Shuo-Han Chen

National Taipei University of Technology

Papers

Total Citations

H-Index

About

Shuo-Han Chen is a researcher at the forefront of software testing and test automation, with a particular focus on enhancing the efficiency and accessibility of automated test development. His key research areas include keyword-driven testing frameworks, test case generation, and the automation of manual testing processes. Chen’s most notable contribution is his work on developing an automation tool that converts natural language test steps into executable keywords for the Robot Framework—a widely adopted, Python-based test automation platform. This innovation significantly lowers the barrier for testers and developers, enabling them to create robust, reusable test scripts without deep programming expertise. While his 2024 paper has garnered initial citations, reflecting growing interest in practical test automation solutions, Chen’s work addresses a critical bottleneck in software quality assurance: the time-consuming transition from manual to automated testing. His research promises to streamline acceptance test-driven development (ATDD) workflows, making automated testing more intuitive and scalable. For students and researchers exploring software engineering and quality assurance, Chen’s contributions offer a compelling bridge between theoretical automation concepts and real-world, industry-ready tools.