Automated Computer Program Evaluation and Projects -- Our Experiences

TL;DR

This work examines scalable automation of programming laboratories and project submissions in CS education using CodeRunner autograding integrated with Moodle and GitHub Classroom for submissions. It details a two-server CR–Moodle deployment with sandboxing and offline-capable configurations, plus a template-driven, test-case–based workflow in GHC for programming labs and team projects. The authors provide concrete setup guidelines, starter templates, and test-case strategies, along with practical insights on benefits and challenges such as plagiarism and faculty training. Collectively, the approach reduces manual grading, provides immediate feedback, and fosters industry-relevant practices through open-source tooling and repository-based collaboration.

Abstract

This paper provides a few approaches to automating computer programming and project submission tasks, that we have been following for the last six years and have found to be successful. The approaches include using CodeRunner with Learning Management System (LMS) integration for programming practice and evaluation, and Git (GitHub) for project submissions and automatic code evaluation. In this paper, we describe the details of how we set up the tools and customized those for computer science courses. Based on our experiences, we also provide a few insights on using these tools for effective learning.

Figures (14)

• Figure 1: Setup of Moodle and CodeRunner
• Figure 2: Customization through domain address
• Figure 3: CodeRunner - Adding Question
• Figure 4: Evaluation with CR
• Figure 5: Creation of Organization in GH