Authors:
Falko Koetter
1
;
Monika Kochanowski
1
;
Maximilien Kintz
1
;
Benedikt Kersjes
2
;
Ivan Bogicevic
2
and
Stefan Wagner
2
Affiliations:
1
Fraunhofer Institute of Industrial Engineering, Nobelstr. 12, Stuttgart and Germany
;
2
Institute of Software Technology, University of Stuttgart, Universitätsstr. 38, Stuttgart and Germany
Keyword(s):
Software Quality, Data-mining, Software Development, Project-based Learning, Metrics, Student Project.
Related
Ontology
Subjects/Areas/Topics:
Computer-Supported Education
;
Learning/Teaching Methodologies and Assessment
;
Metrics and Performance Measurement
;
Project Based Learning and Engineering Education
Abstract:
Group student software projects are important in computer science education. Students are encouraged to self-organize and learn technical skills, preparing them for real life software development. However, the projects contribute to multiple learning objectives, making coaching students a time consuming task. Thus, it is important to have a suitable best practice development process. For providing better insights for the students, the resulting software has to be of value and meet quality requirements, including maintainability, as in real life software development. Using source code quality metrics and by data mining repository data like commit history, we analyze six student projects, measuring their quality and identifying contributing factors to success or failure of a student project. Based on the findings, we formulate recommendations to improve future projects for students and researchers alike.