John Doe

John Doe Mobile Test Engineer

Appium · XCUITest · Espresso · Java · Kotlin · TestNG · Cucumber · Selenium · Jenkins · Git · CI/CD · AWS Device Farm

Education

Senior Mobile Test Engineer @ Google June 2022 – Present

Architected and implemented a cross-platform mobile test framework using Appium, XCUITest, and Espresso, increasing UI coverage by 45% and reducing critical bugs in production by 30%.
Integrated automated test suites into Jenkins pipelines and Google’s internal device lab, cutting end-to-end regression runtime by 40%.
Introduced data-driven test design and self-healing retry logic that decreased flaky test failures by 50%.
Mentored a team of 4 SDETs on best practices for mobile automation, BDD with Cucumber, and parallel test execution.

Mobile Testing Consultant @ OpenAI December 2020 – Present

Designed and executed automated UI and performance tests for a biometric training simulation app using Appium and XCUITest, ensuring 99% stability under concurrent user loads.
Built an Espresso-based Android test suite that caught 95% of critical UI regressions before release.
Automated test data generation and integrated with CI/CD workflows, reducing manual testing effort by 60%.
Conducted root-cause analysis of recurring test failures and implemented corrective actions, improving overall suite reliability.

Developed a modular test framework in Java and Kotlin leveraging Appium, XCUITest, and Espresso.
Implemented a plugin architecture for custom locators, logging, and reporting with TestNG and Allure.
Enabled parallel, containerized test execution on local emulators and cloud device farms.

Created load and stress test scenarios in Espresso to simulate 10,000+ daily users, uncovering memory leaks and UI jank issues.
Automated capturing of CPU, memory, and network metrics, feeding results into Grafana dashboards for real-time monitoring.

Guest Lecture: Mobile Automation Testing Big Data & Machine Learning for Scientific Discovery (PHYS 5336) – Spring 2021
Workshop: Advanced Appium Strategies SDET Summit – Fall 2020
Seminar: Self-Healing Test Automation Software Test Architect Community Meetup – Summer 2020

Doe, J.; Lee, S.; Kumar, A. “AI-Driven Anomaly Detection in Mobile UI Test Automation.” Journal of Software Testing and Verification, Vol. 15, No. 2 (2023), pp. 112–128. https://doi.org/10.1007/s11219-023-0856-2
Doe, J.; Chen, L.; Patel, R. “Self-Healing Mechanisms for Cross-Platform Mobile Automation Frameworks.” IEEE Transactions on Software Engineering, Vol. 49, No. 1 (2024), pp. 34–47. https://doi.org/10.1109/TSE.2024.3021147
Doe, J.; Ochoa, M.; Zhang, Y. “Parallel Espresso and XCUITest Execution on Cloud Device Farms.” Proceedings of ICST 2023, pp. 210–219. https://doi.org/10.1109/ICST.2023.00034
Doe, J.; Santos, F. “Data-Driven Test Case Generation Using Deep Neural Networks.” Journal of Automated Software Engineering, Vol. 31, No. 4 (2023), pp. 257–276. https://doi.org/10.1007/s10515-023-00321-4
Doe, J.; Nguyen, T.; Fernández, R. “Performance Profiling and Bottleneck Analysis in Mobile Applications with Espresso.” ACM Transactions on Software Engineering and Methodology, Vol. 32, No. 1 (2024), pp. 5:1–5:23. https://doi.org/10.1145/3571120
Doe, J.; Roberts, K. “Hybrid Orchestration of Appium and XCUITest for End-to-End Mobile Testing.” In: AIOpsTest 2022 Workshop, pp. 58–66. PMID: 35789012