Daniel Bruzual, Maria L. Montoya Freire, M. D. Francesco
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Automated Assessment of Android Exercises with Cloud-native Technologies
Mobile applications are very challenging to test as they usually have a complex graphical user interface and advanced functionality that involves interacting with remote services. Due to these features, student assessment in courses about mobile application development usually relies on assignments or projects that are manually checked by teaching assistants for grading. This approach clearly does not scale to large classrooms, especially for online courses. This article presents a novel system for automated assessment of Android exercises with cloud-native technologies. Different from the state of the art, the proposed solution leverages a mobile app testing framework that is largely used in the industry instead of custom libraries. Furthermore, the devised system employs software containers and scales with the availability of resources in a data center, which is essential for massive open online courses. The system design and implementation is detailed, together with the results from a deployment within a master-level course with 120 students. The received feedback demonstrates that the proposed solution was effective, as it provided insightful feedback and supported independent learning of mobile application development.