With continuous testing gaining momentum across enterprises, many teams debate shifting existing manual testing efforts to automated approaches. However, prudent quality assurance strategies utilize both human-driven manual testing and scripted test automation in a balanced manner based on context. Let’s examine the unique strengths of manual testing vs. automation testing, along with recommendations on optimal scenarios to drive test strategy decisions.
When Manual Testing works the best
Exploratory Testing: For validating new features, undefined edge cases, and unfolding complex scenarios, innate human intuition, judgment, and creativity still often help generate varied test ideas that go beyond what automation alone could cover, constrained to pre-scripted known test cases.
Usability Testing: Direct, organic user feedback on human-centric elements like UI design, navigation flows, interaction patterns, and UX remains far more insightful than strictly simulated, scripted interactions exercised via automation.
Edge Cases: Human testers frequently demonstrate greater skill in creatively adapting processes to handle unplanned scenarios and generate relevant edge cases that automation would likely overlook without explicit supplemental logic coded to handle such gaps proactively.
New Project Kick-offs: Manual testing still retains merit during the initial exploratory phases of greenfield applications to pragmatically help testing staff rapidly gain familiarity with new projects without the larger upfront investments warranted in automation at the early stages.
When Automation Delivers the Best Results
Regression Testing: Automating repetitive validation of multi-step workflows, front-to-back transaction flows, and boundary use cases across releases delivers exponentially cheaper and more reliable regression capabilities long-term at scale versus purely manual repetitive testing.
Load Testing: High-volume scripted performance tests can reliably execute under the sustained intensity of load simulations far beyond human capabilities to manually develop and execute sufficient test data volume promptly.
Schedule Triggers: Automated test suites resiliently handle not only high-intensity execution loads but also wide variability in execution scheduling constraints, spanning overnight test runs, weekend simulations, and recurring test jobs, compared to manual scheduling limitations.
Fast Execution: Once implemented, automation intrinsically vastly accelerates executing the high-volume, high-velocity test iterations essentially unattainable via singularly manual testing techniques.
Reusability: A yet underappreciated aspect, once baseline test scripts are validated across supported versions and configurations, ongoing reuse and derivation of automated assets across application generations maximizes useful lifespan, helping
broadly amortize upfront investments over time.
Balancing Approaches
Project Lifecycle Stage: Manual testing suits new app exploration; automation helps optimize mature apps.
Application Type: Transactional systems benefit automation more than exploratory interfaces like BI tools.
Testing Types: While automation handles repetitive validation well, usability needs human insight.
Team Expertise: Apps with technical test staff may adopt automation faster than less technical products.
Pace of Change: Frequently evolving applications present maintenance overhead for automation.
Test automation with Opkey
Opkey is a test builder that offers a one-click test creation feature, allowing users to increase test coverage without requiring a software developer. Its drag-and-drop interface allows employees to create complex tests without writing code. Proactive notifications about test changes are provided before they are pushed into production. Opkey’s self-healing scripts ensure test stability.
In conclusion
Prioritize testing based on factors like stage, project variety, pace of change, and team capability. The ERP testing tools like Opkey make automation more user-friendly, which helps tip the scale towards scripted testing agility even for fewer technical teams to maximize quality.