Nadia Ellyani Azis

Papers

Total Citations

H-Index

About

Nadia Ellyani Azis is a researcher focused on software engineering and quality assurance, with a particular emphasis on software testing automation and its application in smart manufacturing. Her work addresses the critical challenge of manual software testing inefficiencies in the era of emerging technologies. Azis’s most cited paper, "Software Testing Automation: A Comparative Study on Productivity Rate of Open Source Automated Software Testing Tools For Smart Manufacturing" (2020), systematically evaluates how open source automation tools can enhance productivity for software test engineers. By comparing tools in terms of test planning, execution, and reporting, she provides actionable insights for project teams seeking to streamline testing processes. This study, with 7 citations, highlights her contribution to bridging the gap between traditional testing methods and the demands of Industry 4.0. Her research is particularly valuable for practitioners and researchers looking to adopt cost-effective, scalable solutions in automated testing. Azis’s work underscores the practical benefits of open source tools, offering a roadmap for improving software quality in manufacturing contexts. Her findings continue to inform best practices in software testing automation, making her a notable voice in the field of software engineering.