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Improving the Scalability and Security of Execution Environments for Auto-Graders in the Context of MOOCs

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dc.contributor.authorSerth, Sebastian
dc.contributor.authorKöhler, Daniel
dc.contributor.authorMarschke, Leonard
dc.contributor.authorAuringer, Felix
dc.contributor.authorHanff, Konrad
dc.contributor.authorHellenberg, Jan-Eric
dc.contributor.authorKantusch, Tobias
dc.contributor.authorPaß, Maximilian
dc.contributor.authorMeinel, Christoph
dc.contributor.editorGreubel, André
dc.contributor.editorStrickroth, Sven
dc.contributor.editorStriewe, Michael
dc.date.accessioned2021-11-15T05:03:40Z
dc.date.available2021-11-15T05:03:40Z
dc.date.issued2021
dc.description.abstractLearning a programming language requires learners to write code themselves, execute their programs interactively, and receive feedback about the correctness of their code. Many approaches with so-called auto-graders exist to grade students' submissions and provide feedback for them automatically. University classes with hundreds of students or Massive Open Online Courses (MOOCs) with thousands of learners often use these systems. Assessing the submissions usually includes executing the students' source code and thus implies requirements on the scalability and security of the systems. In this paper, we evaluate different execution environments and orchestration solutions for auto-graders. We compare the most promising open-source tools regarding their usability in a scalable environment required for MOOCs. According to our evaluation, Nomad, in conjunction with Docker, fulfills most requirements. We derive implications for the productive use of Nomad for an auto-grader in MOOCs.en
dc.identifier.doi10.18420/abp2021-1
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/37539
dc.language.isoen
dc.relation.ispartofProceedings of the Fifth Workshop "Automatische Bewertung von Programmieraufgaben" (ABP 2021),virtual event, October 28-29, 2021
dc.relation.ispartofseriesWorkshop „Automatische Bewertung von Programmieraufgaben“
dc.subjectAuto-Grader
dc.subjectScalability
dc.subjectMOOC
dc.subjectProgramming
dc.subjectSecurity
dc.subjectExecution
dc.titleImproving the Scalability and Security of Execution Environments for Auto-Graders in the Context of MOOCsen
dc.typeText/Conference Paper
gi.conference.sessiontitleVollbeiträge „Architekturen für die automatische Bewertung“

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