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Assessing Software Quality of Agile Student Projects by Data-mining Software Repositories

 
: Kötter, Falko; Kochanowski, Monika; Kintz, Maximilien; Kersjes, Benedikt; Bogicevic, Ivan; Wagner, Stefan

:

Lane, H. (Ed.) ; Institute for Systems and Technologies of Information, Control and Communication -INSTICC-, Setubal:
11th International Conference on Computer Supported Education, CSEDU 2019. Proceedings. Vol.2 : May 2-4, 2019, Heraklion, Crete, Greece
SciTePress, 2019
ISBN: 978-989-758-367-4
S.244-251
International Conference on Computer Supported Education (CSEDU) <11, 2019, Heraklion>
Englisch
Konferenzbeitrag
Fraunhofer IAO ()

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.

: http://publica.fraunhofer.de/dokumente/N-552265.html