Nur Diyana Joha

Papers

Total Citations

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About

Nur Diyana Joha is a researcher whose work sits at the intersection of software engineering and smart manufacturing, with a particular focus on software testing automation. Her most-cited paper, “Software Testing Automation: A Comparative Study on Productivity Rate of Open Source Automated Software Testing Tools For Smart Manufacturing” (2020), has garnered 7 citations, establishing her as a thoughtful voice in the ongoing effort to modernize quality assurance. In this study, Joha directly addresses a critical pain point for project teams: the inefficiency of manual testing in the face of rapid technological change. By systematically comparing open-source automation tools, she provides actionable insights into how software test engineers can improve productivity in test planning, creation, execution, and reporting. Her work is especially relevant for smart manufacturing environments, where software reliability is paramount. Joha’s contribution lies not just in her comparative analysis, but in her practical, industry-oriented approach—she bridges the gap between academic research and real-world engineering challenges. For students and researchers exploring test automation, her findings offer a clear, evidence-based roadmap for tool selection, making her a valuable guide in the quest for more efficient, scalable software testing.