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Exploring Automated Assessment of Scalable Web Applications
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Perustieteiden korkeakoulu |
Master's thesis
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SCI3084
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en
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50
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Abstract
The World Wide Web (Web) has become an integral part of our daily lives, spanning diverse areas such as entertainment, education, health care, and transportation. Web applications, which power a significant portion of the Web, are utilized by hundreds of millions of people globally. Therefore, these applications must be able to scale in response to increased traffic. Accordingly, the development of scalable web applications is a common component of many computer science curricula.
Typically, these web application scalability courses feature practical exercises with automated tests to verify the functionality requirements of the submissions. For example, Aalto University’s Designing and Building Scalable Web Applications course offers students both theoretical insights and practical experience in web application scalability techniques. However, these courses lack mechanisms for automatically assessing the scalability of the submitted applications. This thesis explores the feasibility of automatically testing and grading scalable web applications.
This thesis began with the investigation of current automated assessment methodologies and solutions. Then, based on Aalto University’s scalable web application course, the most suitable methods for scalability assessment were selected. Lastly, a Proof of Concept (PoC) testing framework was developed, which can automatically assess the scalability of Kubernetes-based assignment submissions. This framework first assesses the baseline infrastructural state of the submitted application and then generates an increased load for it. Then, it again examines the infrastructural state and verifies if the application properly scales in response to the generated load.
The findings reveal that this thesis fills a gap in current research because previous works on automated assessment do not focus on the scalability aspects of web applications. Regarding the techniques, combining infrastructure testing with load generation proves to be a feasible method for testing the scalability of web applications deployed on Kubernetes. This framework provides educators a viable approach for automated assessment in educational settings, and for industry practitioners, it serves as a model for testing real-life web applications.