ANALYZING GIT LOG IN AN CODE-QUALITY AWARE AUTOMATED PROGRAMMING ASSESSMENT SYSTEM: A CASE STUDY

Abstract

Automated programming assessment systems have transformed the evaluation of programming assignments, providing detailed feedback and reducing instructors' workload. This paper explores the benefits of Git log analysis in ProgEdu, a code-quality aware automated programming assessment system. ProgEdu was utilized for assessing Java homework assignments and web programming projects over two semesters. The integration of Git log analysis in ProgEdu highlights its potential in tracking student progress, predicting performance, determining student groups based on submission behaviors, identifying inequality in group projects, and facilitating instructors' intervention. The study emphasizes the importance of enhancing software industrial practices in programming courses, including code version control, static code quality checking, unit testing, and automation tools. By incorporating these practices, students benefit from hands-on learning and situated learning experiences. Embracing these practices enhances the learning experience, improves student performance, and fosters a collaborative programming environment. It highlights the benefits for students and instructors, urging institutions to invest in software industrial practices and demonstrating the potential impact on programming education.