Abstract

Test automation tool selection is usually reported as a feature checklist for one technology, most often web UI automation. That framing does not fit enterprise financial-services environments, where a single quality-assurance function must validate a mainframe policy administration system, a web-based new-business workflow, a native mobile application, an ACORD TX103 XML messaging layer, and the Oracle/DB2 databases underneath them. This paper presents a framework for evaluating and migrating automation from a licensed tool (UFT One) to a single codeless platform (accelQ) across these five layers. The framework has two parts: (i) a layer-by-layer evaluation that tests licensing cost, coverage, codeless authoring, and self-healing claims against each technology layer separately, and (ii) a five-phase, gate-controlled migration method that uses risk-based prioritization, per-layer pilots, parallel-run UFT-versus-accelQ outcome comparison, and staged license retirement, so that automated coverage never drops below its pre-migration level. The framework is evaluated on an industrial insurance platform using four research questions covering cost, coverage parity, authoring and maintenance effort, and adoption. Practitioners can reuse the method for any tool-to-tool automation migration.

References

• OpenText. 2024. UFT One Help Center: Terminal Emulator Add-in and API Testing. OpenText Corporation. https://admhelp.microfocus.com/uft/
• accelQ Inc. 2026. accelQ Platform Overview: Web, Mobile, API, Desktop and Mainframe Automation. https://www.accelq.com/product
• ACORD. ACORD Life & Annuity Standards: TX103 New Business Submission Transaction. ACORD Corporation.
• TestGrid. POC in Testing: A Complete Guide to Proof of Concept for Automation. TestGrid blog.
• Song, R. Cypress to Playwright Migration Guide. In Proceedings of the Pacific Northwest Software Quality Conference (PNSQC), 339–348.
• Martins, G., Tenório, N., and Bernardino, J. 2026. AI-Driven Software Testing: A Review. Big Data and Cognitive Computing 10, 7, Article 233. DOI: 10.3390/bdcc10070233.
• Gatla, G., Gatla, K., and Gatla, B. V. 2023. Codeless Test Automation for Development QA. American Scientific Research Journal for Engineering, Technology, and Sciences 91, 1, 28–35.
• De Reanzi, S. R. and Thangaiah, P. R. J. 2021. A survey on software test automation return on investment, in organizations predominantly from Bengaluru, India. International Journal of Engineering Business Management. DOI: 10.1177/18479790211062044.
• Chiranjeevi Partha Saarathy, S., Bathrachalam, S., and Rajendran, B. K. 2024. Self-Healing Test Automation Framework using AI and ML. International Journal of Strategic Management 3, 3, 45–77. DOI: 10.47604/ijsm.2843.
• Gojare, S., Joshi, R., and Gaigaware, D. 2015. Analysis and Design of Selenium WebDriver Automation Testing Framework. Procedia Computer Science 50, 341–346. DOI: 10.1016/j.procs.2015.04.038.
• García, B., Muñoz-Organero, M., Alario-Hoyos, C., and Delgado Kloos, C. 2021. Automated driver management for Selenium WebDriver. Empirical Software Engineering 26, 5, Article 107. DOI: 10.1007/s10664-021-09975-3.
• Shuaibu, I., Machina, M. M., and Ibrahim, M. 2019. Investigation onto the Software Testing Techniques and Tools: An Evaluation and Comparative Analysis. International Journal of Computer Applications 177, 23, 24–30. DOI: 10.5120/ijca2019919685.
• Selenium Project. 2026. Selenium WebDriver Documentation. https://www.selenium.dev/documentation/webdriver/
• Microsoft. 2026. Playwright Documentation: API Testing and Mobile Emulation. https://playwright.dev/docs/intro
• Appium Project. 2026. Appium Documentation. https://appium.io/docs/