Marina Cernat

Papers

Total Citations

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About

Marina Cernat is a software engineering researcher whose work sits at the intersection of test automation and Robotic Process Automation (RPA), a rapidly growing field focused on automating repetitive digital workflows. Her research addresses a critical and often overlooked challenge in the software development lifecycle: ensuring the quality and reliability of RPA implementations through rigorous, automated testing methodologies. Her most cited work, "Improving UI Test Automation using Robotic Process Automation" (2020, 22 citations), explores how RPA technologies can themselves be leveraged to enhance the effectiveness of user interface testing — a creative and practical contribution that bridges two complementary domains. Her complementary paper, "Towards Automated Testing of RPA Implementations" (2020, 14 citations), tackles the inverse problem, examining how traditional testing approaches must evolve to adequately validate RPA processes, recognizing that classical testing methods are insufficient for this emerging paradigm. Together, these works reflect Cernat's commitment to advancing quality assurance practices in modern software engineering. Her research is particularly valuable for practitioners and academics navigating the challenges of deploying reliable automation solutions at scale, making her an important voice in the evolving conversation around intelligent process automation and software quality.