Mobile-app QA automation that shrank a full-device regression from 5 hours to 40 minutes
Mobile banking has to work perfectly on every phone, yet manual QA across dozens of Android and iOS versions was stretching each release to five slow days. In just three months we automated all priority flows with Appium, TestNG, and BrowserStack. A full-device regression now finishes in 40 minutes and powers bi-weekly releases with 95 % coverage.
Background & Challenge
- Device & OS fragmentation — manual testing across dozens of Android 8-13 and iOS 13-17 combinations was slow and error-prone.
- High update frequency — monthly releases required full regression on core banking flows plus new promotional features.
- Limited test coverage — network-sensitive features like mobile-check deposit and biometric login were hard to verify reliably in-house.
- Slow feedback loop — end-to-end QA cycles stretched to five days, delaying production pushes.
1 Framework selection & architecture
- Adopted Appium (Java client) for true cross-platform mobile automation.
- Structured suites with TestNG to parameterise devices and enable parallel runs.
- Implemented a Page Object Model for Login, Dashboard, Payments, Deposit and Settings screens.
2 Cloud-device integration
- Connected tests to BrowserStack Automate for on-demand access to real devices.
- Built Android and iOS device pools that cover 90 % of the active user base (OS versions + screen sizes).
3 CI/CD & parallel execution
- Embedded execution in Jenkins pipelines, triggered on every commit to the develop branch.
- Leveraged TestNG parallelism with BrowserStack concurrency to run 30 tests simultaneously, cutting a full regression from five hours to under 40 minutes.
4 Reporting & monitoring
- Streamed live videos, logs and screenshots to the BrowserStack dashboard for instant triage.
- Aggregated TestNG results into Allure reports, auto-published to the internal QA portal for total visibility.
Outcomes & Benefits
- Dramatic Test Speed-Up: regression suite now runs in 40 minutes vs 5 hours, enabling daily test executions.
- Device Coverage Increase: automated suites run across 25 real devices in parallel, covering 95 % of active user environments.
- Defect Reduction: 50 % fewer post-release defects on critical flows (login, transfers, deposits).
- Cost Efficiency: retired the in-house device lab, reducing hardware and maintenance costs by 30 %.
- Faster Time-to-Market: release cycles shortened from monthly to bi-weekly while preserving app stability.
