Solomiya Yatskiv

Papers

Total Citations

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About

Solomiya Yatskiv is a researcher specializing in software testing automation, robotic process automation (RPA), and the integration of artificial intelligence into quality assurance workflows. Her work addresses a critical challenge in modern software engineering: the inefficiency of repetitive, time-consuming testing tasks and the limitations of conventional automation frameworks. Yatskiv's most influential contributions center on advancing RPA methodologies within software testing environments. Her 2019 paper, "Improved Method of Software Automation Testing Based on the Robotic Process Automation Technology," which has garnered 35 citations, introduced innovative approaches to overcome the functional constraints that traditional automation tools impose when tightly coupled to the system under test. Building on this foundation, her 2020 follow-up study, "Method of Robotic Process Automation in Software Testing Using Artificial Intelligence," with 32 citations, pushed the boundaries further by demonstrating how AI can expand and enhance RPA capabilities, enabling smarter, more adaptable testing solutions that reduce costs and optimize human resource allocation. Together, these works have established Yatskiv as a notable voice in the evolving intersection of intelligent automation and software quality assurance, offering practical frameworks that resonate with both industry practitioners and academic researchers exploring next-generation testing methodologies.