Automated Testing Platform for Samsung
Samsung
Samsung Mobile needed to optimize its validation processes for new devices, particularly on functional and regression testing before each release. QA teams spent weeks on repetitive manual tests: running the same scenarios on dozens of different models, across multiple firmware versions, in multiple languages, with traceability required for every detected anomaly. As the product catalog grew, the cost of manual validation became unsustainable and time-to-market suffered. We were asked to design a platform capable of creating, executing and monitoring test scenarios at scale, directly integrated with the existing CI/CD pipeline, so that each new firmware version would automatically trigger the right test battery on the right devices.
The main challenge was not making an isolated automated test work, it was mastering the scale and complexity specific to a global manufacturer. We had to understand Samsung-specific validation workflows, the multiple levels of internal acceptance, the very strict security constraints imposed on pre-release firmware (none of which can leave a controlled environment), and integrate the platform into an existing CI/CD ecosystem without disrupting current release cycles. Add to that the need to support thousands of scenarios executed in parallel on physical and virtual test benches, with fine-grained verdict management and structured escalation of anomalies to the relevant development teams. Everything had to be documented, auditable and usable by QA teams who are not all developers.
We designed an automated testing platform with a scenario creation interface accessible to QA teams without requiring advanced development skills, massively parallel execution on test benches, real-time reporting and native integration with Samsung's CI/CD pipeline. The architecture was designed from the start to support thousands of parallel tests, with rigorous management of shared resources (physical devices, virtual environments, software licenses) and a prioritization system allowing critical releases to jump the queue. Results are consolidated in clear dashboards for QA managers and targeted alerts are sent directly to the development teams concerned by each anomaly. The platform was gradually deployed on several products to validate scaling, then extended to the entire catalog, with documentation and training for internal teams to ensure long-term autonomy.
Results
"This application has transformed the way we work. We detect issues much earlier in the development cycle."
Tech Lead
Samsung Mobile