Artemis needs comprehensive sorting, categorizing, and visualizing of test case failures during grading, hindering instructors’ ability to gain a high-level overview of feedback and understand the cause of errors in student submissions. To ensure a high-level overview, this thesis aims to enhance Artemis by improving the feedback sorting, categorizing, and visualization functionalities.
The methodology involves collecting and sorting various types of errors encountered after running test cases, then categorizing and presenting them visually within the Artemis platform. Presenting this data visually allows for planning strategies to improve the quality of feedback from test cases. Improved feedback quality helps instructors inform students of specific error types, reducing complaints and enabling timely tracking of student progress through a transparent, categorized overview of common errors. The objective is to streamline the error analysis process within Artemis, ensuring its functionality and usability meet the evolving needs of instructors and students.