Nataliya Yatskiv

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Total Citations

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About

Nataliya Yatskiv is a researcher whose work sits at the dynamic intersection of software testing, robotic process automation (RPA), and artificial intelligence. Her research addresses one of the most pressing challenges in modern software engineering: the efficient automation of repetitive, time-consuming testing processes that traditionally demand significant human resources. Through her highly cited contributions, Yatskiv has made meaningful strides in advancing how organizations approach software quality assurance. Her 2019 paper, "Improved Method of Software Automation Testing Based on the Robotic Process Automation Technology," garnered 35 citations and introduced novel approaches to leveraging RPA to overcome the inherent limitations of conventional automation testing frameworks. Building on this foundation, her 2020 follow-up work, "Method of Robotic Process Automation in Software Testing Using Artificial Intelligence," which earned 32 citations, pushed the boundaries further by integrating AI capabilities to expand RPA's functionality beyond its traditional constraints. Together, these works reflect Yatskiv's commitment to bridging practical industry needs with innovative technological solutions. Her research has resonated strongly within the software engineering community, offering actionable methodologies that help organizations reduce costs, optimize human capital, and enhance the reliability of their software systems without requiring disruptive changes to existing processes.