Test automation promises increased testing velocity, improved test coverage, and enhanced software quality. Yet many organizations struggle to realize these intended benefits. Common test automation pitfalls turn this vital accelerator into a burden sapping precious tester time and energy.
In my years working across various test automation initiatives, I have witnessed these predictable obstacles routinely hampering efforts. By calling attention to the most prevalent challenges, testers can proactively employ mitigation strategies to avoid or overcome them.
Failing to Define a Test Automation Strategy
The enthusiasm over test automation capabilities often obscures the essential groundwork. Well-intentioned testers anxiously plunge into tools without clearly defining the intended purpose, scope, and governance. This lack of strategic alignment dooms the initiative as disjointed efforts working at cross purposes.
Defining a formal test automation strategy upfront aligns stakeholders on the primary drivers and goals. Is the priority accelerating regression testing, expanding test coverage, or enabling continuous testing? What testing levels and types provide the greatest ROI for automation? What factors determine which tests get automated?
Documenting the automation strategy plots the course accounting for current state capabilities and constraints. It orients test automation decisions around delivering the highest business value rather than chasing tool proficiency. Reviewing this guiding strategy as changes emerge keeps automation efforts targeting the most impactful areas.
Selecting the Wrong Tests for Automation
With limited time and resources, not every test merits automation. Determining automation suitability based on arbitrary factors wastes precious efforts. Common missteps include only automating happy paths or choosing the easiest tests to code.
Align test case selection with the defined automation strategy and ROI. Automating complex tests delivering deep insight plus tedious repetitive checks maximizes testing efficiency. Ensure a risk-based mindset governs what gets automated rather than robotic test conversion alone.
Clearly document guidelines and thoughtfully evaluate each test against criteria during triage. Regularly reviewing automated checks against usage and value flags obsolete and low ROI tests for retirement. Ongoing governance prevents test bloat obstructing automation productivity over time.
Poor Framework Foundation
Test automation requires much more than capturing a series of browser interactions. The underlying architecture enabling desired test capabilities largely determines the framework’s maintainability, flexibility, and scalability.
Attempting to shortcut or overlook the framework foundation invites long-term drag on test creation and upkeep. What begins as quick test recordings eventually bogs down under test maintenance costs. Brittle and flaky tests sap productivity rather than fueling it.
Invest upfront in a resilient, modular framework tailored to project needs. Define desired aspects like test parallelization, cross-browser support, custom reporting, data interfaces, and object recognition strategies. Architect with future test volume, complexity, and team growth in mind.
Leverage existing open source frameworks to avoid reinventing the wheel. Build upon proven test automation foundations saving significant design and testing costs. Prioritize framework robustness over expedited test case output.
Insufficient Collaboration
Test automation intersects multiple teams including developers, IT operations, business analysts, and manual testers. Disconnected efforts minimizes collective insight into optimal testing solutions. Silos emergence encourages finger pointing when issues arise.
Promote active collaboration across groups through reviews, design sessions, and regular exchanges. Foster positive accountability where all technology teams own quality and testing success. This unifies commitment to the automation framework’s capabilities and reliability.
Developers offer automation coding expertise and best hook points for test access. Operations provides environments, test data, and pipeline connections. Business partners define scenarios and expected outcomes. Manual testing informs real-world usage context. Combined perspectives vastly improve automation coverage and stability.
Skills Shortfalls
Test automation demands specialized skills from understanding frameworks to writing validation checks. Expecting manual testers to inherently possess these competencies creates unhealthy tensions when testing needs outpaces abilities. The learning curve also slows test creation progress.
Be realistic about required automation skills and close gaps through mentoring, training, and potentially new hires. Foster an open culture encouraging people to acknowledge what they don’t know. Equip those eager to expand capabilities through hands-on education.
Define testing roles leaning into individual strengths for manual testing, test automation, framework development, and coding. Growinginternal talent through continuous skills development ensures testing keeps pace with technology advances.
Neglecting Test Maintenance
The bulk of test automation effort gets spent on maintaining existing test cases rather than authoring new ones. Neglecting the refactoring, enhancing, and safeguarding of checks causes automation decay. Test reliability plummets as frameworks drift while test coverage and utility declines.
Build test care and feeding into team standards that are measured and rewarded. Budget time for scheduled test set reviews, framework upgrades, and documentation of changes. Monitor test metrics like pass rates, run frequency, and detection effectiveness to flag aging.
Automate maintenance workflows as much as possible through test case parameterization, dynamic object mapping, and code modularity. Proactively refresh tests aligning to latest UI changes and functionality. View test rot as technical debt needing vigilant prevention and remediation.
Lack of Measurement
Absent tangible tracking, it becomes impossible to evaluate test automation’s ROI or evolving impact. Loose test case counts omit critical quality details like runtime, pass rate, and defects found. Vanity metrics encourage misguided team perceptions about progress and value.
Institute test reporting dashboards and analytics that reveal meaningful test performance. Track test design, development, execution, and maintenance efforts separate from manual testing. Monitor tests finding defects, flakiness trends, and age. Establish objective automation metrics upfront and routinely evaluate.
Ongoing measurement fuels data-driven decisions about test additions, removals, and framework improvements. It spotlights automation shortcomings needing attention while demonstrating tangible value to stakeholders. Simply put, what doesn’t get measured in test automation doesn’t get improved.
Conclusion
The allure of test automation is potent but realizing its potential requires avoiding these common pitfalls. Mitigate risk through smart test selection, robust framework design, skill building, and rigorous maintenance workflows. Measure impact to drive optimization. Purposeful adoption rooted in a strategic vision for automation pays compounding dividends over time as tests seamlessly accelerate release velocity through enhanced quality and confidence.
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