Empirical Evaluation of Transforming Traditional Programming Laboratories into PaaS-Based Environments Using CloudBees

Authors

  • Hassan KH Mohamed Department of Computer Science, Faculty of Arts and Sciences – Sluk, University of Benghazi, Sluk, Libya Author

DOI:

https://doi.org/10.65420/sjphrt.v1i2.57

Keywords:

Cloud Computing, Platform as a Service (PaaS), Programming Laboratories, Empirical Evaluation, System Responsiveness, Cost Model

Abstract

The rapid evolution of cloud computing has fundamentally transformed the provisioning and consumption of computational resources in higher education institutions. Traditional programming laboratories require continuous investment in hardware, licensed software, and technical maintenance, which often limits their scalability and long-term sustainability. This study presents a controlled empirical evaluation of transforming traditional programming laboratories into Platform as a Service (PaaS)-based environments using CloudBees. The evaluation focuses on two critical quality attributes: system responsiveness and cost efficiency. A cross-over experimental design was conducted with 40 undergraduate students enrolled in an Object-Oriented Programming course. System responsiveness was assessed using task completion time and the Application Performance Index (Apdex), while cost efficiency was evaluated through a structured per-student cost model. The results indicate that PaaS-based programming laboratories significantly improve responsiveness and achieve notable cost reductions, approximately 28% per student, when compared to traditional laboratory environments. These findings provide empirical evidence supporting the feasibility and effectiveness of adopting cloud-based, PaaS-oriented programming laboratories in higher education institutions.

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Published

2025-12-31

Issue

Section

Articles

How to Cite

Empirical Evaluation of Transforming Traditional Programming Laboratories into PaaS-Based Environments Using CloudBees. (2025). Scientific Journal for Publishing in Health Research and Technology, 1(2), 334-341. https://doi.org/10.65420/sjphrt.v1i2.57