Testing Environments

Creating an overly stable test environment with custom, non-representative user elements can lead to an illusion of stability. Automation is best utilized when it mirrors real user behaviors in all of their unpredictable glory, what they look for, what they click on, and what they expect to happen. Some popular testing frameworks recommend the usage of custom HTML attributes to be used as selectors for hard-to-reach elements – yes, I'm looking at you, popular framework Cypress – but by doing so, we may inadvertently build a facade of stability that fails to challenge the software in meaningful ways, and may even leave gaps where identifying inconsistencies in front-end structure may have been beneficial. This artificial stability can mean that bugs remain hidden, only to be discovered by chance at the hands of an adventurous manual tester, negating the usefulness of the automated test and leaving automation engineers questioning their existence.

Embracing the concept of 'let it fail' in automated testing sets a higher standard for software quality, context, and real world knowledge of the feature under test. It's not about accepting lower automation stability but striving for excellence by learning from our automated tests' failures. Continuing to push the boundaries of expectation, understanding and utilizing these failures as learning opportunities is crucial for the advancement of development and testing methodologies and the creation of software that truly meets the demands of its users.